VOLUME 11, ISSUE 5, MAY 2024

Abstract: During this pandemic, the majority of people's health care requires medication and doctor's recommendations to improve and safeguard their health. Also, I've observed numerous incidents when many people have been afflicted with COVID. To limit physical contact and prevent the spread of infections, the recommended methodology is to introduce a personalised healthcare chatbot in hospitals. A personalised healthcare chatbot is one that uses natural language processing (NLP) in text format. AI and Deep Learning for Medical Diagnostics help to power a personalised healthcare chatbot. The project's purpose is to develop a personalised healthcare chatbot that overcomes the recommended technique. Many people were unable to see doctors for minor ailments like a cold or fever.

Keywords: Personalized healthcare, NLP, Chatbot

Abstract: The study aimed to explore challenges encountered by dried fish processors and owners across processing, production, and marketing aspects of the industry. Quantitative methods were employed exclusively for data analysis. A total of 100 participants took part, including dried fish processors, owners, barangay officials, and coastal barangay residents. Mean scores were utilized to analyze quantitative data, revealing various challenges such as technical assistance and sanitation issues, lack of high-technology equipment, insufficient training seminars, improper handling techniques, limited storage facilities, and financial constraints faced by dried fish processors and owners in the industry.

Keywords: Challenges, Processing, Production, And Marketing. Downloads: | DOI: 10.17148/IARJSET.2024.11501 How to Cite: [1] ISABEL E. CABUGAO, "Challenges in the Processing, Production, and Marketing of the Dried Fish Industry," International Advanced Research Journal in Science, Engineering and Technology (IARJSET), DOI: 10.17148/IARJSET.2024.11501 Copy Citation

Abstract: This study explores high-performance concrete (HPC) focusing on workability, durability, and strength. A total of 1050 cubes were tested with various curing mediums like fresh water and chlorine to assess the effects of Chikoko, an admixture, on concrete containing uniformly or well-graded sand as fine aggregates. Multiple regression analysis was used to optimize the calcination temperature and admixture concentration of pulverized Chikoko in M25 concrete, with uniformly graded Abraka sand as the fine aggregate. The study found a quadratic relationship between admixture concentration (0-20%), with 10% CPC being the optimal level. The compressive strength of pulverized sand concrete improved significantly at this concentration, nullifying the strength advantage of natural sand over pulverized sand. The study also determined independent variables for optimization, resulting in notable improvements in chloride attack resistance and compressive strength compared to the natural sand control group. The research suggests that CPC-NS concrete meets high-performance concrete standards for strength and durability, while CPC-PS concrete can be used to make standard-strength concrete in areas without well-graded sands.

Keywords: High-performance concrete, Chikoko admixture, durability, compressive strength, chloride attack.

Abstract: Hydrate formation in subsea pipelines poses significant challenges to flow assurance and operational safety. This paper takes a look at gas hydrate inhibition in a simulated offshore environment using silicon oxide nanoparticles and aluminium oxide nanoparticles as inhibitors. The essence of this work is to compare the effectiveness of silicon oxide nanoparticles and aluminium oxide nanoparticles for hydrate inhibition. Experiments were conducted using a mini flow loop. It will involve mitigating hydrate formation using varying weight percentages of the inhibitors (0.01wt%, 0.02wt %) and then evaluate their effect on hydrate inhibition in the mini flow loop. Sensitivity charts for pressure, temperature and time both nanoparticles were made. From the analysis, 0.01 weight percentages of silicon oxide nanoparticles has close match with 0.01 weight percentage of aluminium oxide nanoparticles, and 0.02 weight percentage silicon oxide nanoparticles showed better inhibitory capacity than aluminium oxide nanoparticles of 0.02 weight percentage.

Keywords: Gas hydrate, silicon oxide nanoparticles, aluminium oxide nanoparticles, simulated offshore environment

Abstract: The most efficient way to dry paint is by using hot air, which applies to any printing process, including silkscreen printing. This study used the developmental method of research. A researcher-made evaluation sheet adopted from the study of Ledesma (2020) [1] was used. However, some items were modified to answer some of the parameters included in this study. The main objective of the study was to fabricate a hot air silkscreen printing dryer. It effectively dried 10 pcs A4 size prints, 20 pcs 3"x 9" size prints, and 60 pcs 2.75" logo size prints per loading in varying times. The shortest drying time for A4 size prints was 3 minutes, and for 3"x 9" and 2.75" sizes was one minute. The device consumes 0.0833 KwHr with a computed cost of Ᵽ1.0629 per minute of operation. Results also showed that the composition, fabrication, features, operating performance, and safety of the device were "Very Acceptable".

Keywords: hot air, drying device, silkscreen printing, operating performance

Abstract: The goal of this project is to create an Internet of Things (IoT) system that will enable consumers to utilize an Android application to control smart lighting in their homes. The system is made up of a number of parts, including Microcontroller Units (MCUs), user-friendly Android apps, and intelligent LED lightbulbs. A number of capabilities are available with the system, such as group control, scheduling, scene creation, brightness and color changes, and on/off control. Convenience, energy economy, enhanced security, better ambience, and accessibility are some advantages of this technology. The Android app must be developed, a communication protocol must be put in place, hardware must be chosen, the system must be tested, and it must be refined. Customers may easily regulate their home lighting with this technology, adding to the enjoyment of owning a smart home.

Keywords: Android app, smart light, Microcontroller Unit (MCU), hardware selection, communication protocol.

Abstract: The protection of betel nut trees is of paramount importance in agricultural practices, especially in regions where betel nut cultivation is a significant source of livelihood. However, ensuring the safety and well-being of these trees amidst environmental challenges such as heavy rainfall, sudden changes in light intensity, and fire outbreaks poses a considerable challenge to farmers. Traditional methods of protection often involve manual monitoring, which is labor intensive and may not guarantee timely intervention. To address these challenges, this project proposes an innovative Betel Nut Protection System that integrates various sensors, Arduino-based automation, and GSM technology to enhance the responsiveness and effectiveness of betel nut tree protection. The system aims to provide real-time detection of environmental factors and trigger appropriate responses, such as closing protective curtains and sending SMS alerts to farmers, even when they are off-site. By leveraging advanced technology, the proposed system seeks to revolutionize betel nut cultivation practices, ensuring the sustainability and productivity of this vital agricultural sector.

Abstract: This paper proposes the implementation of a system called Summer-Riser, which is an automated text summarization bot using Natural Language Processing (NLP) approaches. This paper provides a complete explanation of how the system works and gives responses to its use. The bot works based on taking the URL as user input, extracting the text, preprocessing the text, and providing the answer to the question asked by the user by summarizing the text. The paper will help both commoners and technically skilled people and researchers to understand how the NLP approaches can be used to develop a text summarization model. The authors have provided an in-depth explanation regarding the models like langchain etc. used to develop the system and various current trends in the field of NLP.

Keywords: Text Summarization, Natural Language Processing (NLP) and langchain

Abstract: Blockchain technology is a decentralized and distributed digital ledger system that records transaction across a network of computers. It consists of chain of blocks, each containing a list of data that are linked together in a chronological and unchangeable chain. Blockchain ensures transparency, security, tamper-resistant, consensus mechanisms and immutability of data. A decentralized voting system using blockchain technology is an innovative approach to improve the integrity, security and trustworthy electoral process.

Keywords: E-polling, voting system, blockchain application, blockchain voting, E-voting, electoral system, blockchain, cryptographic hash, secure voting. Downloads: | DOI: 10.17148/IARJSET.2024.11508 How to Cite: [1] Keerthi Prada S, Meghana K S, Nagashree M N, Nikhita A N, Ashwini M S, "Blockchain Powered Decentralized Voting System," International Advanced Research Journal in Science, Engineering and Technology (IARJSET), DOI: 10.17148/IARJSET.2024.11508 Copy Citation

Abstract: This research presents an innovative approach to assist people with visual impairments by merging both recognition of objects and currency detection through YOLO (You Only Look Once) model. This model, renowned for its real-time detection of object capabilities, is adapted to identify both objects and currency notes in live camera feeds. Using computer vision and deep learning, the system provides instant auditory guidance to help visually impaired individuals recognize and handle currency notes better. This implementation seeks to enhance the independence and accessibility of visually impaired people across different situations. The results from experiments confirm the precision and efficacy of this approach in recognizing objects and currency notes in real-world scenarios.

Keywords: YOLO, Object Recognition

Abstract: This research paper investigates the impact of project-based learning (PBL) on student engagement, skill development, and academic success. Emphasizing the multifaceted advantages of PBL, we explore its role in fostering critical thinking, collaboration, and real-world application of knowledge. Through a comprehensive review of literature, empirical evidence, and case studies, the study aims to provide a nuanced understanding of how PBL enhances academic performance and cultivates essential life skills. By examining various models, best practices, and challenges associated with PBL implementation, the paper contributes valuable insights to educators, policymakers, and researchers. Advocating for the integration of project-based learning into modern education, this research supports its role as an indispensable component.

Keywords: project-based learning, academic performance, student engagement

Abstract: This research paper explores the perceptions of teachers regarding the integration of Artificial Intelligence (AI) tools in student homework assignments. As education continues to evolve in the digital age, the incorporation of AI into assessment practices has gained attention. This study aims to understand how teachers view the use of AI tools in assessing and enhancing the learning experience through homework assignments. Through a comprehensive examination of teachers' perspectives, this research provides insights into the potential benefits and challenges associated with the integration of AI tools in the assessment process.

Keywords: artificial intelligence, assessment process, homework assignment

Abstract: KarmikConnect is a new app that makes it easier for daily wage workers to find jobs. It acts like a simple and clear meeting place for workers and employers. Employers can post detailed job ads, and workers can show interest easily. This app helps bridge the gap between workers and employers, making the whole process more transparent and efficient. It even has a document verification so the employer can build trust over the worker. Plus, it's handy for contractors too, helping them manage their workers better. Overall, KarmikConnect aims to make finding work simpler and help businesses run more smoothly. This app is easy to process and also user friendly.

Keywords: KarmikConnect, daily wages worker, streamlined interface, contractor, user friendly.

Abstract: The concept of a "personal virtual doctor" refers to an innovative approach in healthcare that utilizes virtual or digital technologies to provide personalized and accessible medical guidance and support. This virtual doctor operates in a digital realm, machine learning, and advanced algorithms to interact with users in a manner like a human healthcare provider. Analyzes data to provide insights into the user's health status and potential areas for improvement. In the realm of technological innovation, the convergence of machine learning and healthcare has led to the development of a groundbreaking solution - the Personal Virtual Doctor. This project harnesses the capabilities of machine learning in Python to create an advanced system capable of predicting diseases based on user-input symptoms. Augmented by a sophisticated healthcare chatbot, the application offers an interactive platform for users to describe their symptoms and receive real time information about potential health issues. With a user-friendly interface and a commitment to privacy and security, this project signifies a transformative leap towards a more informed and proactive approach to personal health. The Personal Virtual Doctor is poised to revolutionize healthcare, empowering individuals to take charge of their well-being through the amalgamation of technology and medical expertise. Challenges faced by many people are looking online for health information regarding diseases, diagnoses, and different treatments. If a recommendation system can be made for doctors and medicine while using review mining will save a lot of time. The idea behind recommender system is to adapt to cope with the special requirements of the health domain related with users. The development and implementation of a personal virtual doctor aim to enhance healthcare accessibility, provide timely information, and empower individuals to take a more proactive role in managing their health and well-being.

Keywords: Personal Virtual Doctor, Disease prediction System, Multiple disease prediction

Abstract: This project aims to design a self-propelling ionic thrust wing, combining aerodynamics and ionic propulsion technology. The system utilizes ionized particles for propulsion, generating thrust by interacting with a charged grid. The wings design incorporates lightweight materials and aerodynamic principles to optimize lift and efficiency. The integration of advanced control systems ensures stable flight, while the ionic thrusters provide a clean and efficient means of propulsion. This innovative approach holds potential for unmanned aerial vehicles with extended flight endurance and reduced environmental impact. The system utilizes a compact and efficient propulsion mechanism to generate thrust. The design also focuses on optimizing weight distribution, control systems and propulsion efficiency to achieve stable and agile flight.

Keywords: Self-Propelling, Wing, Propulsion, Aerodynamic, Efficiency, Unmanned Aerial Vehicle, Endurance, Environmental Impact.

Abstract: The project focuses on enhancing Document Question Answering (DocQA) systems in the financial sector through the integration of the fine-tuned DoNUT model. This model enables swift and accurate extraction of crucial information from various financial documents, facilitating faster decision-making and regulatory compliance. Through training and fine-tuning on diverse synthetic financial datasets, the proposed system aims for high precision and recall in extracting key financial information from the forms. Empirical evaluations and case studies within financial institutions aim to quantify the time savings and efficiency gains achieved by AI-driven DocQA systems, highlighting the tangible benefits of the DoNUT-enhanced model. Ultimately, this research underscores the transformative potential of AI-driven document understanding in the financial sector, emphasizing the importance of sophisticated AI models for improving operational efficiency, regulatory compliance.

Keywords: Document Question Answering (DocQA), DoNUT, artificial intelligence (AI), key-value pair extraction.

Abstract: Recent advancements in technology have played a pivotal role in enhancing various aspects of human life. Recognizing the valuable contributions of individuals with disabilities to society, it is crucial to facilitate their effective engagement through appropriate platforms. A prototype has been devised to operate household appliances by tracking eye movements for cursor manipulation. Through capturing eye movements via a camera and pinpointing the center position of the pupil, a range of commands for a virtual keyboard are generated. These commands enable interaction with the virtual keyboard through a motor driver, allowing the prototype to maneuver in different directions based on the chosen command. The contemporary computing industry is dedicated to advancing hands-free computing to aid quadriplegics. This article proposes a Human-Computer Interaction (HCI) system specifically designed for individuals facing amputations or hand mobility impairments. This system employs eye-based interfaces to translate various eye movements like blinking, staring, and squinting into actions of the mouse cursor. The implementation of this system necessitates the utilization of Python, OpenCV, NumPy, and other software tools for face recognition utilizing a standard webcam. Techniques such as the HOG feature, linear classifiers, and the sliding window method can construct a face detector devoid of additional equipment or sensors, ensuring a hands-free experience. The paper introduces an innovative algorithm for managing the movement of a computer screen cursor through iris movements. By accurately detecting the iris position within the eye and mapping it to specific locations on the computer screen, the algorithm empowers physically challenged individuals to control cursor movements in all directions. Moreover, the algorithm facilitates actions such as opening and closing folders, files, or applications through a clicking mechanism.

Keywords: Technology advancements, Technology advancements, Eye tracking, Hands-free computing.

Abstract: DRIVESAFE- The Emotive Transport Initiative discovers how transport concepts can improve road safety through the integration of new technologies. This study explored yawning findings, tracking contracts and mobile phones to keep drivers focused and alert on the road. The practice is to use pre-trained models and custom training to achieve accuracy. Regular updates and stringent testing ensure that the model is constantly improved, making it a powerful tool for implementing safety strategies and monitoring control driving in the automotive industry. The aim is to change the transport landscape and provide a safer road for all road users today.This integration is achieved by combining computer vision and audio signal processing. The system adapts to various driving conditions to increase its effectiveness in real situations. The continuous development of the model through revisions makes it responsible for change in thinking. The program helps improve driver care to improve road safety and health.

Keywords: Road safety technology, Emotion detection, Driver monitoring, Transportation safety innovation.

Abstract: With the rapid progress of technologies like Artificial Intelligence (AI), deep learning, and Machine Learning(ML), the ability to manipulate and modify images has become more accessible. This has led to the emergence of a concerning phenomenon known as deepfakes, where criminals can generate deceptive videos, images, or audio content. In addressing this growing challenge, the present paper introduces implementation of numerous approaches including Residual Networks (ResNet), Long Short-Term Memory (LSTM), and Convolutional Neural Networks (CNN) and Random forest with reference to identification of fake content. Despite the video, audio and image deepfake detection, this paper also introduces about live creation of the deepfakes.

Keywords: Deepfake, Residual Networks, LSTM, CNN, and Random Forest

Abstract: In the realm of education, the creation of question papers is a fundamental yet time-consuming task for educators. With the advancements in Natural Language Processing (NLP), automated systems can now assist in generating question papers efficiently and effectively. This paper proposes a Question Paper Generator (QPG) that utilizes NLP techniques to analyze and generate questions tailored to specific educational domains. The QPG employs various NLP tasks such as text summarization, keyword extraction, and semantic analysis to understand the content of educational materials. By processing textbooks, lecture notes, and other relevant resources, the system identifies key concepts and formulates questions that assess the students' understanding of the subject matter. Additionally, the QPG ensures the questions adhere to the prescribed curriculum and learning objectives. Furthermore, the QPG incorporates features for customization, allowing educators to specify parameters such as question types (e.g., multiple choice, short answer, essay), difficulty levels, and topic preferences. Through this flexibility, the system can generate question papers that meet the diverse needs of different educational settings. Evaluation of the QPG involves comparing the generated question papers with those created manually by subject matter experts. Metrics such as accuracy, diversity, and relevance of questions are assessed to validate the effectiveness of the system. Additionally, user feedback from educators and students is gathered to refine and improve the QPG over time. The Questions are generated into two types such as subjective and objective. The application is executed using the framework called Flask. Overall, the proposed Question Paper Generator leveraging NLP techniques presents a promising solution to streamline the question paper creation process, thereby saving educators' time and ensuring the quality and relevance of assessment materials in educational settings. home.

Keywords: Question generator, NLTK, Natural Language Processing, POS Tagging, Flask.

Abstract: Nowadays, there has been increasing interest in leveraging blockchain technology for secure and transparent electronic voting systems. This paper presents the design and implementation of a blockchain-based e-voting system aimed at enhancing the integrity, security, and accessibility of traditional voting processes. The system architecture utilizes distributed ledger technology to record and verify votes, ensuring immutability and transparency of the electoral process. Our approach addresses key challenges such as voter anonymity, verifiability, and prevention of tampering or fraud. The implementation leverages smart contracts to automate vote counting and result tabulation, thereby minimizing the need for manual intervention and reducing the potential for errors. We discuss the technical components of the system, including the blockchain network setup, consensus mechanisms, and cryptographic techniques employed to safeguard voter privacy and data integrity. Furthermore, we evaluate the performance and scalability of the system, considering factors such as transaction throughput and latency. Real-world deployment scenarios and potential challenges in adopting blockchain-based e-voting systems are also discussed. The outcomes of this research contribute to the advancement of secure and trustworthy e-voting systems, paving the way for more inclusive and efficient democratic processes.

Keywords: Blockchain, e-voting, distributed ledger technology, smart contracts, security, transparency, integrity, voter anonymity, verifiability, cryptographic techniques, consensus mechanisms, scalability, democratic processes.

Abstract: Agriculture is a significant occupation for a large portion of the Indian population. Crop production plays a crucial role in our economy. The quality of crop production can suffer due to improper crop selection for specific soil types or lack of knowledge about different crops' growth requirements. The proposed system makes use of machine learning to recommend crops based on historical soil parameter data, reducing the risk of soil degradation and promoting crop health. Factors like Sulphur, potassium, calcium, temperature, humidity, rainfall and soil ph. levels are analyzed using neural networks to suggest suitable crops for cultivation. One of the main reasons for low crop yield is the presence of infections caused by microorganisms, viruses, and fungi. Plant disease analysis is a key task in agriculture and can be prevented by utilizing plant disease detection techniques. Manual monitoring and management of plant diseases are labor-intensive and time-consuming, hence the use of image processing for disease identification. The objective of this study is to develop a model that can detect diseased crop leaves and predict plant diseases. This work is based on the convolution neural network(CNN).The detection of pests in agricultural field has attracted a lot of attention, which is helpful in achieving smart agriculture. In particular, the monitoring of crop pests is one of the key ways to manage and optimize agricultural resources. You Only Look Once (YOLO) based approaches have provided good results. Moreover, there is no large dataset for pest detection. In essence, this study puts forth a complete approach that tackle the ability of machine learning to revolutionize crop recommendation, disease detection, and pest detection in the agricultural sector. The primary objective is to optimize crop yield and foster sustainable practices. Through the integration of neural networks for crop recommendation, CNN for disease detection, and the challenges associated with pest detection, this research plays a crucial role in project the development of modern agricultural practices in India.

Keywords: Machine learning Algorithms, Neural Networks, Convolution neural network, You Only Look Once(YOLO).

Abstract: The "IOT Based Smart Weighing System" is of large scope project designed to make safety and effective operations. The system engages the services of various sensors and cloud connectivity to perform the parameters such as load weighing, air quality and fire hazards. Firstly, a load sensor is used to detect the weight of item to be placed. This sensor connected with an ESP8266 microcontroller which will transmit the data to Blynk cloud platform. In addition to this, the project also deals with air quality sensor to detect the harmful air quality levels such as Carbon monoxide or volatile organic compounds when it is detected a buzzer is triggered to alert and for create safe working environment. Furthermore, the system also had a fire detection sensor which is used to detect the abnormal increase in temperature or presence of smoke if it is detected it will activate the buzzer to alert the surroundings. Overall, this system approaches the safety and efficiency activity by using sensors and cloud connectivity to create secure environment.

Keywords: ESP8266/Node MCU microcontroller, Weighing load cell, MQ 135 Air quality/Gas detector, Flame sensor, Arduino IDE.

Abstract: Healthcare is a critical component of the medical industry in the modern digital era, as consumers look for pertinent health information online. Although the internet is a great resource, consumers may find it difficult to get useful information due to the large amount of scattered clinical data across multiple websites. Sentiment analysis, machine learning, and natural language processing (NLP) are used by an advanced drug recommendation system to examine user opinions in drug-related content. After processing this data, machine learning algorithms customize recommendations based on user profiles and adjust to changing sentiments over time. In order to accurately evaluate sentiment in user evaluations, natural language processing (NLP) is essential for comprehending and contextualizing linguistic nuances. The amalgamation of quantitative and qualitative data yields highly customized and context-sensitive recommendations, thereby augmenting the user experience in its entirety. In this paper, a drug recommender system based on user-generated drug reviews sentiment analysis is presented. With an emphasis on filling the knowledge vacuum in sentiment analysis research related to healthcare, the system seeks to assist patients in choosing medications with knowledge.

Keywords: Sentiment Analysis, Natural Language Processing(NLP), Machine learning

Abstract: The study formulated the brown rice chips with herbs (basil, onion laves, parsley), specifically to evaluate its sensory qualities and acceptability in terms of appearance, aroma, color, taste and crispiness. The method used in this study was developmental-experimental method of research. In the developmental research, this method used for formulation of brown rice chips with herbs for potential development and commercialization while in the experimental method attempted to investigate the proportion of brown rice chips with herbs using three treatments. This used the Completely Randomized Design: one (1) was tested by panel of evaluators and second (2) for final processes for consumer's preference evaluation. Score cards with the Nine (9) Points Hedonic Scale was used to obtain the data. The mean and Analysis of Variance (ANOVA) were used to analyze the data into alpha level set at 0.01 alpha. Findings on the sensory evaluation of the brown rice chips with herbs showed that (onion leaves) was the best quality attributes. When the general acceptability was considered in terms of appearance, aroma, color, taste, and crispiness. The brown rice chips with herbs was safe for human consumption as the results of microbial analysis of the product and based on the BFAD standard for microorganism test for products belonging Snack Foods category.

Keywords: Brown Rice, Herbs

Abstract: This mostly happens on tight mountain routes, hairpin curves, and U-turns. When driving in this position, the car coming from the other direction is invisible to the driver. Thousands of people lose their lives in auto accidents as a result each year. A automobile approaching from the side should be warned in order to prevent more collisions. Before the bend in the road, place the ultrasonic range detection sensor on one side, and after the bend, place the light indicator system on the other. An ultrasonic sensor on one side of the road uses a light system to transmit a signal to the other side of the road when a car approaches from a distance. The driver may stop the vehicle in response to a warning and hold it there until the other vehicle has passed. Additionally, a bell will be employed to alert that approaching car's driver.

Keywords: Electrical, Internet Of Things, u-turn, blindends, ultrasonic

Abstract: Mobile Ad hoc Networks (MANETs) are decentralized networks where nodes communicate directly with each other without a fixed infrastructure. Routing protocols in MANETs are crucial for establishing efficient communication paths among mobile nodes. This paper presents a detailed performance analysis of four widely used MANET protocols- Dynamic Source Routing (DSR), Ad hoc On-Demand Distance Vector (AODV), Destination-Sequenced Distance Vector (DSDV), and Optimized Link State Routing (OLSR). The evaluation is conducted using the NS-3 network simulator, focusing on three key performance metrics: packet delivery ratio, average throughput, and average delay. Through simulations in NS-3, this study provides insights into the comparative performance of these protocols, aiding in the selection of optimal routing protocols for MANET deployments. Additionally, the paper discusses the impact of network size, node mobility, and traffic patterns on the performance of these protocols, offering a comprehensive understanding of their behaviour in diverse MANET scenarios.

Keywords: MANET protocols, NS-3 simulation, performance analysis, packet delivery ratio, average throughput, average delay

Abstract: To overcome the traditional methods of teaching and make the topics student- centric. By overcoming the classroom teaching methods. This research paper will introduce a method consisting of the involvement of students. The method includes the practical approach of students by performing activity related to each concept.

Keywords: Implementable, Interactive, Conceptual

Abstract: In this paper is wind and solar powered street light pole wherein, design of the components and their analysis has been carried out and, the fabrication of the model has been done as per the calculations that have been obtained from the design and analysis. Electricity has helped in reducing physical efforts to a very large extent, but, the way in which it is produced is quite a matter of concern. Even today, most of the electricity that we use is produced through conventional methods. These conventional methods commonly use fossil fuels to produce electricity. Not only are these methods expensive, but also cause grave damage to the environment. The use of fuels for the generation of electricity results in increased costs and emissions of hazardous pollutants. The only alternative is a new method that is not only cheap and efficient, but also eco-friendly

Keywords: Solar, Wind, Power Generation

Abstract: Hybrid solar PV and wind generation system become very attractive solution in particular for stand-alone applications. Combining the two sources of solar and wind can provide better reliability and their hybrid system becomes more economical to run since the weakness of one system can be complemented by the strength of the other one. The integration of hybrid solar and wind power systems into the grid can further help in improving the overall economy and reliability of renewable power generation to supply its load. Similarly, the integration of hybrid solar and wind power in a stand-alone system can reduce the size of energy storage needed to supply continuous power. Solar electricity generation systems use either photovoltaic's or concentrated solar power. The focus in this paper will be on the photovoltaic's type. Detailed descriptions of the different technologies, physics and basics of PV can be found in many textbooks and papers. In this paper is wind and solar powered street light pole wherein, design of the components and their analysis has been carried out and, the fabrication of the model has been done as per the calculations that have been obtained from the design and analysis. Electricity has helped in reducing physical efforts to a very large extent, but, the way in which it is produced is quite a matter of concern. Even today, most of the electricity that we use is produced through conventional methods. These conventional methods commonly use fossil fuels to produce electricity. Not only are these methods expensive, but also cause grave damage to the environment. The use of fuels for the generation of electricity results in increased costs and emissions of hazardous pollutants. The only alternative is a new method that is not only cheap and efficient, but also eco-friendly.

Keywords: Solar, Wind, Power Generation

Abstract: The field of agriculture greatly influences our lives. The most significant economic sector in our country is agriculture. A profit in agricultural products is the result of proper management. Farmers produce less because they lack knowledge about leaf disease. Since production determines both profit and loss, plant diseases of the leaves detection is crucial. The method for classifying and detecting leaf diseases is CNN. The primary goal of this study is to identify leaf diseases in tomato, potato, grape, apple, and corn plants. Plant leaf diseases are tracked over vast agricultural fields for the purpose of detecting crop diseases. As a result, certain disease features are automatically identified and treated accordingly. The suggested Deep CNN model has been contrasted with well-known transfer learning techniques like VGG16.

Keywords: CNN, VGG16, Agriculture, Leaf diseases.

Abstract: In this research, "EMPOWERING PATHS: THE POTENTIAL OF FOOTSTEP-GENERATED POWER," piezoelectric materials are strategically placed in flooring or walkway surfaces to harness the energy created by footsteps. Since these materials can convert mechanical stress from feet into electrical energy, they can be employed as a component of larger grids or to power low-energy gadgets. Scalability, adaptability to various circumstances, and seamless connection with the current infrastructure are advantages. This technology offers a sustainable solution to cities' energy needs and opens the door to further research and development, leading to a more ecologically friendly future.

Keywords: Electrical, Internet Of Things, piezoelectric plates, power generation.

Abstract: This project, at the core of this endeavour lies the imperative of effectively segregating different wastes, a fundamental facet of recycling and waste management. This project introduces an ingenious approach to tackle this challenge by harnessing the power of a robotic arm. Its central mission is to conceive, fabricate, and implement a robotic system equipped with the capability to autonomously identify and segregate metal and non-metal materials. This robotic arm integrates a sophisticated suite of IR sensors, encompassing metal detectors and motors, ensuring an accurate differentiation between these two material categories. Once identified, the robotic arm seamlessly employs a precision sorting mechanism to direct these materials into separate collection bins. The integral components of this solution include IR sensors designed for precise gripping, DC motors and motor drives, metal proximity sensors, and a sophisticated microcontroller, uniting to herald a new era of waste management and resource efficiency.

Keywords: Servo motor, Power supply unit, motor driver, DC Motor, Metal sensor, Moisture sensor.

Abstract: The study formulated the phyto-colored taro farfalle with blue ternate, bougainvillea and squash flower extracts, specifically it aimed to evaluate its sensory qualities and acceptability in terms of appearance, aroma, color, taste and texture. The method used in this study was developmental-experimental method of research. In the developmental research, this method used for formulation of taro farfalle for potential development and commercialization while in the experimental method attempted to investigate the proportion of taro farfalle using three treatments. This used the Completely Randomized Design: one (1) was tested by panel of evaluators and second (2) for final processes for consumer's preference evaluation. Score cards with the Nine (9) Points Hedonic Scale was used to obtain the data. The mean and Analysis of Variance (ANOVA) were used to analyze the data into alpha level set at 0.01 alpha. Findings on the general acceptability showed that taro farfalle with bougainvillea extracts obtained the highest acceptability when the sensory qualities were considered in terms of appearance, aroma, color, taste, and texture. The taro farfalle was safe for human consumption as the results of microbial analysis of the product and based on the BFAD standard for microorganism test for products belonging Pasta Product category.

Keywords: Taro, Farfalle, Blue ternate, Bougainvillea, Squash Flower

Abstract: Electric aircraft propulsion is a potential and relatively choice for a reduction of emissions in flight operations. This paper showcases four architectures of aircraft propulsion systems being now considered to utilise the advantages of electric propulsion with commercially profitable operating range and payload capabilities. One of the largest technological obstacles to the widespread use of electric propulsion in aviation is the low energy density of modern electric batteries. The aircraft of the future will be simpler to operate and more capable than today's singlepiston-engine aircraft due to a rare convergence of technologies, mainly Electric Propulsion and Information Technology. The transformation is already shaping the automotive industry with most of the legacy car manufacturers and some outsiders as well jumping into the electric car mass production bandwagon, all of them hoping to carve out bigger slices of the market. This paper describes some of the challenges and opportunities that arise when the upcoming technology convergence wave finds applications in a four/five seat general aviation aircraft to enter in service by 2025.

Abstract: The system detects and alerts the user or the administrator when is fall below the predefined conditions, and display on the Web browser. Using the Internet of Things Technology for supervising solar power generation can greatly enhance the performance, monitoring and maintenance of the plant. Solar power plants need to be monitored for optimum power output. The solar system deployment requires sophisticated systems for automation of the plant monitoring remotely using web-based interfaces as majority of them are installed in inaccessible locations and thus unable to be monitored from a dedicated location. A solar panel is used that keeps monitoring the sunlight, here different parameters like voltage, current and intensity of light are displayed on the LCD and web browser by using IOT technology. Our system will constantly monitor solar panel parameter and transmit to IOT system over the internet.

Keywords: Internet of Things (IoT), solar panel, monitoring

Abstract: The foldable chair has become somewhat of an icon, and its design has not been changed much throughout the many decades it has been around. Nowadays there are plenty of different kinds and versions of foldable chairs. Their frame is mostly made out of aluminum or wood so that their weight can remain low and therefore convenient to carry. The foldable chair, one version of foldable beach chairs and closely related to the one Petrie patented, was a popular chair for being used at ships. Its inventor remains uncertain though. The seat and backrest are often made out of a water-resistant fabric. In this paper we study the various research papers on manufacturing of easily foldable and mobile chair for person, the used the different technology for foldable and mobile chair.

Keywords: chair, linkages, foldable furniture

Abstract: One of the main problems since the creation of plastic product and its large production is its useful life and waste management. In the document "Development of an extrusion machine for the production of plastic figures" the purpose is to reuse plastic and thus reduce pollution from the excessive consumption of plastic product. To fulfill this purpose, the extrusion machine must be created, where it works correctly and quickly. The desired method is from plastic granules, creating figures based on molds and thus extending the useful life and reducing waste. The design of this machine will allow the recovery, conversion and reuse of plastic waste as an input for the creation of different figures, thus reducing its environmental impact and the mismanagement of this resource. This project aims to develop an extrusion machine that is cost effective and reduces labor work due to the optimization of time. Development of an extrusion machine will produce a lot of automation, reduces cycle and manufacturing lead time.

Keywords: Injection Molding, Plastic, Extrusion Molding

Abstract: Injection moulding machine is one of the most widely used method for conversion of plastics into various end products application to wide range of plastic material. The main principle is to compress the plastic material in a heating chamber (barrel) with the help of plunger and induction coil convert plastic polymer into molten (semi-solid) state. Then the plastic polymer in predetermined quantity is forced through the nozzle into the die under pressure. After completing the process, final product is obtained from the die. We can use plastics, metals or alloys for this process. In our project we are using plastics polymers for making bushes, switches, fishing hooks, mobile covers etc. This machine is a prototype for producing small plastic components. This injection moulding machine is very useful for the small scale industries because of its low manufacturing cost, low maintenance cost, no skilled worker is required. It can be recommended for small scale investors those who are willing to produce small plastic products. The describe an injection molding machine, which is a widely used method for converting plastics into various end products. The machine operates by compressing plastic material in a heating chamber using a plunger and induction coil, transforming it into a molten state. The molten plastic is then injected under pressure through a nozzle into a die, resulting in the formation of the final product. The process can utilize plastics, metals, or alloys. The described machine is a prototype designed for producing small plastic components such as bushes, switches, fishing hooks, and mobile covers. It offers benefits such as low manufacturing and maintenance costs, as well as not requiring skilled labor. As a result, it is recommended for small-scale industries and investors looking to manufacture small plastic products.

Keywords: Injection Molding, Plastic, Extrusion Molding

+91-7667918914 iarjset@gmail.com 0 Items International Advanced Research Journal in Science, Engineering and Technology A Monthly Peer-Reviewed Multidisciplinary Journal ISSN Online 2393-8021 ISSN Print 2394-1588 Since 2014 Home About About IARJSET Aims and Scope Editorial Board Editorial Policies Publication Ethics Publication Policies Indexing and Abstracting Citation Index License Information Authors How can I publish my paper? Instructions to Authors Benefits to Authors Why Publish in IARJSET Call for Papers Check my Paper status Publication Fee Details Publication Fee Mode FAQs Author Testimonials Reviewers Topics Peer Review Current Issue & Archives Indexing FAQ’s Contact Select Page Power Control System Outage Device JAYVEE D. CRESPO Abstract. Power control system outage device are crafted to enhance electrical system reliability by integrating sensors, communication modules, and data analytics, enabling real-time monitoring of power parameters and automated responses to interruptions, ensuring uninterrupted power supply and improved system resilience. The study aimed to develop a power control system outage device integrating Internet of Things (IoT). This device combines sensors, communication modules, and data analytics to enable real-time monitoring of power parameters and automated responses to interruptions. Its main objectives included designing and implementing the IoT-based device, evaluating its efficiency and yield, consulting with IT specialists for assessing its embedded system, and conducting an end-user acceptance assessment. The IoT control functions include switching main power, backup power, temperature monitoring, and perimeter lights. The significance of the research lies in providing a safety device that prevents damage during natural disasters and ensures uninterrupted power supply. The evaluation involved 30 evaluators, including experts, instructors, technicians, and end-users. The findings indicated that the device was sensitive, with accurate responses to power outage in real-time.

Keyword: Power outage, over and under voltage protection, protective device, Automated, IoT, ATS Downloads: | DOI: 10.17148/IARJSET.2024.11540 How to Cite: [1] JAYVEE D. CRESPO, "Power Control System Outage Device," International Advanced Research Journal in Science, Engineering and Technology (IARJSET), DOI: 10.17148/IARJSET.2024.11540 Copy Citation Call for Papers Rapid Publication 24/7 April 2026 Submission: eMail paper now Notification: Immediate Publication: Immediately with eCertificates Frequency: Monthly Downloads Paper Format Copyright Form   Submit to iarjset@gmail.com or editor@iarjset.com   Submit My Paper Author CenterHow can I publish my paper? Publication Fee Why Publish in IARJSET Benefits to Authors Guidelines to Authors FAQs (Frequently Asked Questions) Author Testimonials IARJSET ManagementAims and Scope Call for Papers Editorial Board DOI and Crossref Publication Ethics Editorial Policies Publication Policies Subscription / Librarian Conference Special Issue Info ArchivesCurrent Issue & Archives Conference Special Issue Copyright © 2026 IARJSET This work is licensed under a Creative Commons Attribution 4.0 International License. Open chat

Abstract: The quality of groundwater in Udaipur, Rajasthan, is of critical concern due to its impact on public health and infrastructure integrity. One of the significant challenges associated with groundwater quality is the potential for scaling and corrosion, which can affect the performance and longevity of water distribution systems. The Langelier Saturation Index (LSI) and Ryznar Stability Index (RSI) are widely used parameters for assessing the scaling and corrosion tendencies of water. This review paper provides an overview of the application of LSI and RSI in evaluating the scaling potential and corrosion risk of groundwater in Udaipur, Rajasthan. It discusses the methodologies, factors influencing LSI and RSI, their implications for water quality management, and potential avenues for future research.

Keywords: Scaling potential, Corrosion assessment, Langelier Saturation Index (LSI), Ryznar Stability Index (RSI), Groundwater quality

Abstract: Sand mining, essential for economic development, poses significant risks to groundwater systems. This paper explores the mechanisms through which sand mining impacts groundwater, including the lowering of water tables, degradation of water quality, and disruption of surface water-groundwater interactions. The environmental, socioeconomic, and health consequences of these impacts are profound, affecting ecosystems, water availability, local economies, and public health. Mitigation strategies are discussed, emphasizing the need for stringent regulation, sustainable mining practices, and community engagement. Achieving a balance between development needs and environmental protection is crucial for the sustainable management of sand resources and the preservation of groundwater systems for future generations.

Keywords: Groundwater, Sand mining, Sustainable, Mitigation

Abstract: During this pandemic, the majority of people's health care requires medication and doctor's recommendations to improve and safeguard their health. Also, I've observed numerous incidents when many people have been afflicted with COVID. To limit physical contact and prevent the spread of infections, the recommended methodology is to introduce a personalised healthcare chatbot in hospitals. A personalised healthcare chatbot is one that uses natural language processing (NLP) in text format. AI and Deep Learning for Medical Diagnostics help to power a personalised healthcare chatbot. The project's purpose is to develop a personalised healthcare chatbot that overcomes the recommended technique. Many people were unable to see doctors for minor ailments like a cold or fever.

Keywords: Personalized healthcare, NLP, Chatbot

Abstract: In this paper, we obtain the necessary and sufficient condition for W_jkh^i, N_jkh^i and H_jkh^i to be recurrent and we get a relationship between them. The projection on indicatrix with respect to Cartan connection has been studied.

Keywords: Recurrence property, Projective curvature tensor, Projection on Indicatrix.

Abstract: Decentralized chat applications using blockchain technology are becoming more prominent due to their ability to enhance security and privacy in online communication. This research paper discusses the design and implementation of such an application, focusing on its decentralized architecture and the use of blockchain for secure messaging. The application ensures that messages are encrypted end-to-end, making them resistant to unauthorized access and censorship. Through an in-depth analysis of the application's performance and security features, this paper underscores the benefits of decentralized chat applications in providing a secure and private communication platform. The results highlight the potential of blockchain technology to transform online communication by ensuring security and privacy.

Keywords: Blockchain, Decentralized, Technology, Application.

Abstract: In the ever-evolving landscape of marketing, the power of sensory experiences has come to the forefront, with olfactory marketing emerging as a particularly captivating and effective strategy. Olfactory marketing, the art of leveraging the sense of smell to influence consumer behaviour, has been the subject of growing academic and industry interest in recent years. The investigation focuses on identifying the factors related to scent marketing which generate purchase intention among consumers. The target population was from Ernakulam district in Kerla, India. Cross-sectional research design was used with structured questionnaire to collect the responses from a sample of 319 respondents. The demographic characteristics and interest in scent marketing was surveyed as the first part of the questionnaire followed by focus on the factors that influence scent marketing from the consumers point of view. Exploratory factory analysis used to reduce the variables into factors.

Keywords: Olfactory marketing, Scent marketing, Purchase decision, Exploratory factor analysis, Multisensory appeals.

Abstract: This paper aims to provide a comprehensive overview of machine learning (ML) techniques across various data types, fostering opportunities to address research gaps and advance the field, particularly in the detection and prediction of crop diseases. The survey presents valuable insights into ML-based techniques for forecasting, detecting, and classifying diseases and pests. It highlights the importance of maintaining long-term datasets encompassing weather, disease, and pest data. Time-series ML models, such as recurrent neural networks (RNNs), are shown to be effective tools for accurately predicting disease and pest occurrences based on sequences of meteorological measurements. Additionally, incorporating normalized difference vegetation index (NDVI) measurements can provide supplementary insights into crop development. Leveraging computer vision and deep learning algorithms, particularly convolutional neural network (CNN) models, proves advantageous for detecting and classifying pests and diseases, outperforming traditional approaches that rely on manual feature extraction.

Keywords: Machine Learning, Support Vector Machine, Random Forest, Artificial Neural Networks, Plant disease detection.

Abstract: This study examined microbial contamination in herbal medicinal products in Jaintia Hills Districts, Meghalaya, India. Analysis of 40 samples revealed widespread bacterial and fungal growth, exceeding safety limits in 30% of samples. Also, Aerobic bacteria counts ranged from 64 × 10^5 to 130 × 10^6 CFU/g, surpassing WHO and Ayurveda Pharmacopeia of India guidelines. Similarly, 87.5% of samples showed significant fungal growth, with 12.5% exceeding safety limits. Bacterial analysis revealed E. coli (35%) which indicates fecal contamination and poor hygiene. S. aureus (53%) suggests poor handling and preparation practices. P. aeruginosa (20%) is another indicator of poor hygiene and potential contamination. The presence of these pathogens in herbal products is a serious concern globally, and it's crucial to address this issue to ensure consumer safety. The three pathogens E. coli, S. aureus and P. aeruginosa can cause a range of health problems, from mild to severe, including gastrointestinal issues (diarrhea, vomiting, abdominal pain), skin and wound infections, respiratory problems (pneumonia, bronchitis), life-threatening conditions (sepsis, meningitis, urinary tract infections).

Keywords: Herbal Medicinal Products (HMPs), World Health Organization (WHO), Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa, Total viable count (TVC), Colony forming units (CFU), Jaintia Hills Districts, Meghalaya, India

Abstract: In the realm of healthcare technology, the quest for improved patient care and monitoring, especially in conditions like Alzheimer's disease, remains paramount. This study tackles this challenge by integrating embedded systems and IoT (Internet of Things) technologies. Through the strategic utilization of tilt, PIR (Passive Infrared), wet, and pressure sensors, coupled with ESP32 and Raspberry Pi 4W microcontroller units, we crafted a sophisticated system tailored for Alzheimer's patient monitoring. This system captures a wide array of patient activities and behaviors, offering a comprehensive view of their daily routines. Crucially, the system promotes cognitive engagement through memory-related activities, aided by audio cues for routine adherence. Preliminary results are encouraging, demonstrating heightened patient engagement and more effective monitoring. Despite encountering design and implementation hurdles, our iterative approach has yielded a functional prototype poised to make meaningful contributions to Alzheimer's care. This paper delineates our design process, challenges faced, and promising initial findings, underscoring the potential of integrated technologies in revolutionizing Alzheimer's patient care.

Keywords: Healthcare Technology, Alzheimer's Patient Monitoring, Embedded Systems, Internet of Things (IOT), ESP32, Raspberry Pi 4W, Sensor Integration, Cognitive Engagement, Audio cues, Protype Development

Abstract: The You Only Look Once (YOLO) algorithm stands as a cornerstone in the realm of object detection, celebrated for its unparalleled accuracy and efficiency. In this research endeavour, we embark on a comprehensive exploration of the various iterations of the YOLO algorithm. Through meticulous comparative analysis, we unveil the evolutionary trajectory of each YOLO version, shedding light on the motivations behind their respective updates. Our investigation delves deep into the intricacies of target recognition and feature selection methodologies, underscoring the algorithm's continual refinement. Furthermore, this study offers valuable insights into the applications of YOLO in diverse domains, including the financial sector. By elucidating the nuances of YOLO and its counterparts, this paper enriches the discourse surrounding object detection literature.

Keywords: Machine learning, Object detection, YOLO algorithm, YOLO versions

Abstract: Diabetes is an illness caused by high altitude of the glucose in the humans body. Diabetes it should not be disregarded and left untreated. Diabetes can cause serious problems such as Blood Heart , kidney problems, circulatory strain, eye harm, and it will also affect different organs in the humans body. Early prediction helps managesdiabetes. To accomplish this objective, Projectwill apply an assortment of Machine Learning methods to predict and improve the accuracy of earlydiabetes in the human body and patients. Machine learning strategies give improved results to forecast by building model from datasets gathered from patients. In the task, applymachine learning order and group strategies to outdataset to predict diabetes. These are the Decision Tree tool algorithm, Support Vector Machine algorithm, XgBoost Classifier algorithm, and Random Forest algorithm. The accuracy of each model is different from the other models. The work of Project Providesan accurate or more accurate model andshows that the model can effectively predict diabetes. Our results show that Random Forest algorithm achieves great accuracy compared with other machine learning.

Abstract: In the modern turbomachinery design trend, blades are getting more and more flexible and loaded, and therefore prone to vibration issues due to forced response and flutter phenomena. a. It has always been important to study the development and improvement of the design of turbomachine, owing to the numerous uses of turbo machining and their high energy consumption, high performance of centrifugal compressor call for a reduction in weight to relax rotor dynamic constraints and a reduction in blade thickness as a way to improve the efficiency. This project we are focused on increasing the efficiencies, reducing the pressure loss by keeping the larger splitter blades and the enhancement of the surge characteristics and the back sweep of the blade will reduce the stall in the compressors will leads to increase the efficiency and the long operating range and this statement can be proved by conducting the forced response analysis on the compressor blades.

Keywords: compressor blade, flutter, surge characteristics, forced response.

Abstract: Structural health monitoring (SHM) in aircraft involves using sensors to assess the condition of critical components in real time, helping detect potential issues and improve overall safety. Common techniques include strain gauges, accelerometers, and non-destructive testing methods like ultrasound. SHM aids in early fault detection, minimising maintenance costs, and enhancing aircraft lifespan. Morphing wings have a large potential to improve the overall aircraft performance, as natural flyers do. By adapting or optimizing dynamically the shape to various flight conditions, there are yet many unexplored opportunities beyond current proof-of-concept demonstrations This project focuses on exploring the concept of bird-inspired morphing wing, a cutting-edge technology that aims to develop adaptive wing structures capable of altering their shape and configuration during flight.

Keywords: Structural health monitoring, Non Destructive Testing, Aerodynamic efficiency and morphing wings.

Abstract: In the advancing era of technology, sentiment analysis became a crucial to-eol for understanding human emotional ion and opinions express through Donald text and talking. Our project, titled "Mindset Analyzer," centres on machine learning technique and of particular the Natural Language Toolkit (NLTK), for cultivating a sentiment analysing machine. The main object is to analysing the sentiment from input data, either in text face or speaking, and classify is in positive, negative, or neutral sentiments. This project intends to contribute to various area like evaluation of customer feedback, tracking feelings on social media, and mining opinions. With the power of NLTK's many features and algorithms, we make a stable sentiment analysing tool able to correctly see the emotions in various written and spoken matter.

Abstract: Track Guard: Anti-Theft Mobile Tracking System is a critical solution in the modern era of smartphones and mobile devices. With the surge in mobile device usage, security concerns have escalated. This system addresses these concerns by offering a proactive and efficient approach to prevent unauthorized access, track a device's location, and facilitate its recovery. The system's operation begins with the continuous acquisition of GPS data, storing latitude and longitude information. To activate the tracking function, a simple message is sent to the device, which triggers its activation. Once activated, the system collects the device's current GPS coordinates and sends them to a predefined email address, which is especially useful for tracking children or ensuring the safety of loved ones. The Anti-Theft Mobile Tracking System employs a comprehensive approach to mobile device security, incorporating advanced technology, user empowerment, and collaboration with law enforcement. By harnessing these elements, users can significantly enhance their chances of recovering lost or stolen devices while also safeguarding their personal data. This system effectively meets the growing demand for mobile device security in our increasingly interconnected world, providing users with peace of mind and the assurance that their devices are protected.

Keywords: Antitheft, Mobile tracking system, GPS (Global Positioning System), Email notification, Security.

Abstract: Hybrid electric vehicles (HEVs), which combine an internal combustion engine (ICE) and an electric motor, are a promising way to cut emissions and fuel use without sacrificing a vehicle's functionality or driving ability. The implementation of a hybrid car with a gasoline engine and battery pack is discussed in this essay. Hybridization reduces fuel consumption compared to regular gasoline and diesel-powered cars. A car with no emissions is an electric vehicle. The separate issues with the gasoline engine and the electric car are cleverly avoided by the suggested HEV. It reduces fuel use and pollutant output. Batteries for electric vehicles are less of a worrisome. The motor has capability to operate as generator to move energy if a battery is not present.

Keywords: Hybrid electric vehicle, petrol engine.

Abstract: Image classification is essential across various sectors, from healthcare to robotics. However, traditional methods often struggle with datasets containing multiple categories. In this paper, we present our innovative approach to multi-class image classification, achieving an accuracy of 86%. Our algorithm is built from scratch, tailored specifically for multi-class categorization. Through rigorous testing, we demonstrate its effectiveness, outperforming baseline methods. Our work contributes to advancing image classification, providing a robust solution for multi-class challenges.

Keywords: Machine learning, Binary classification, Neural Networks, Application.

Abstract: This project is a visitor management application developed using the Tkinter library in Python. The main functionality of the application is to capture and process images of various ID documents, such as Aadhaar Cards, PAN Cards, Driving Licenses, and Voter IDs. The application utilizes Optical Character Recognition (OCR) to extract relevant details from the captured images, including the visitor's name, document number, gender, and date of birth, and stores this information in a MySQL database. This application generates the digital badge which is unique for each visitor and is used to track check-in and check-out times via QR code scanning. The application includes voice assistance functionality to guide the user through various stages. Additionally, the service provides reporting and data analysis capabilities, allowing users to view visitor statistics, such as daily, weekly, and monthly visitor numbers per category, and perform cluster analysis for identification trends and patterns. Overall, this project demonstrates the integration of computer vision, data processing, and database management techniques to create a comprehensive visitor management system with a variety of reports to work with, making it a valuable tool for organizations requiring effective management and tracking of visitors.

Keywords: Visitor, AI, Management, Automated

Abstract: In contemporary data-driven environments, efficient log management and analysis are imperative for maintaining system reliability, diagnosing issues, and optimizing performance. The "Kafka-ELK Data Pipeline" project addresses these demands by configuring Logstash to ingest data from Kafka topics and perform data modification as needed. This paper provides a comprehensive overview of the project's architecture and functionalities, emphasizing its role in facilitating robust log management and analysis. The pipeline comprises several critical components, including Filebeat for log collection and forwarding, Kafka for data brokering and queuing, Logstash for data aggregation, processing, and shipping to Elasticsearch, and Elasticsearch for data indexing. Additionally, Kibana serves as the visualization and analysis tool for the processed data. Notably, the entire infrastructure is containerized using Docker containers, orchestrated via YAML files for seamless deployment and management. Beyond the technical details, this paper delves into the broader context of monitoring in the industry and its significance. In today's dynamic business landscape, organizations across various sectors rely heavily on monitoring solutions to ensure the uninterrupted operation of their digital systems. Monitoring plays a pivotal role in detecting anomalies, diagnosing issues, and preemptively addressing potential disruptions. From IT infrastructure and network performance to application health and security, monitoring encompasses a wide array of use cases critical for business continuity and operational excellence.

Keywords: Cloud services, Monitoring, Log analysis, ELK stack

Abstract: This paper provides a detailed account of the development and implementation of a voice-activated desktop assistant created using Python, Pygame, and Tkinter. The assistant integrates with Google Assistant, allowing users to communicate with it via voice commands and receive personalized responses. Moreover, it provides voice control for various system functions, such as launching applications like Notepad, Paint, and YouTube. The primary aim of this system is to enhance user productivity and convenience by enabling hands-free interaction with the desktop environment.

Keywords: Voice-based desktop assistant, Python, Pygame, Tkinter, Voice-to-voice customizable Q&A, System control

Abstract: In order to meet the demands of the expanding population, agriculture plays a vital role in boosting food supply. Unfortunately, conventional techniques for identifying diseases and applying pesticides to crops are labor-intensive, slow, and frequently ineffective. We suggest improving a machine learning-based pest recognition and pesticide sprayer in order to address the aforementioned problems. The goal of this project is to use IOT and artificial intelligence technology to automate disease diagnosis and pesticide spraying procedures. For intruder detection and control, the robot makes use of an Arduino microcontroller, motors, motor drivers, a Bluetooth module, and a PIR sensor. We also employ machine learning models for plant disease identification that are available on Google Colab. This technique seeks to increase food security, decrease the need for physical labor, minimize the use of pesticides, and increase agricultural output.

Keywords: Machine Learning, Pest Recognition, Pesticides Spray, Google Colab, Internet of Things (IOT).

Abstract: The "E-Bike speed controller system by stm32" is of large scope project designed to make protection and speed control operations. The system engages the services of sensors and motors to perform the parameters such as speed control and battery protection. Firstly, a battery is 8.4 volts is turned on, but the system works on 5v, so a bug converter is used to distribute the correct amount of voltage. When the motor starts the user accelerates to high speed and suddenly the E-bike crashes the motor wheel stops rotating then this system knows stall detected and stops the flow of current from the battery to the motor. If the E-bike in high speed and we keep on applying the load the system knows overload is detected, it stops the rotation of the motor and cuts the power supply from the battery to the motor. Overall, this system approaches protection and speed control by using sensors and MOSFET to create a secure environment.

Keywords: STM32 Microcontroller, Buck Converter, MOSFET, LCE display, I2c Module, Current Sensor, Motor, Battery.

Abstract: This research focuses on fish species classification using deep learning models, specifically ResNet-50 and MobileNetV2. The ResNet-50 model, a 50-layer deep convolutional neural network, is employed for its proven excellence in image classification tasks. The dataset comprises 20 freshwater fish species, with 57 samples per species captured using a Samsung Galaxy M30s mobile phone. Data preprocessing involves image conversion and offline augmentation to address the small dataset size. The ResNet-50 architecture consists of 5 stages with convolution and identity blocks, employing batch normalization and ReLU functions. The model is trained on 224x224x3 image inputs and utilizes over 23 million trainable parameters. The bottleneck design is incorporated into the residual units for enhanced performance. The system's effectiveness is evaluated through species detection, where the model predicts the fish species from input images. In contrast, the MobileNetV2 model is introduced as a lightweight convolutional neural network tailored for mobile and embedded devices. It employs depth wise separable convolutions and an inverted residual structure for efficiency. The network architecture includes Conv 1x1 and Dwise 3x3 layers, showcasing its ability to reduce computational cost and improve information flow. The effectiveness of both models is assessed in the context of fish species classification, providing insights into their performance and suitability for the given task. The research contributes to the understanding of deep learning models in the domain of fish classification, with implications for applications in aquatic biodiversity monitoring. Our experiments reveal that MobileNetV2 consistently outperforms ResNet50 in terms of accuracy. MobileNetV2 achieved an impressive accuracy of 99.44%, while ResNet50 achieved 98.45%. The higher accuracy of MobileNetV2 suggests its efficacy in capturing intricate features within images, even with its more compact architecture.

Keywords: MobileNetV2, ResNet50, Convolutional neural network (CNN), Data Preprocessing, Fish species detection.

Abstract: The Blood donation system is a comprehensive online platform aimed at optimizing blood donation processes by prioritizing the referral of active blood donors and conducting thorough analyses of donor data. This system focuses on improving the efficiency of blood donation networks to ensure a consistent and sustainable blood supply for healthcare institutions. Its key feature involves a user-friendly interface allowing potential donors to register and create profiles, providing essential information on blood type, availability, and willingness to donate. Intelligent algorithms match donor profiles with real-time blood demand, facilitating targeted referral notifications. The system also integrates advanced analytics tools to comprehensively analyse donor data, including tracking donation histories, identifying supply and demand trends, and generating insights into active donor demographics. These analytical capabilities empower blood banks and healthcare authorities to make informed decisions, strategize donation campaigns, and optimize resource allocation for better emergency preparedness. In summary, the system serves as a platform for connecting active blood donors with those in need, offering critical insights through data analysis to enhance the efficiency and sustainability of blood donation networks, ultimately contributing to saving lives and improving healthcare outcomes. By leveraging technology, it minimizes logistical challenges and maximizes the utilization of available resources, thereby reducing wastage and improving the overall efficacy of blood donation campaigns. This instills trust among donors and healthcare stakeholders, encouraging participation and fostering long-term partnerships. Moreover, the Blood donation system facilitates collaboration among different blood banks and healthcare institutions, enabling seamless sharing of data and resources. This collaborative approach enhances coordination during emergencies and enables a swift response to fluctuating blood demands, thereby saving valuable time and potentially lives. In conclusion, the system represents a paradigm shift in blood donation management, harnessing the power of technology and data analytics to revolutionize the way blood supply is managed. By fostering a culture of continuous improvement and innovation, it promises to address the evolving challenges faced by blood banks and contribute significantly to the advancement of healthcare delivery systems worldwide.

Keywords: PHP, MySQL, online platform, donor registration, user-friendly interface, real-time blood demand, analytics tools, donation histories, supply and demand trends, donor demographics, resource allocation, emergency preparedness, efficiency, sustainability, technology, logistical challenges, wastage reduction, innovation, healthcare delivery, saving lives.

Abstract: This review paper investigates how technologically advanced safety jackets can be made safer for miners by incorporating innovative technologies. The study analyses existing hazard difficulties and the unique risks encountered by miners, with a focus on addressing the major safety issues in mining. In addition to highlighting the creative use of Atmega 328p and NodeMCU controllers in safety wearables, the study looks at how these smart jackets provide protection and can even save the lives of miners working in unsafe conditions. This paper provides a thorough analysis of how innovative safeguarding jackets are set to transform safety standards in the mining sector, highlighting a major shift towards making sure the welfare and security of underground workers. It does this by reviewing recent literature and technological advancements.

Keywords: Safety jacket, Real-time monitoring, IoT- enabled application, Miner safety.

Abstract: In this project, a cost-free Artificial intelligence-based application for smartphones built to detect vitamin deficiencies in humans using pictures of specific body organs is introduced. Recent vitamin deficiency detection methods require costly laboratory analysis. A wide spectrum of vitamin deficiencies can show one or more visually distinguishable symptoms and indications that appear in multiple locations in the human body. The application provides individuals with the capability to diagnose their possible vitamin deficiencies without the need to provide blood samples through the analysis of photos taken of their eyes, lips, tongue, and nails. The application then suggests a list of nutritional sources to fight the detected deficiency and the expected complications through nutritional micro-correction. The intelligent software was trained to distinguish and differentiate vitamin deficiencies with high confidence from imagery inputs of the selected body parts that are known to show different symptoms in terms of changes in the tissue's structure when the human body suffers a nutritional deficit. The platform also allows medical experts to assist in improving the range of detection and accuracy of the application through the contribution and verification of visual data of their patients allowing for more refined image analysis and feature extraction capabilities with the potential to surpass human's ability to diagnose medical conditions. This application is a useful tool for people to overcome a global problem that affects millions of people worldwide mainly as a result of inadequate nutritional awareness, and it will help healthcare workers in the long term in obtaining more accurate diagnoses.

Keywords: Detect Vitamin deficiency, CNN, Food suggestion, Mobile application.

Abstract: The education system plays a crucial role in shaping individuals' careers, and students' health is an increasingly significant research topic because they are the foundation of our society. Researchers have leveraged various technological advancements to address health issues among schoolchildren and college/university students, with machine learning becoming a commonly used tool. However, to gauge the effectiveness of machine learning and advancements in student health research, a concise review of its impact on student health is needed, which the proposed work aims to provide. The primary objective is to analyze which student health concerns are effectively addressed by machine learning algorithms and the outcomes of these approaches. The project also explores the factors that contribute to poor academic performance in schools, colleges, and universities, and whether machine learning can enhance student health in the future. The main aim of the project is to determine how student health problems affect their academic performance. Unsupervised learning algorithms are applied to process educational data and generate correlations between student health issues and academic performance. In this proposed system, we develop automation for the education sector. The proposed system is a browser-based application designed for a college, developed using Microsoft technologies such as Visual Studio, C#, and SQL Server.

Keywords: Education system, Student health, Machine Learning, Health issues, Correlation, Browser-based application.

Abstract: Each day, millions grapple with the challenges of vision impairment, facing difficulties with everyday tasks at home or work without assistance. According to the World Health Organization (WHO), over 250 million people have visual disabilities, with approximately 35 million being completely blind. This demographic encounters a world rife with hazards, where even crossing a street becomes perilous due to their inability to perceive obstacles and traffic. Despite a strong desire for independence, many individuals with visual impairments depend on others for routine tasks. However, advancements in technology, particularly in computer vision, offer hope for greater autonomy. While traditional aids such as white canes, guide dogs, and specialized software have been invaluable, emerging innovations aim to revolutionize perception by translating visual information into sound. These developments hold the promise of enhanced autonomy and safety, empowering the visually impaired to navigate the world with increased confidence.

Keywords: Blindness, Visual disabilities, Assistance, Independence.

Abstract: The application and importance of vehicle monitoring systems based on the Controller Area network (CAN) Protocol in the contemporary automotive engineering are examined in this research. These systems make use of the CAN Protocol's dependability and efficiency to allow electronic control units (ECUs) in cars to communicate with one another in real time. They offer thorough monitoring of important characteristics including engine performance, vehicle speed, fuel level by collecting the information from components like sensors. This paper highlights the role that CAN Protocol-based vehicle monitoring systems play in improving vehicle performance, safety, and maintenance efficiency. It also analyzes the design, functioning, diagnostic capabilities, and advantages of such systems.

Keywords: CAN, ECU, Vehicle Monitoring System, Diagnostics capabilities, maintenance efficiency.

Abstract: The dust particles accumulating on the solar panels (20,000 Square meters).The cleaning of dust particles on the solar panel is a panels will prevent the solar energy from reaching the huge problem because it's time consuming process and solar cells, thereby reducing the overall power requires lot of man power and money. To remove this generation, Power output is reduced as much as by 50%,limitation, robotics can be used as it eliminates human if the module is not cleaned for a month. In order to labour and at the same time more economical and regularly clean the dust, an automatic cleaning system autonomous. which removes the dust on the solar panel is developed. In this paper, the problem is reviewed and the method for dust removal is discussed. A robot cleaning device is developed and it travels the entire length of the panel. A PIC microcontroller is used to implement robots control system. The robot provided a favourable result and proved that such a system is viable by making the robotic cleaning possible, thus helping the solar panel to maintain its efficiency. This paper provides an overview of the cleaning aspects of solar panels through a literature review. We first discuss the drawbacks of unwanted deposits on solar panels in terms of energy production and efficiency. Existing cleaning practices and technologies are then presented with an emphasis on factors such as the size of the facility, location, cost, and available resources. Finally, comparative cost- benefit analysis is carried out using decision support tools and taking into account different relevant criteria to support users choose the right cleaning maintenance for their specific solar installation.

Keywords: Cleaning aspects; solar panels; unwanted deposits; energy production; efficiency existing .

Abstract: Traffic law violations have become a significant concern, contributing to the erosion of societal moral values due to widespread casual and irresponsible attitudes among drivers. Despite notable advancements in traffic laws, the persistence of human involvement in the current enforcement system remains a liability, resulting in suboptimal outcomes. This laxity fosters a culture of carelessness among drivers, exacerbated by delays and occasional inaccuracies in the delivery of paper-based and electronic challans. To address these challenges, our proposal advocates for the automation of the traffic offender identification process using advanced technologies such as object detection and tracking. By directly accessing vehicle information from the Regional Transport Office (RTO) database through number plate detection, the system generates Smart-challans promptly and accurately. These Smart-challans are then efficiently delivered to offenders via Email and SMS on the same day the offense is registered. Through this initiative, the proposed system aims to significantly enhance efficiency, accuracy, and reduce the likelihood of human error, thereby bolstering the effectiveness of traffic law enforcement efforts.

Keywords: Smart-challans, object detection, Regional Transport Office (RTO).

Abstract: The critical shortage of organs for transplantation necessitates exploring innovative solutions to improve the matching and allocation process. Blockchain technology, with its significant principles of the decentralization, security, and transparency, presents a promising avenue for building a more efficient and trustworthy platform for organ donation and transplantation. This paper surveys the current state of organ donation systems, explores the potential benefits of blockchain integration, and analyzes existing research on blockchain-based platforms for this domain

Keywords: Organ Donation, Transplantation, Blockchain Technology, Smart Contracts, Decentralization, Transparency.

Abstract: Online project outsourcing involves contracting third-party providers, often located overseas, to deliver products or services via the internet. This business process leverages outsourcing or freelancing marketplaces, which are crucial in connecting clients (small businesses and individuals) with service providers (freelance workers). These platforms facilitate the formation of relationships based on mutual needs and the professionalism and competence of both parties involved. A freelancer, freelance worker, or "freelance" is someone who is self-employed and not committed to a long-term employer. Freelancers typically enjoy a wider variety of assignments compared to regular employment and have more freedom in choosing their work schedules, subject to the necessity of earning a regular income. However, freelancing comes with significant drawbacks, such as the uncertainty of work and income, and the lack of company benefits like provident fund (PF), health insurance, paid holidays, and bonuses.

Keywords: Freelancer Connect Empowering Opportunities in a GIG Economy, Freelancing marketplaces, Professionalism and competence, Regular income.

Abstract: Breast cancer is the type of cancer that is originates in cells of breast. Breast cancer can occur in both men and women, but it is far more common in women. Breast cancer detection is critical for early diagnosis and treatment. Mammography is the most known and effective process to detect early signs of breast cancer. Convolutional Neural Networks (CNNs) have emerged as powerful tools for mammogram image analysis due to their ability to automatically learn and extract relevant features from complex data. This study explores the application of CNNs for detecting and classifying the stages of breast cancer from mammographic images. By employing a deep learning framework, we trained a CNN Pre-train model like EfficientNet B4, Inception V4 model on a labeled dataset of mammograms, where the images were preprocessed to enhance feature extraction. The model's performance was evaluated using metrics such as accuracy, sensitivity, specificity, and the area under the ROC curve (AUC). Results demonstrated that the CNN achieved high accuracy in distinguishing between different stages of breast cancer, highlighting its potential as an effective diagnostic aid. Further improvements and validations with larger datasets are necessary to enhance the model's robustness and generalizability. This approach promises to support radiologists in making more accurate and timely diagnoses, ultimately improving patient outcomes.

Keywords: Breast cancer, Convolutional Neural Networks (CNNs), mammogram images, CNN Pre-train model like EfficientNet B4, Inception V4 model

Abstract: Significant safety concerns are associated with trekking in distant or difficult areas, as people are frequently at risk of getting lost or running into emergencies. This article suggests integrating Fog IoT technology into hiking GPS systems to provide real-time tracking and safety monitoring for trekkers in order to successfully address these difficulties. The approach entails the thoughtful placement of edge sensors and gateways along the hiking route in addition to the strategic deployment of IoT devices with GPS sensors on both trekkers and equipment. Strategically placed at vital junctures, fog nodes are essential for locally processing GPS data, allowing for quick analysis of planned route deviations and possible crises. By taking a decentralized method, latency is drastically decreased and bandwidth is preserved, guaranteeing effective data transfer to a central base station. When possible problems are found in trekker GPS data, the base station acts as a complete command centre, making it easier to coordinate rescue efforts in reaction to alerts. To further improve overall safety and rescue effectiveness, the system keeps a library of past GPS data for post-event analysis, route optimization, and incident assessment. Even in the most distant and difficult environments, this integrated method significantly increases outdoor adventure security by streamlining resource utilization, strengthening safety procedures, and utilizing cutting-edge technology.

Keywords: Fog Computing, Cloud computing, Arduino IDE, IOT (Internet of Things), HTTP (Hypertext Transfer Protocol), etc.

Abstract: The "Social Media Audio Conversations Speech Safeguard System" is a framework designed to improve the security, privacy, and responsible use of audio-based interactions on social media platforms. It incorporates measures to address user privacy, content moderation, data security, policy enforcement, and regulatory compliance. The system uses advanced speech recognition, content analysis, and moderation tools to create a secure and respectful environment for users. Natural Language Processing (NLP) algorithms are used during the text-to-speech conversion process to ensure accurate interpretation and safeguarding of audio content. This promotes responsible user behavior and fosters trust among platform users. The system aims to maintain a secure and respectful online environment by integrating NLP algorithms into the text-to-speech conversion process, thereby promoting responsible user behaviour and trust among platform users.

Keywords: Social Media Audio Conversation Speech Safeguard System, NLP, content, Privacy, audio secure.

Abstract: In contemporary logistics operations, technology plays a pivotal role in replacing antiquated systems. This article proposes a comprehensive solution for securing goods in transit using a integration of cryptography and IoT technology to mitigate threats. In our proposed system cryptographic measures at logistics doors, requiring authorized personnel to give a hash function, specifically utilizing the MD5 encryption algorithm, to inspect the goods. It employs encryption technique to secure the passwords associated with access points along the transportation route. Upon door opening, an alert message is deliver to the sender via the Blynk App, enabling real-time tracking and location verification. Additionally, the system incorporates weight sensors to detect any tampering to the transported goods. Upon detecting such anomalies, the system triggers alarms or sends the alert to relevant stakeholders. The stakeholder can remotely access the system via the Blynk app to track the location. This integrated approach ensures the protection of goods throughout the journey, safeguarding against potential cyberattacks and theft incidents.

Keywords: Cryptography - MD5 algorithm, Weight sensor, Microcontroller (NodeMCU), Blynk application

Abstract: Indoor air pollution poses a significant threat to human health and comfort, with pollutants such as dust, chemicals, and allergens contributing to respiratory problems and discomfort in indoor spaces. To address this issue, we propose a solar-powered smart air monitoring and purification system. Integrated with sensors for temperature, humidity, and air quality measurement, the system detects pollutants in indoor environments in real-time. Utilizing an ESP8266 Wi-Fi module, the system transmits data to the cloud for analysis and monitoring. When air quality surpasses predefined thresholds, the system activates a fan to improve ventilation and incorporates a HEPA filter for enhanced air purification. This proactive approach to indoor air quality management ensures healthier and more comfortable indoor environments for occupants.

Keywords: Indoor air pollution, solar-powered, cloud analysis, HEPA filter.

Abstract: Algorithmic trading has revolutionized the financial markets by leveraging computational power and complex mathematical models to execute trades at high speeds and frequencies. This paper proposes a novel algorithmic trading model that optimizes trade execution using machine learning techniques. We employ a combination of supervised learning for predictive modeling and reinforcement learning for decision-making processes. The results demonstrate significant improvements in trading accuracy and profitability, outperforming traditional heuristic-based trading systems. Our findings suggest that the integration of advanced machine learning methodologies can enhance trading strategies and contribute to more efficient market operations.

Keywords: Algorithmic Trading, Machine Learning, Supervised Learning, Reinforcement Learning, Predictive Modeling, Financial Markets, Trading Strategies, High-Frequency Trading

Abstract: The "IOT BASED SMART STREET LIGHT SYSTEM" project is an Internet of Things application. The system's primary goal is to use Arduino to develop a smart street light controller system. The primary goal of the system, which is designed to save energy, is to prevent energy waste caused by street lights that turn on automatically at dusk and off at dawn. It makes use of an Arduino Uno board along with an IR and LDR sensor. Arduino is an open-source platform for prototyping built on user-friendly hardware and software. To write code and upload it to your board, Arduino offers an intuitive and open-source programming tool. It's often known as the Arduino IDE. The LDR sensor, which regulates the brightness that the infrared sensor is exposed to, is unquestionably the primary controller in use. The vehicle or any obstructions in the path are detected using an infrared sensor. The system will turn on a led when it detects a car or obstruction. A portion of the lights in our system are ON, while others are OFF. Lights turn on when there is an obstruction or when cars approach. The light will turn off after the car or obstruction has moved.

Abstract: In today's world, everyone prefers submitting documents in digital format rather than in hard copy, as Digital Document Management is the current trend for submitting documents to officials, authorities, and others. This scenario sparks curiosity in verifying documents in digital settings. When submitting documents online, it is important to provide clarifications about their security, novelty, trustworthiness, and other relevant aspects. On the flip side, the user must ensure they have additional privacy measures in place when submitting documents online for further processing. The suggested system addresses the challenges of Security, Novelty, Integrity, Access Control, and Durability to find solutions to the mentioned problems and queries. Blockchain is a term that encompasses all industries today, whether government or non-government, as it extends its influence across various sectors to demonstrate its importance universally. The banking industry also utilizes Blockchain to offer security to account holders. The suggested program utilizes Blockchain technology for document verification, offering the highest level of security for users to digitally submit documents to authorities. The authorities can verify the documents intelligently while adhering to security protocols. The Blockchain system generates necessary data as a Block, with the first block being called the Genisis Block, guiding subsequent blocks sequentially without interference. The Miner Verification process in Blockchain checks the records in a Block against incoming records to ensure uniqueness before allowing them to be added to the next block. In the current system, records are blocked by Miner Verification process if they are already in the block. However, in this new system, Miner Verification is a voluntary process where volunteers physically verify Blockchain Miner verification process. More details will be provided later on. Every block in the Blockchain has a unique identity represented in cipher form through the use of SHA, a strong one-way encryption algorithm with a 256-bit encryption process. The whole procedure of the suggested system guarantees a secure and smart document verification scheme using Blockchain technology with effective innovation.

Keywords: Blockchain, Crypto Hashing, Document Check, Integrity Analysis, Secure Hash Algorithm, Cloud Interface, Miner Verification Process, Volunteer, Genisis Block.

Abstract: Water pollution has become world-wide phenomenon. Both deficiency and excess of minerals and trace elements in water can have deleterious consequences on biological system. The major ecological problem are the pollutants from industries, pesticides, herbicides, fertilizers and chemicals. The underground water is polluted by many hazardous pollutants like colored dyes, nitrates, metals, pesticides and fluoride. Fluoride is one of major concern among these pollutants. The problem due to high concentration of fluoride in ground water has now become one of the most important health geo-enviornmental issues in india. Fluorosis which was considered to be a problem related to teeth only has now turned up to serious health hazard. However no system of the body can be considered as exempt. 2 3- at At the normal levels of fluoride ingestion (approximately 6 mg/day) almost 87% of the absorbed fluoride is excreted through kidneys (McClure et al.,1945, Hodge 7 and Smith, 1972).Thus among the soft tissues, kidneys supposedly have the highest fluoride content as both excreation and retention of fluoride are affected by kidneys, thus kidney are more prone to fluoride toxicity then other soft organs which generally do not attain high fluoride levels, to which kidneys are subjected S to. bund 2023/06/30 22:06 Experimental studies have shown that the dietary factors such as calcium, amino- acids and vitamin C,D and E can mitigate the toxic effects of individual treatment of fluoride. Thus the present investigation is undertaken to investigate the effects of sodium fluoride (5 and 50 ppm), ascorbic acid (25 ppm) and calcium (calcium phosphate 25 ppm) alone and with calcium and ascorbic acid with sodium fluoride in producing various changes at histological levels in the kidney of mice for understanding the mechanism of action of fluoride. Recovery studies for 10,20 and 30 days were also undertaken with a hope that it is quite possible that recovery will play an important role in the restoration of normal structure once the kidney is effected. T dependent. After withdrawal of treatment, the signs of recovery were evident on day 10.The recovery process continued till day 30 and it was more pronounced with ascorbic acid+ calcium treatment.

Keywords: Histological changes, Fluorosis, Ascorbic acid, Sodium Fluoride.

Abstract: The "Blockchain based Document Storage and Authentication system" is designed to enhance data security and integrity. The system incorporates user registration, document uploading, admin approval, document verification and face capturing functionalities to provide a comprehensive and secure document management solution. Users register on the platform, upload documents that are encrypted and store on the blockchain, undergo admin approval for verification and can verify document authenticity through blockchain transactions, Additionally, users can utilize face capturing for biometric authentication. This system leverages blockchain technology to ensure transparency, immutability and enhanced security in document storage and authentication processes.

Keywords: Blockchain, Hashing, Ethereum, Document Verification, Digital Signature, Cryptography, Certificate Authentication, Governance

Abstract: Women's Empowerment can be defined as promoting women's sense of self work, their ability to determine their own choices and their rights to influence social change for themselves and others. The empowerment of women is an essential factor for the sustainable growth of society. In Kerala, a southern state of India Kudumbashree, the women's empowerment organisation, has given. women have social and economic equality. Kudumbashree is a group of women working under the Kerala State Poverty Eradication Mission and under the jurisdiction of local self-government institutions. State government established a poverty alleviation and women's empowerment program at the time of covid 19 that is Janakeeya hotels. Janakeeya Hotel is a food distribution system implemented by the State Government through local bodies with the objective of providing low cost food to all as part of the Covid control program. The scheme is fully implemented through Kudumbashree. This study is conducted among 40 Janakeeya hotel workers who are members of Kudumashree. The aim of the study is to understand whether they were empowered in using financial services or not.

Keywords: Financial Inclusion, Financial empowerment, Women, Kudumbashree,

Abstract: Brain tumours pose significant challenges in diagnosis and treatment due to their diverse appearances and complex features. Manual interpretation by radiologists often leads to subjectivity and variability in diagnoses, while traditional machine learning approaches may struggle to capture intricate patterns from medical imaging data effectively. To address these challenges, this study proposes a robust brain tumour classification system based on the ResNet50 architecture, a deep convolutional neural network known for its effectiveness in image classification tasks. Leveraging deep learning techniques, the system automates feature extraction and learns hierarchical representations directly from brain MRI scans. By initializing the ResNet50 model with pre-trained weights and fine-tuning it on a comprehensive dataset, the system achieves high classification accuracy, sensitivity, and specificity. Extensive experimentation and validation demonstrate the system's capability to accurately distinguish between gliomas, meningiomas, and pituitary tumours, providing clinicians with a reliable tool for improved diagnosis and patient care.

Keywords: Classification system, ResNet50 architecture, Deep learning Convolutional neural network, MRI scans

Abstract: Health has become a major concern in today's generation. In this world every person is undergoing one or more problems regardless of age, the problem may be related to any parts of the human body. Due to the hectic schedule, forgetting things become the major problem nowadays. So the people or the old age one's forget to take their prescribed pills at proper time. When a people are in high medications, it can lead to confusion, so they may undergo over dosage or under dosage. Medicine reminder helps to the user to regularly track their health conditions even with the absence of the caretaker. Thus this paper is going to help the old age people to consume their prescribed pills without physically in touch with the caretakers. The proposed system becomes a bridge between medical field and technology. This aims in addressing the issue related to medication non-adherence by providing personalized reminders and assisting the users. So the proposed system integrates a camera and MAX30100 sensor has an additional feature, which improves medication adherence and also provides real-time video stream updates and keep track of patient's overall healthcare conditions.

Keywords: Arduino Uno, RTC module, IR sensor, MAX30100 sensor, Pill box, Servo motor.

Abstract: Most of the time, due to the failure of the GPS in indoor locations, the accuracy of navigation and guidance will be very poor which in turn provides inaccurate and biased results. This project proposes a novel solution leveraging ESP8266 devices and RSSI technology to achieve accurate and real-time positioning within indoor environments. By deploying ESP32 device strategically, including a Bluetooth module, MPU 6050 mounted on a car and fixed nodes mounted on walls, the system measures signal strength and calculates distances using RSSI to navigate the car to the desired location.

Keywords: Global Positioning System (GPS), Received Signal Strength Indicator (RSSI), Espressif (ESP8266), Bluetooth, Magnetic Pick Up (MPU).

Abstract: Kasaragod, the last formed district in Kerala, is famous for the cultural symbiosis and use of seven local languages. The pluralistic cultural background of Kasaragod is reflects in various art forms and also the lifestyle of the people. The place was one of the major centers of foreign invasion, freedom movement and also the migration of different religions particularly Jainism, Islam and Christianity. But, nowadays it is famous for the violation of human rights with the use of a pesticide known as Endosulfan. The pesticide sprayed in the cashew plantations of Kasaragod from 1978 onwards which ultimately caused for many health issues to the people including the new born babies in this area. It resulted in diseases ranging from physical deformities, cancers, birth disorders and damages to brain and nervous system. People are still dying from the after-effects of the pesticide and hundreds of people are now living in utter misery. It destroyed not only the dreams and desires, but also the right of a group of people to live without fear. The environment activists generally considered it as an utter violation of the human right mainly for protecting the needs and interests of the Plantation Corporation in Kerala.

Keywords: - Endosulfan, Pesticide, Plantation, Health Issues, Human Rights Violation etc.

Abstract: Computer science is experiencing rapid growth. Reconstructing cooking recipes from photos of food presents an intriguing challenge. The goal is to create complete recipes with ingredient lists, titles, and comprehensive instructions using convolutional layers in CNNs. About identifying complex patterns in food photos, this study clarifies the capabilities and limitations of CNNs by assessing critical performance metrics like recipe generation accuracy and efficiency. This work helps the culinary industry develop new technological solutions in response to the increasing need for a thorough understanding of meal preparation. Moreover, the implications of this research go beyond computer science, as it has the potential to drastically change how people interact with food. This research opens the door to a more diverse and interconnected culinary landscape by democratizing culinary knowledge and fostering a deeper understanding of global gastronomic traditions. In the end, this study's conclusions will guide future research into creating AI-powered culinary apps that are customized to each user's unique preferences and tastes, enhancing the appreciation of cooking around the world.

Keywords: Convolutional Neural Networks (CNNs), computer vision, culinary exploration, cooking instructions, deep learning architectures, Recipe1M dataset, image-to-recipe prediction, natural language processing, AI-driven culinary applications.

Abstract: This project focuses on the development of a fruit sorting system utilizing Raspberry Pi and machine learning techniques. The primary objective is to implement an automated system capable of detecting and sorting tomatoes based on their ripeness. The system utilizes a Raspberry Pi for object detection using the Haar Cascade algorithm and analyzes the color of the detected tomatoes to determine their ripeness. The determined data is then transmitted to an Arduino, which controls a servo motor to sort the tomatoes accordingly. This abstract provides an overview of the project's methodology, key components, and anticipated outcomes.

Keywords: Raspberry pi, Haar cascade algorithm, Arduino uno

Abstract: Duplex stainless steel (DSS), which consists of austenite and ferrite phases are widely use in chemical, petrochemical, offshore, railway and power generation sectors due to its excellent corrosion resistance, high strength, and easy formability. The Cold metal transfer (CMT) is an advanced method of droplet detachment for a dip transfer arc welding process. CMT mode of metal transfer in Gas Metal Arc Welding (GMAW) process used to develop butt welding in 8 mm plates of EN 1.4462 (2205) grade. General corrosion behaviour was determined by potentiodynamic in 0.1%N H2SO4 solution, while pitting corrosion susceptibility was studied by cyclic polarization test in 3.5 %NaCl solution. Pitting and crevice corrosion test performed as per ASTM G48 method A and B respectively. The findings demonstrate good general and pitting corrosion resistance with lower weight loss. Cyclic polarization results show greater value of Erp which indicates that after the damage of passive film in DSS once again passivated and if pitting initiates, it will not propagate because of passive film formation.

Keywords: Duplex Stainless steel, Cold metal transfer, Pitting corrosion, Crevice corrosion, Potentiodynamic test, Cyclic polarization test.

Abstract: In today's rapidly advancing technological landscape, the ubiquitous presence of mobile devices has become a defining characteristic of modern society. From smartphones to tablets, laptops to wearable gadgets, these devices have seamlessly integrated into both personal and professional spheres, driving the need for efficient and accessible charging solutions. Traditional reliance on fixed charging stations or wall outlets often proves inconvenient, particularly in public spaces, outdoor events, or during travel where access to power sources may be limited. Moreover, the rise of smart technologies and cashless transactions has spurred the exploration of innovative charging solutions that cater to evolving preferences and requirements. In response to these challenges, the Coin and Smart Card-Based Mobile Charging System emerges as a pioneering endeavor ,leveraging microcontroller technology, sensor systems, and RFID authentication to revolutionize the way electronic devices are powered. This abstract provides a comprehensive overview of the system's objectives, significance, and anticipated contributions to the realm of mobile charging technology.

Abstract: In today's culture, blind people face major problems in maintaining their independence and safety. Traditional techniques of navigation and obstacle detection frequently require human aid, restricting the blind's autonomy. To address these challenges, we introduce the notion of an IoT-based smart shoe for the blind. This revolutionary idea seeks to empower blind people by providing real-time support in navigating their environment. Our smart shoe, which uses IoT and artificial intelligence technology, incorporates sensors, microcontrollers, and communication modules to identify obstructions and send audible or vibratory notifications to the user. Our technology improves the user's ability to recognize and avoid obstacles more accurately by enhancing movement. This technology aims to improve the blind community's freedom and quality of life by boosting mobility and lowering reliance on external help, as well as encouraging inclusivity and accessibility in society.

Keywords: Obstacle detection, Embedded C, Sensor, Microcontrollers.

Abstract: This paper covers design of compact BALUN transformer using Klopfenstein transformer. The verification of BALUN is done through three different approaches. First approach is to connect 100 Ω SMD resistor and then using two different dipole antennas covering Bluetooth and WiMax applications. All the measurements are satisfactory and confirms the successful design of compact Klopfenstein BALUN transformer.

Keywords: Coplanar stripline, Bluetooth, WiMAX, BALUN, taper transformer, Klopfenstein transformer.

Abstract: Concern over the possible dangers of creating realistic-looking but artificial images-known as "deep fakes"-has grown as deep learning techniques, especially Generative Adversarial Networks (GANs), continue to progress quickly. Deepfake medical images are a major danger to patient safety and the integrity of healthcare in the medical industry, where reliable and accurate imaging data is essential for diagnosis and treatment. The goal of this project is to research on a novel deepfake image detecting system specifically for the medical field. We present a novel method to differentiate real medical photos from artificial ones by utilising the power of GANs, which are widely used for image synthesis. Convolutional neural networks (CNNs) and sophisticated anomaly detection methods are combined in the suggested system to efficiently recognise and flag possibly altered medical images. The findings of this study have important ramifications for preserving the accuracy of diagnostic processes, protecting patient safety, and upholding the integrity of medical imaging datasets. Our method advances safe and reliable procedures in the medical domain by tackling the special problems presented by deepfake medical images.

Keywords: Deep learning, Machine learning, Generative Adversarial Networks (GANs), Medical Images

Abstract: Our project focuses on the development of a computer application and the training of a model specifically designed to address the unique needs of individuals with disabilities participating in the standard online examinations, particularly when the assessments heavily rely on visual elements. Our project introduces a voice-enabled examination system tailored for visually impaired students, leveraging Text-to-Speech (TTS) and Speech-to-Text (STT) technologies.

Keywords: Speech recognition, speech synthesis, Natural Language Processing (NLP), Proctoring Systems, Audio Monitoring.

Abstract: Growing inclination toward sustainable and effective fire suppression technologies subsequently drives the market for new technologies. AbstractThis project paper discusses the design and construction of a solar powered fire alarm cum extinguisher. Their system would use solar power, allowing for a constant source of power without greenhouse gas emissions that help drive climate change in the way batteries used to power conventional fire extinguishers do. The next solar-powered fire extinguisher will have been equipped with high-grade sensors and AI algorithms for the real-time tracking and analysis of burning incidents. Not only does the integrated fire alarm system immediately trigger extinguishing action, but it also alerts those on-site as well as emergency response services. This networked approach improves the overall efficiency of fire suppression systems and makes an intelligent and robust solution for both domestic and non- domestic areas Similarly, the aim of the project is to find out if this kind of a solar powered fire extinguisher can be cost-effective, reliable and adapt itself to different locations. This project advances the mission of developing sustainable and effective solutions for fire prevention systems, emergency response, while also utilizing alternative energy sources

Keywords: Solar Energy, Renewable Energy,Fire Extinguisher, Fire Alarm.

Abstract: In the era of smart homes, the "Smart Switch Board" project aims to revolutionize traditional home appliance control by integrating Bluetooth technology and touch switches into a centralized system. The core components of the system include touch switches, Bluetooth modules, and a NodeMCU microcontroller, providing both tactile and voice-controlled automation capabilities. The touch switches serve as the interface for manual control, allowing users to interact with their home appliances effortlessly. Simultaneously, the integration of Bluetooth technology enhances the project's versatility, enabling voice-controlled commands for a hands-free experience. The NodeMCU microcontroller acts as the brain of the system, orchestrating communication between touch switches, Bluetooth modules, and connected appliances. Through this centralized hub, users gain the ability to manage multiple devices remotely, fostering a seamless and interconnected smart home environment. This project not only introduces convenience but also contributes to energy efficiency and sustainability. By automating the control of home appliances, users can optimize their energy consumption, leading to reduced environmental impact. In conclusion, the Smart Switch Board project represents a leap forward in home automation, combining tactile and voice-controlled functionalities to create an intelligent and user-friendly solution for modern living.

Keywords: Proximity Switch Sensor, Solenoid Electric Lock, Fingerprint Reader Sensor Module, Digital Temperature Controller.

Abstract: The abstract serves as a concise overview of our research paper, which delves into the fusion of facial recognition technology and IoT devices to elevate elderly care in assisted living environments. Through a systematic investigation, we assess the efficacy of this novel system in monitoring residents' well-being and swiftly responding to emergencies. Our methodology entails deploying cameras embedded with facial recognition software and IoT sensors throughout the facility, enabling real-time data collection to detect distress signals and trigger alerts for timely caregiver intervention. Our findings underscore significant enhancements in the responsiveness and effectiveness of elderly care, fostering a safer environment and providing reassurance to residents and their families. This research underscores the transformative potential of technology-driven solutions in addressing the evolving needs of an aging population within the healthcare landscape.

Keywords: facial recognition, IoT, elderly care, emergency response, healthcare technology.

Abstract: Titled "VIRTUAL GAME FOR ASTHMA PATIENTS," this project presents an IoT-based PyGame designed to address the challenges faced by asthma patients. Asthma, a prevalent respiratory condition affecting millions worldwide, necessitates effective management for improved quality of life. In response, our Virtual Game project offers a novel approach to educate and support individuals in managing their asthma effectively. Combining hardware components like NodeMCU, a Respiration Sensor, and a 16x2 LCD with Pygame-powered software, the project creates an engaging and informative virtual gaming experience. These hardware elements collaborate to monitor users' respiration rate and quality, providing real-time insights into their breathing patterns. This data dynamically influences gameplay, immersing players in a virtual world where they must manage their character's asthma by controlling their breathing. Through interactive gameplay, users acquire deeper insights into proper breathing techniques and effective asthma management strategies.

Abstract: The Solar Mobile Charger harnesses solar energy for on-the-go device charging. In response to the increasing demand for sustainable charging solutions in of portable electronic devices, this research paper presents an in-depth exploration of the Solar Mobile Charger integrated with a Power Bank Module. With a focus on environmental sustainability, efficiency, and versatility, this project introduces a comprehensive approach to harnessing renewable solar energy for on-the-go device charging. The Solar Mobile Charger employs photo voltaic technology, serving as the primary energy source, while a 7805 voltage regulator enhances system efficiency by optimizing solar energy conversion. Coupled with a Power Bank Module, this integrated solution not only promotes sustainability but also reduces dependence on nonrenewable energy sources, liberating users from traditional power outlets and enabling charging anywhere. The Solar Mobile Charger with 7805 voltage regulators and Power Bank Module emerge as a viable and sustainable solution, symbolizing the potential of renewable energy in addressing modern-day power consumption challenges. Keywords- Solar Energy, Energy Crisis, Renewable Energy, Solar Charger, Solar power bank mobile charger.

Abstract: Managing finances efficiently is crucial in today's world. However, traditional financial AI platforms often present significant challenges, including high costs, complex interfaces, and lack of personalization, which can discourage users from taking full advantage of their services. FinanceGPT is a new cross-platform financial AI platform that addresses these challenges and aims to revolutionize the way people manage their finances. Powered by advanced natural language processing (NLP) algorithms, FinanceGPT offers personalized financial services and insights tailored to each user's unique needs and goals. From budgeting to investing and planning for the future, FinanceGPT provides intuitive tools and recommendations to help users make informed decisions with confidence. One of FinanceGPT's key features is its cross-platform accessibility.

Keywords: Natural Language Processing, Artificial Intelligence, Machine Learning, Finance, Cross Platform

Abstract: The "Auto Speed Control System" project aims to enhance vehicle control using RFID technology and Arduino. The fundamental idea involves the creation of a robot setup with components such as Arduino, Motor driver, DC motors, LCD display, RFID reader, and Bluetooth module. The system utilizes RFID cards to identify specific zones, with each zone associated with a predefined speed limit. When a particular RFID card is detected, it signifies entry into a specific zone, and the corresponding speed limit is communicated to the vehicle. The implementation includes a detailed setup where Arduino processes information from the RFID reader, interprets the designated zone, and displays this information on an LCD screen. The system also integrates Bluetooth technology, allowing for the wireless adjustment of the vehicle's speed. This enables real-time control and modification of the vehicle's speed based on the detected zone. In summary, the Auto Speed Control System seeks to provide an intelligent and automated approach to regulating vehicle speed by employing RFID technology for zone identification and Arduino for processing and control. The integration of Bluetooth adds a layer of flexibility, enabling dynamic speed adjustments based on specific requirements or conditions. This project has applications in enhancing safety, efficiency, and control in various environments.

Keywords: Arduino UNO, RFID Reader Module.

Abstract: When cement concrete is subjected to significant shrinkage and settling, the existence of voids in the material may cause a decrease in performance. This study concentrated on using bacteria to decrease concrete voids and increase performance. It was discovered that the Bacillus family of bacteria were the concrete's greatest healers. In the current investigation, Bacillus megaterium bacteria from the Bacillus family were used at a concentration of 108 CFU. After seven and twenty-eight days of curing, a total of forty-eight specimens were cast and examined for mechanical strength and water absorption. In comparison to conventional M30 grade, the test results show that after 28 days of curing, the compressive, split tensile, and flexural strengths increased to 12.91%, 10.28%, and 9.02%, respectively.

Keywords: Bacterial concreate, Bacteria with cement,

Abstract: The "Anti-Theft Floormat" project innovatively merges piezoelectric sensors with Arduino microcontrollers to transform ordinary floormats into intelligent security devices. By embedding sensors, it detects unauthorized access by converting footsteps into electrical signals. The Arduino acts as the central processor, monitoring sensor data and triggering an alarm when pressure exceeds a set threshold, alerting occupants in real-time. Power management is a focus, utilizing Arduino's sleep modes to balance responsiveness and energy efficiency, optimizing performance while conserving power during idle times. This project reimagines security systems, addressing vulnerabilities overlooked by conventional methods, offering a versatile and effective solution for homes and offices

Keywords: Anti-theft device, Piezoelectric sensors, Home security, Security innovation.

Abstract: Our nation relies on grains for agricultural revenue, with rice being a primary crop. The quality of milled rice determines its commercial viability, impacted by contaminants like stones and weed seeds. While grain testing is partly automated, human labor remains essential. Ensuring food grain quality affects supply chain profits, especially varietal purity, though the process is time-consuming. Advanced techniques like GLCM and CNN aid in quality assessment and contaminant detection, streamlining the labor-intensive process for farmers.

Keywords: GLCM, support vector machine, image processing, Convolutional Neural Networks, quality assessment.

Abstract: This project presents a comprehensive solution for vehicle speed detection using an Infrared (IR) sensor and an ESP32 camera module. The primary objective is to design an efficient and cost-effective system capable of accurately measuring and monitoring the speed of vehicles on the road. The IR sensor is employed to detect the presence of a vehicle by measuring the interruption of the IR beam. Once a vehicle is detected, the ESP32 camera captures images to log the event and provide visual evidence. The system calculates the speed of the vehicle by measuring the time taken to travel between two predefined points with known distance apart. The combination of the IR sensor and ESP32 camera allows for real-time speed monitoring and data logging, which can be utilized for traffic management, law enforcement, and research purposes. The ESP32's robust processing power and wireless communication capabilities enable remote monitoring and integration with IoT platforms for advanced data analytics. This project demonstrates the feasibility of using affordable components to build a reliable vehicle speed detection system, offering potential improvements in traffic safety and management efficiency.

Abstract: In the evolving landscape of smart cities, efficient traffic management is paramount to reducing congestion, minimizing accidents, and improving urban mobility. This paper presents a comprehensive approach to road vehicle detection utilizing the Internet of Things (IoT). The proposed system integrates various IoT devices, including sensors, cameras, and communication modules, to create a robust network capable of real-time vehicle detection and traffic monitoring. Our methodology employs a combination of sensor networks and edge computing to collect and process data locally, thereby reducing latency and enhancing responsiveness. The system architecture is designed to be scalable and adaptable, accommodating various urban environments and traffic conditions. By leveraging advanced data analytics and machine learning algorithms, the system can accurately identify vehicle types, count traffic flow, and detect anomalies such as accidents or traffic violations. To validate the effectiveness of the proposed system, extensive simulations and field tests were conducted in diverse traffic scenarios. The results demonstrate significant improvements in detection accuracy, real-time data processing, and overall system reliability. Moreover, the IoT-based vehicle detection system offers a cost-effective solution with potential applications in intelligent transportation systems, automated toll collection, and enhanced road safety measures. The integration of IoT in road vehicle detection presents a transformative approach to traffic management, promising smarter and more efficient urban transportation infrastructures. Future research directions include the enhancement of sensor fusion techniques, integration with autonomous vehicle systems, and the exploration of 5G networks to further augment system capabilities.

Keywords: Node MCU, Ultra-Sonic sensor, Power supply, IoT.

Abstract: At the beginning and end of each session, attendance is an important aspect of the daily classroom evaluation. When using traditional methods such as calling out roll calls or taking a student's signature, managing attendance can be a time-consuming task. The teacher normally checks it, although it is possible that a teacher will miss someone or some students' answers many times. Face recognition-based attendance system is a solution to the problem of recognizing faces for the purpose of collecting attendance by utilizing face recognition technology based on high-definition monitor video and other information technology. Instead of depending on time-consuming approaches, we present a real-time Face Recognition System for tracking student attendance in class in this work. After the recognition is completed, the attendance will be immediately updated in a Database with the relevant information. Many institutions will profit greatly from this endeavour. As a result, the amount of time it takes and the number of human errors it makes are minimized, making it more efficient.

Keywords: Face Detection, Face Recognition, Attendance, OpenCv.

Abstract: Sharing multimedia data is becoming a more and more necessary component of daily life for users to access various systems, services, and applications. with the actual world, data exposure happens often with cloud storage services. In safe data transfer medium, authentication and copyright protection of multimedia materials have long been issues. utilization of modern technology and the Internet, the problem has gotten worse. Making copyright protection is more challenging and complex, though. The copyright protection issue has a solution: digital watermarking. Both watermarking and the Proxy Re-encryption (PRE) methodology are employed in the suggested method for effective sharing of multimedia material. In digital material like photographs, watermarking is used to conceal information like secret information. Data security is achieved using encryption methods. In order to prevent unauthorised access, information is encoded using encryption, making it impossible for anyone who are not authorised to view it. In the proposed approach, a key may be used to encrypt a secret key using an encryption method. The user's private key may then be integrated into the picture using LSB (Least Significant Bit), along with encrypted key information. Images may be encrypted using the ECC Encryption technique once secret information has been included. With the aid of the inbuilt data verification procedure, the decryption key may finally be extracted by an authorised user. When user Data does not correspond embedded information, illegal or unauthorised access can be recognised.

Abstract: The System aims to redefine traditional notice boards by integrating a microcontroller, MQTT, and an I2C LCD display. Through a physical button interface, users input data, transmitted via MQTT, leading to real-time updates on the LCD display. This innovation bridges web-based inputs with hardware communication, offering seamless and instant information dissemination. It revolutionizes communication in educational institutions, public spaces, and offices, allowing remote updates for notices, messages, or alerts. By merging IoT technology with a button-controlled microcontroller, the system enables dynamic content delivery, enhancing communication efficiency. This versatile solution transforms static notice boards into dynamic displays, facilitating swift and impactful information sharing. Its integration of web-based inputs, MQTT communication, and a user- friendly interface creates a novel platform for efficient, real-time communication in diverse environments.

Keywords: Node-MCU; LCD Display; I2C Adapter; Buzzer

Abstract: Lung cancer is a kind of cancer that originates in the lungs and cannot be prevented in its late stages of development, but its risk can be reduced using the sessions. As a result, quick detection of lung cancer can help to lower the survival rate. The number of chain smokers is probably equal to the number of people affected by lung cancer. The lung cancer is predicted using the Logistic Regression. The study employs logistic regression to analyse categorical datasets. After evaluating parameters and assessing the significance of each influencing attribute, the model undergoes testing. This process yields 18 prediction models and identifies factors correlating with disease size risk. Utilizing logistic regression, the study predicts lung cancer occurrence in patients based on various factors such as symptoms, habits, and health history. Notable symptoms associated with lung cancer include smoking, alcohol consumption, swallowing difficulties, coughing, chronic ailments, fatigue, and age.

Keywords: Prediction, Logistic Regression, Machine Learning.

Abstract: Concrete is widely used construction materials. However, the production of Portland cement releases large amount of CO2 (carbon dioxide), a greenhouse gas. One ton of Portland cement clinker production releases approximately one ton of CO2 and other gases. Environmental issues are playing essential role in the sustainable development of concrete industry. Metakaolin is mainly used as a mineral admixture in cement and concrete. Compared to silica fume and fly ash, metakaolin has a very high reactivity level. Previous studies have shown that metakaolin can increase the mechanical strength of concrete to varying degrees, depending mainly on the replacement rate of metakaolin, the water/binder ratio, and the age at testing Remarkably, metakaolin has a positive effect on reducing drying shrinkage and improving durability.

Keywords: Compressive Strength, metakaolin, Normal curing, Accelerated curing.

Abstract: Due to the fact that it contains vital information about human emotional states, facial expression is a powerful means for humans to communicate. It is a vital component of computing systems that are competent at identifying human emotions and responding to them more appropriately. However, the challenge of automatically recognizing various facial expressions makes the automated recognition of facial expressions a significant issue in human-system interactions, human emotion appraisal, and decision making. Facial expression detection has therefore become a hot area for research in the domains of image processing, pattern recognition, machine learning, and human reputation in addition to human-computer interaction. With the help of the HAAR CASCADES set of rules and the Support Vector Machine set of rules, we may use techniques in this mission to robotically identify face features and categories emotions. Using a K-Nearest Neighbor technique, provide a playlist of songs that are suited for his current state of mind. You may include a glance at photo of an expression you want to be recognized while trying out a feature. This look-at image may be compared to face database files to play music based on identified emotions. Finally, a player with an advanced recognition rate that is fully emotion-based is offered.

Abstract: This project investigates the design and implementation of an automatic temperature-based fan speed controller with digital use a fan speed controller Arduino. The system employs a temperature sensors to continuously monitor the ambient temperature, and Arduino microcontroller processes this data to dynamically adjust fan speed accordingly. By integrating a feedback loop, the controller ensures efficient cooling while minimizing energy consumption. The project aims to provide a cost-effective and user-friendly solution for maintaining optimal temperature conditions in various environments, contributing to energy efficiency and automated

Keywords: Temperature, Fan, Speed, PWM.

Abstract: IoT is the boon for industries with capabilities to digitize complete industry process, system, software's and machineries on one single platform. The capability enables the 360 degree view of the industry. The security concerns is very important while implementing the IoT, since it become crucial for any IoT or IIoT project to implement the security else since IoT application has direct access on internet hence it become more prone to internet attacks hence to avoid we need to have high security which ensures full proof system for this we can have integration of block chain technologies with IoT.

Keywords: IoT, IIoT, Blockchain, Privacy, Security.

Abstract: This study examines how investors at ValueLabs, a technology-focused company, use artificial intelligence (AI) to influence their purchasing and selling decisions. The study investigates how individual investors use AI-based tools like algorithmic trading platforms, robo-advisors, and predictive analytics in their investment decisions as a result of AI's growing integration into financial markets. The study uses descriptive and correlation analysis to look at usage trends, perceived benefits, related risks, and the general dependability of AI tools. It is based on primary data that was gathered from 230 investors using structured questionnaires. The results show that a significant percentage of investors actively use AI, with the most common users being younger and mid-level professionals. AI is recognized for facilitating enhanced market trend analysis and quicker decision-making, both of which are essential for prompt investment decisions. Nevertheless, the study also reveals important user concerns, such as inadequate human oversight, lack of transparency, and data security. Interestingly, despite the widespread use of AI, most investors are hesitant to suggest these tools to novices because of their complexity and possible hazards. The study comes to the conclusion that although AI has improved efficiency and analytical capacity, which has improved individual trading behavior, overcoming significant obstacles is necessary for its successful integration into the investment process. Expanding its safe and efficient use will require raising system transparency, enhancing AI literacy, and creating tools that are easy to use for a range of investor types. By providing insights into actual investor perspectives in a technologically sophisticated corporate setting, this study adds to the expanding body of knowledge on artificial intelligence in financial markets.

Keywords: Artificial Intelligence (AI), Stock Trading, Robo-Advisors, ValueLabs Investors.