VOLUME 11, ISSUE 12, DECEMBER 2024

Abstract: A mathematical model of turbulent fluid flow over a porous aerofoil wing design within a magnetic field is considered. The fluid flow was modelled using Navier stokes equations of conservation of momentum, energy and mass in cylindrical coordinates. The governing equations were then non-dimentionalized and gave rise to the non-dimensional parameters. Computational fluid dynamics (CFD) techniques was used to simulate the flow of air over a porous wing within a range of magnetic field strengths. Examinations of the effects of the magnetic field on key performance metrics such as lift, drag, and efficiency, as well as the overall flow structure of the wing was performed and found valuable insights into the use of porous aerofoil wings in the design of aircraft operating in high-magnetic field environments, such as those found in space or near the Earth's poles. Additionally, the outcomes of the research had wider implications for other domains investigating the impact of magnetic fields on fluid motion, such as in the design of magnetic resonance imaging systems or in the study of planetary motions. Aerofoil wings are an essential component of aircraft design, as they provide lift and enable flight. However, the flow of air over the wing is often turbulent, which can lead to decreased efficiency and performance. Porous aerofoil wings was proposed as a means of reducing turbulence, and the effects of such wings on fluid flow within a magnetic field have been thoroughly investigated. In this research, numerical investigation of the effects of a magnetic field on turbulent fluid flow over a porous aerofoil wing design was done. It is evident from the results that the primary velocities increase when the magnetic parameter was reduced. It was also found that the lift force increases when the Grashof number and Prandtl number decreases.

Keywords: Turbulent, Porous medium, Aerofoil, Prandtl number, Magneto hydrodynamics.

Abstract: The Abaoub-Shkheam Decomposition Method (QDM) is employed in this paper to solve nonlinear initial value problems of second order. Adomian polynomial is used to decompose nonlinear functions that exist in a given equation. We are using this method (QDM) to find the exact solution of different types of non-linear ordinary differential equations, which is based on the Abaoub Shkheam transform method (QTM) and the Adomian Decomposition Method (ADM). An example is provided to demonstrate the efficacy of this approach.

Keywords: Ordinary differential equations, Abaoub Shkheam transform, Adomian Decomposition Methodise.

Abstract: In the pursuit of efficient and sustainable energy storage solutions, nanocomposites have emerged as a pivotal material class, offering remarkable enhancements in mechanical, thermal, and electrical properties. This comprehensive review examines the integration of nanoparticles such as carbon nanotubes (CNTs), graphene, and nanoclays into various matrix materials, including polymers, metals, and ceramics-to significantly improve the performance of energy storage systems. The paper discusses the application of nanocomposites in lithium-ion batteries, supercapacitors, and other storage devices, highlighting how these materials contribute to superior energy density, charge/discharge rates, and overall device durability. Additionally, the review addresses the current challenges in the field, including issues related to material synthesis, scalability, and long-term stability. Future research directions are proposed, focusing on advanced functionalization techniques, real-time performance monitoring, and environmentally friendly production methods. This study underscores the transformative potential of nanocomposites in advancing energy storage technologies, thereby supporting the global shift towards renewable energy sources.

Keywords: nanocomposites, energy storage, carbon nanotubes, renewable energy, scalability, durability.

Abstract: This mixed method research aimed to determine the influence of metacognitive strategies to the conceptual learning and scientific reasoning of the STEM students. This was conducted to the 312 out of 1411 grade 12 STEM students of public schools in the province of Capiz for the school year 2023-2024. Stratified sampling were employed in the sample. The data were gathered using a 37- item Conceptual Learning Test where questions were adopted from the General Chemistry 1 Modules provided by the Department of Education was utilized for conceptual learning and 24- item adopted Scientific Reasoning Test from Lawson Scientific Reasoning Test was used for the scientific reasoning. An adopted 52 items Metacognitive Strategies Questionnaire from Schraw and Dennison (1994) was utilized to determine the metacognitive strategies employed by the students. In order to validate and verify detailed and relevant information, a Focus Group Discussion (FGD) was utilized for STEM students to gather data from Grade 11 STEM students of different schools for the Focus Group Discussion. The guide questions consist of 11 questions. The descriptive statistics used were the frequency count, mean, and standard deviation while One-way Analysis of Variance (ANOVA) and Pearson r were used for inferential statistics. All inferential tests were set at 0.05 alpha level of significance. The findings showed that the level metacognitive strategies of the STEM students was high. In terms of subcomponents under the knowledge about cognition, subdomain procedural knowledge was "high" and the highest among the three, followed by the declarative knowledge which was "high" and the conditional knowledge as "high" also. On the other hand, the highly utilized in the regulation of cognition subdomains was debugging which was "high", information management strategies was "high", and evaluation was "high". However, the planning was "moderate" and the comprehension monitoring was the lowest as "moderate also. The overall level of conceptual learning of the STEM students was moderate. The subcomponent concrete was "high", identity and classification were "moderate", and formalization was "low". The overall level of scientific reasoning of the STEM students was low. In terms of its subcomponents, conservation was "low", proportional reasoning was "low", identification and control of variables was "low", probabilistic and combinatorial reasoning was "low", and hypothetical-deductive was "high". There was no significant difference in scientific reasoning among the levels of metacognitive strategies of STEM students. There was a significant difference in scientific reasoning among the levels of conceptual learning of STEM students. Lastly, there was no significant relationship between metacognitive strategies and conceptual learning and between metacognitive strategies and scientific reasoning. On the other hand, there was a significant relationship between conceptual learning and scientific reasoning of the STEM students.

Keywords: Metacognitive strategies and scientific reasoning

Abstract: The integration of artificial intelligence (AI) into health informatics is a transformative shift in healthcare that has been witnessed in various aspects, especially in terms of early diagnosis and monitoring of diseases. With the use of predictive analytics and real-time data processing combined with machine learning models, AI has empowered healthcare practitioners to make more informed decisions, optimize patient care, and improve health outcomes. The current paper covers diverse applications of AI in health, where focus will be placed on analysis from EHRs, wearable device information, and medical images to provide information on disease onset forecasts, patient conditions tracking, and personalized treatment planning. Real-life examples are made use of in case study applications to explain the concreteness AI has bestowed on areas like cancer diagnostics, cardiovascular monitoring, and chronic disease management. These examples demonstrate the possibility of AI in the detection of hard-to-spot patterns and risk factors that otherwise would have gone unattended, leading to earlier interventions and more specific and accurate management of health conditions.The paper presents both the huge potential benefits and critical ethical considerations around the use of AI in healthcare. These include data privacy, algorithmic bias, and the transparency of decision-making processes; emphasis is placed on developing proper regulatory frameworks, creating AI systems with the underlying principles of fairness, accountability, and trust in patients. The paper concludes by urging a holistic approach to the deployment of AI, appropriately addressing technical and ethical challenges in order to have AI technologies used in ways that promote equitable, efficient, and effective healthcare delivery.

Keywords: Health Informatics, Artificial Intelligence, Early Diagnosis, Disease Monitoring, Predictive Analytics, HER

Abstract: An amphibious hovercraft is a versatile vehicle designed to travel across both land and water, providing unparalleled mobility in challenging environments. By utilizing a cushion of air generated by large fans, it can glide over various surfaces, including water, mud, ice, and sand. This makes it ideal for operations in flood-prone areas, wetlands, and rough terrains where traditional vehicles might struggle. The hovercraft's ability to operate seamlessly between land and water enables rapid response in emergency situations, such as rescue missions and disaster relief. Additionally, its applications extend to military, transportation, and recreational uses. Despite its benefits, challenges like fuel efficiency, noise, and maintenance need to be addressed for widespread adoption. Modern amphibious hovercrafts are often equipped with advanced technologies such as GPS navigation, sophisticated propulsion systems, and durable materials to enhance performance and reliability.

Keywords: Skirt Design, Hybrid Propulsion, Durable Materials.

Abstract: Assistance for any person with disability in movement is always necessary. Spinal cord injuries, strokes and many more are the reasons for paralysis. In view point of the people with paralysis who can move their finger , we have designed an assistance and remote-control system. Our system differs from traditional assistance systems and methods which require a large hardware setup and bulk software coding which is not feasible to the patient. Our model helps people with paralysis to control their surroundings like controlling the home automation such as bulb, fan etc. For their basic needs such as food, water and many other based on their requirements or any other device using GPS, GSM Modules which helps to track the patent's location to the respective person through simple operations. This proposed model deals with flex sensor placed on finger. It picks up bending in finger and translates to a selective control. Further the Arduino micro-controller is used which assists the patient and communicates the patient's condition to the concerned person using one of its units in case of emergency.

Keywords: Hand Glove, Flex sensors, GSM and GPS modules, Home automation, IOT

Abstract: Large language models (LLMs) like GPT-4 have shown potential in generating scientific feedback on research papers, but their effectiveness is limited by vagueness, a lack of domain-specific insights, and insufficient technical critiques, especially regarding model architecture and design. This study aims to address these limitations and enhance the LLM-based feedback system for research papers. The identified gaps include the need for specific, actionable feedback and domain-specific expertise. Our multi-faceted approach includes fine-tuning LLMs with domain specific datasets, incorporating expert-driven feedback, and focusing on detailed, section-specific comments. We also introduce specificity metrics, hybrid models combining LLM and human reviews, and iterative feedback mechanisms. These strategies aim to enhance the quality and utility of LLM-generated feedback, making it more actionable and aligned with expert human reviews. The proposed improvements could significantly reduce the number of review cycles before publication, providing timely and relevant feedback to authors. This research fills critical gaps in existing feedback systems, offering a robust solution to improve the academic review process.

Keywords: Large Language Models (LLMs), GPT-4, Scientific Feedback, Domain-Specific Datasets, Expert-Driven Feedback, Section-Specific Comments, Specificity Metrics, Hybrid Models, Academic Review Process.

Abstract: Wireless charging is a type of charging method which uses an electromagnetic field to transfer energy through electromagnetic induction. Energy is transferred between devices (transmitter and receiver) through the process of mutual induction. Power from solar is given as input to transmitter inductive coil, the receiver inductive coil receives the power and converts it into electric current to charge the battery. Solar panels convert solar energy into electricity. They use the concept of photoelectric effect, emission of electrons when light falls on solar panel. Solar panels are made up of silicon cells, silicon has an atomic number 14. When light falls on silicon cell, the outer most electrons of silicon i.e. two electrons are set into motion. This initiates the flow of electricity. Silicon has two different cell structures: monocrystalline and polycrystalline Monocrystalline solar panels are manufactured from one large silicon block and are made in silicon wafer formats. Polycrystalline solar cells are also silicon cells, which are produced by melting multiple silicon crystals together. Wireless Power Transfer (WPT) utilizing attractive reverberation is the innovation which could set human free from the irritating wires. Indeed, the WPT embraces a similar essential hypothesis which has just been created for something like 30 years with the term inductive power exchange. Recently WPT innovation is growing rapidly at control level. The makes the WPT very useful to the electric vehicle (EV) charging applications in both stationary and dynamic charging situations. This project surveyed the advancements in the WPT to EV remote charging. By presenting WPT in EVs, charging system can be effectively relieved. Battery innovation is never again pertinent in the mass market entrance of EVs. It is trusted that specialists could be supported by the cutting-edge accomplishments, and push forward the further improvement of WPT just as the extension of EV.

Abstract: The integration of Counterfeit Insights (AI) in farming has revolutionized traditional cultivating hones by upgrading productivity, productivity, and maintainability. This literature overview investigates the different AI procedures and their applications in horticulture, counting crop observing, bug discovery, abdicate expectation, and exactness cultivating. Through a comprehensive survey of later ponders, we highlight the headways, challenges and prospects of AI in agriculture.

Keywords: Artificial Intelligence, Agriculture, Precision Farming, Crop Monitoring, Yield Prediction, Pest Detection

Abstract: Water pollution is a global issue, endangering health, ecosystems, and sustainability. Traditional methods of water quality assessment are slow and labor-intensive, delaying contamination detection and increasing the risk of waterborne diseases. This paper presents a low-cost, efficient system for real-time monitoring of key water quality parameters, such as pH, turbidity, temperature, TDS, and flow rate. The system uses sensors integrated with an Arduino microcontroller for continuous data collection, displaying real-time results on a TFT screen. Alerts are triggered when parameters exceed set thresholds, enabling timely intervention. Advanced calibration algorithms ensure accurate readings, while low power consumption supports long-term deployment in remote areas. The system is designed for easy use by both technical and non-technical users, providing reliable, cost-effective monitoring for improved decision-making in various environments.

Keywords: Water monitoring, Microcontroller, Turbidity sensor, PH sensor, Cloud

Abstract: This study presents the design and development of smart billing trolley using RFID. Radio Frequency Identification (RFID) technology offers a promising solution to these challenges. Unlike barcode systems, RFID does not require line-of-sight scanning. RFID tags embedded in products can be automatically read by an RFID reader, enabling faster and more efficient data collection. The system aims to revolutionize the shopping experience by automating the billing process and enhancing customer satisfaction. The concept of a smart trolley equipped with an RFID reader is an innovative approach to streamline the shopping and billing experience. By integrating RFID technology into shopping carts, items placed in the trolley can be automatically identified and billed in real time. This eliminates the need for manual scanning at the checkout counter and significantly reduces the time spent in queues. Additionally, this system provides an opportunity to enhance inventory management and reduce errors associated with manual data entry.

Keywords: RFID RC-522 , Aurdino UNO Board, 16x2 I2C LCD, load cells .

+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 SURVEY ON STAIR CASE CLEANING ROBOT S. Shajith Ali, Yashwanth M, Vyshak G R, Adithya D,Dr. Rekha N ABSTRACT- The Staircase Cleaning Robot is an innovative solution designed to automate the cleaning of staircases in residential, commercial, and industrial settings. The robot is equipped with advanced sensors for obstacle detection, edge recognition, and precise navigation, ensuring effective cleaning without falling or collisions. It features modular cleaning tools, including brushes and vacuum mechanisms, tailored to remove dust and debris in horizontal surfaces. Powered by a rechargeable battery and the robot can operate autonomously. This device offers a time-saving, efficient, and user-friendly alternative to manual staircase cleaning. Keywords - Autonomous cleaning, obstacle detection, edge recognition, modular cleaning tools, automation, robotics. Downloads: | DOI: 10.17148/IARJSET.2024.111213 How to Cite: [1] S. Shajith Ali, Yashwanth M, Vyshak G R, Adithya D,Dr. Rekha N, "SURVEY ON STAIR CASE CLEANING ROBOT," International Advanced Research Journal in Science, Engineering and Technology (IARJSET), DOI: 10.17148/IARJSET.2024.111213 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

+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 Review on Automated Grass Cutter with Pesticide Sprayer Deeksha H K, Naveen S, Kambhampati Vivek, Mrs. Vishalini Divakar,Nandan K Abstract- The aim of this project is to create an grass cutting and pesticide spraying robot that will decrease pesticide use and human health damage, allowing farmers to be protected and labour intensity can be reduced. The robot will have full route planning and navigation systems, as well as driving control, spraying mechanism and system construction and obstacle avoidance with multi-sensor module integration. The spray robot will be designed, including spraying and grass cutting simulations and analyses. It is used not only to track motion and monitor orientation, but also to compensate for path errors in order to achieve good stability and reliability. Meanwhile, the spraying system will be improved to eliminate leaks and prevent repeated spraying, with automatic sprays varying according to the target. This project proposes a pesticide spraying and grass cutting system which will help farmers in field of agriculture. Keywords- DC Motor, Arduino UNO, GSM Module, Pesticide sprayer, Cutter, Android App Downloads: | DOI: 10.17148/IARJSET.2024.111214 How to Cite: [1] Deeksha H K, Naveen S, Kambhampati Vivek, Mrs. Vishalini Divakar,Nandan K, "Review on Automated Grass Cutter with Pesticide Sprayer," International Advanced Research Journal in Science, Engineering and Technology (IARJSET), DOI: 10.17148/IARJSET.2024.111214 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: Ensuring the safety and productivity of workers in hazardous environments, such as oil refineries, is a critical challenge. This project proposes the development of a Workers Monitoring and Safety Assurance Bot using an ESP32-CAM module. The bot integrates real-time video surveillance, environmental monitoring, and safety alert systems to enhance worker safety and operational efficiency. Equipped with sensors to detect hazardous gases, temperature fluctuations, and motion anomalies, the system provides live video feeds and alerts to a central monitoring hub. By leveraging low-cost, high-efficiency IoT technology, this solution aims to mitigate risks, ensure compliance with safety regulations, and improve incident response times. The implementation is scalable and adaptable to various industrial safety requirements, making it a versatile tool for modern refineries

+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 Literature Survey On Autonomous Uv Sanitization Robot Mrs. Pragati P, Apoorva B, Prajwal Patil ,Pavan Gowda HP, Sowmya A M ABSTRACT- In the context of global health and sanitation, the use of robotics and automation in healthcare environments has gained significant attention. This project proposes an Autonomous UV Sanitization Robot designed to effectively eliminate harmful germs and bacteria in hospitals and similar settings using UV-C light. The robot employs advanced technologies such as LiDAR-based navigation, autonomous path planning, and environmental monitoring. Enhanced safety measures ensure that the UV-C light automatically shuts off in the presence of humans, reducing risks. Preliminary results show the robot's ability to efficiently sanitize surfaces while optimizing resource use. Downloads: | DOI: 10.17148/IARJSET.2024.111216 How to Cite: [1] Mrs. Pragati P, Apoorva B, Prajwal Patil ,Pavan Gowda HP, Sowmya A M, "Literature Survey On Autonomous Uv Sanitization Robot," International Advanced Research Journal in Science, Engineering and Technology (IARJSET), DOI: 10.17148/IARJSET.2024.111216 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

+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 Automated Crime Detection and Alert System via Embedded Deep Learning Dr Devika B, Akshay M S, Lohit S H , Lohith B, Manoj T V ABSTRACT- During the last few decades, surveillance cameras have been installed in different locations. Analysis of the information captured using these cameras can play effective roles in event prediction, online monitoring and goal-driven analysis applications including anomalies and intrusion detection. Nowadays, various Artificial Intelligence techniques have been used to detect anomalies, amongst them convolutional neural networks using deep learning techniques improved the detection accuracy significantly. The goal of this article is to propose a new method based on deep learning techniques for Crime detection in video surveillance cameras. The proposed method has been evaluated in the UCSD dataset, and showed an increase in the accuracy of the Crime detection. Downloads: | DOI: 10.17148/IARJSET.2024.111217 How to Cite: [1] Dr Devika B, Akshay M S, Lohit S H , Lohith B, Manoj T V, "Automated Crime Detection and Alert System via Embedded Deep Learning," International Advanced Research Journal in Science, Engineering and Technology (IARJSET), DOI: 10.17148/IARJSET.2024.111217 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: Weeding is a crucial but time-consuming task in agriculture that requires significant manual labor and often relies on chemical herbicides, which can negatively impact the environment and human health. An autonomous weeding robot is proposed as a solution to address these challenges. The robot employs computer vision and machine learning techniques to detect and classify weeds. The objective of this project is to develop an autonomous weeding robot that can effectively and efficiently identify weeds from crops, while reducing the reliance on chemical herbicides, minimizing labor costs, and promoting sustainability in agriculture. The methodology involves designing and building a prototype robot, training and testing its computer vision and machine learning algorithms, and evaluating its performance in real-world field conditions. The outcomes of this project can include improved weed management, reduced reliance on chemical herbicides, labor cost savings, increased efficiency and productivity, enhanced sustainability, and advancements in agricultural technologies. This project proposes the development of an autonomous weeding robot using computer vision and machine learning techniques, specifically the YOLO (You Only Look Once) ML model. The robot aims to effectively detect and classify weeds, reducing the reliance on chemical herbicides and minimizing labor costs in agriculture. The prototype robot is designed, and its algorithms are trained and tested, achieving a model accuracy of 82.6% and a validation accuracy of 77.72%. The project's outcomes include improved weed management, cost savings, increased efficiency, sustainability, and advancements in agricultural technologies.

Keywords: Weed Detection Techniques, YOLO, TensorFlow, Raspberry Pi, Agricultural Robotics, Sustainable Farming, Herbiside Reduction, Image Processing, Precision Farming.

+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 Neuro-Driven Speech Synthesis for Paralysis Dr. Bharathi Gururaj,Gurushankara M,Anagha Prakash,Anirudha R Bhat Abstract -Speech is fundamentalmeans of communication that allows individuals to express thoughts, emotions, and ideas. However, millions of people worldwide are unable to communicate verbally due to conditions such as amyotrophic lateral sclerosis (ALS), brainstem stroke, locked-in syndrome, or severe paralysis. Traditional augmentative and alternative communication (AAC) devices, such as eye-tracking systems or text-based interfaces, are often slow, labour-intensive, and less expressive. In recent years, advancements in neuroscience, machine learning, and brain-computer interface (BCI) technologies have paved the way for neuro-driven speech synthesis, which holds the promise of restoring communication for individuals with severe speech impairments. Downloads: | DOI: 10.17148/IARJSET.2024.111219 How to Cite: [1] Dr. Bharathi Gururaj,Gurushankara M,Anagha Prakash,Anirudha R Bhat, "Neuro-Driven Speech Synthesis for Paralysis," International Advanced Research Journal in Science, Engineering and Technology (IARJSET), DOI: 10.17148/IARJSET.2024.111219 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

+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 Environment Scanning and Navigation of Fields with Real Time Data Transmission Drone for Agriculture Dr. Dinesh Kumar D , Misba M, Monisha D, Pooja R Abstract- This collection of study explores advancements in drone technology across various domains, including military reconnaissance, agriculture, emergency communications, and forensic applications. By integrating AI and machine learning technologies such as YOLO models, reinforcement learning, and advanced neural networks, drones are achieving greater autonomy, precision, and adaptability. The research highlights the use of synthetic and augmented datasets for model training, the development of lightweight architectures for real-time applications, and innovative algorithms for resource-constrained environments. Challenges such as environmental complexity, ethical concerns, computational limitations, and communication reliability are analyzed, alongside solutions like simulation-to-reality transitions, adaptive algorithms, and robust evaluation frameworks. This paper offers a comprehensive examination of the evolving landscape of drone technology, emphasizing its potential for societal impact across diverse applications. Keywords- Drone Technology, Artificial Intelligence, YOLO Object Detection, UAV Applications, Reinforcement Learning, Military Reconnaissance, Precision Agriculture, Emergency Communication Systems, UAV Forensics, Simulation-to-Reality Transition Downloads: | DOI: 10.17148/IARJSET.2024.111220 How to Cite: [1] Dr. Dinesh Kumar D , Misba M, Monisha D, Pooja R, "Environment Scanning and Navigation of Fields with Real Time Data Transmission Drone for Agriculture," International Advanced Research Journal in Science, Engineering and Technology (IARJSET), DOI: 10.17148/IARJSET.2024.111220 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: Sorting and navigation are critical tasks in various industries, such as manufacturing, logistics, and recycling. Traditional methods of manual sorting and navigation are often inefficient, time-consuming, and prone to human error. Our prototype integrates two essential functionalities-color sorting and line-following-into a single robotic system, offering an automated and efficient solution. The color sorting system uses advanced sensors to accurately identify and categorize objects based on their color, while the line-following system ensures precise navigation along predefined paths. This combination delivers high accuracy, reduced manual intervention, and improved operational efficiency, making it a reliable and cost-effective solution for industrial and educational applications.

Keywords: color sorting, line following, automation, efficient, accurate, cost-effective, robotic system.

Abstract: This research presents an autonomous surveillance rover for defense applications designed to enhance real-time enemy detection and situational awareness. The system is powered by a Raspberry Pi, enabling centralized control and processing of data from various sensors. Ultrasonic sensors ensure obstacle detection, while inductive proximity sensors identify landmines and explosive devices. A camera module provides real-time video streaming, which is analyzed using image processing algorithms to classify individuals as authorized or threats. When a threat is identified, the system triggers a laser module to simulate a defensive response. The rover autonomously navigates its environment, continuously scanning for hazards and relaying real-time alerts to defense personnel via a communication module. This integration of IoT, artificial intelligence, and robotics makes the rover a reliable and efficient solution for modern defense challenges. The project highlights its potential to enhance security, reduce human risks, and adapt to evolving operational demands.

Keywords: Autonomous surveillance, enemy detection, real-time monitoring, Raspberry Pi, obstacle detection, image processing, IoT, defense robotics.

Abstract: Wireless EV charging stations use inductive power transfer (IPT) for contactless charging, offering conven-ience, scalability, and reduced maintenance, while addressing challenges like efficiency and safety to support sus-tainable EV adoption

Keywords: wireless electric vehicle charging, Static Wireless Charging, Smart Charging Systems, Green Energy Charging.

Abstract: Wildlife observation is essential for biodiversity conservation and ecological research. However, traditional methods of wildlife monitoring often disrupt natural habitats and pose safety challenges to researchers. A wildlife observation robot offers a non-intrusive, efficient, and automated solution to address these limitations. Equipped with advanced sensors, cameras, and GPS modules, the robot can navigate diverse terrains and monitor animal behavior, environmental conditions, and habitat changes in real-time. Integration with AI-powered image and sound recognition systems allows for accurate species identification and behavioral analysis. This autonomous system reduces human intervention, minimizes habitat disturbance, and enhances data collection accuracy. Additionally, remote operation and data transmission capabilities enable researchers to monitor wildlife from a safe distance, making it an invaluable tool for conservation efforts and ecological studies.The conservation of wildlife and the study of ecosystems are critical for maintaining biodiversity and ensuring ecological balance. Effective monitoring of wildlife is essential for understanding species behavior, habitat dynamics, and the impacts of environmental changes. However, traditional observation methods, such as manual surveys, stationary cameras, and tracking devices, often face limitations including habitat disturbance, high operational costs, limited geographic coverage, and risks to researchers. These challenges highlight the need for innovative, automated solutions, leading to the conceptualization and development of wildlife observation robots.A wildlife observation robot is an autonomous or semi-autonomous system designed to monitor and study wildlife with minimal human intervention. Equipped with advanced sensors, cameras, GPS modules, and artificial intelligence, these robots can collect real-time data on animal behavior, environmental parameters, and habitat conditions. AI-driven capabilities enable accurate species identification, behavioral analysis, and anomaly detection, providing researchers with valuable insights while maintaining the integrity of natural ecosystems.Theoretical foundations for this innovation draw from fields such as robotics, machine learning, and environmental science. Robotics offers a means to traverse diverse and challenging terrains autonomously, while AI enhances the robot's ability to interpret visual and auditory data with high precision. The integration of IoT (Internet of Things) technology enables seamless data transmission and remote monitoring, ensuring continuous observation even in remote or inaccessible locations.By minimizing ecological disturbance and offering scalability, wildlife observation robots contribute to the global conservation agenda. They provide a sustainable, efficient, and ethical alternative to traditional methods, ensuring comprehensive data collection without compromising the well-being of wildlife. This project bridges the gap between technology and conservation science, fostering innovative approaches to preserving biodiversity and supporting ecological research for future generations.

Abstract: The main goal of the project is the development of an RC (Remote Control) water purification boat that offers a new solution for dealing with water pollution in smaller water bodies such as ponds, lakes and rivers. This project focuses on the design and construction of a prototype autonomous RC boat capable of collecting floating dirt and debris. The boat is equipped with sensors, a collection mechanism and a remote control interface for efficient operation in various water conditions. The project emphasizes sustainability by using eco-friendly materials and a solar energy system that reduces the environmental impact of the ship itself. In addition, the boat is designed to be modular and easy to maintain, ensuring long-term usability. The integration of real-time data processing enables optimal navigation and allows the ship to navigate through obstacles and adjust its path for efficient waste collection. This research highlights the potential of combining automation with environmental management, opening avenues for future developments in water pollution control using innovative technologies.

Keywords: Water Cleaning, Remote Control Boat, Environmental Sustainability, Pollution Control, Waste Collection, Autonomous Navigation, Solar Power, Eco-friendly Design, Water Pollution Management, Technology Integration.

Abstract: The project titled " Gesture Controlled Robotic Arm with Mobile Rover Integration" aims to develop an innovative robotic system that combines gesture recognition, mobility, and automation. The system is designed to operate using hand gestures detected through sensors embedded in a glove, enabling precise and intuitive control of the robotic arm. Mounted on a rover, this robotic arm is capable of performing complex operations such as object handling, picking, and dropping with high accuracy. The mobility of the rover further extends the arm's functionality, making it adaptable for various environments and applications. The hardware system includes an Arduino Nano, ESP32, MPU6050 accelerometer, flex sensors, PCA9685 servo driver, MG966R servo motors, DC motors, and a L298N motor driver. Communication between components is established via Bluetooth HC-05, while the system is powered by a dual voltage setup (5V and 12V). The integration of these components ensures precise movement of the robotic arm and seamless mobility of the rover. A mobile application is used for additional control, making the system user-friendly and versatile. The methodology involves input sensing at the transmitting end, where hand gestures are captured and processed using sensors and an Arduino. The processed data is wirelessly transmitted to the receiving end using Bluetooth modules. The ESP32 at the receiving end controls the arm's servo motors and the rover's mobility system, enabling synchronized operation of the arm and rover. This system has a wide range of applications, including military (e.g., surveillance, bomb defusal), healthcare (e.g., surgical assistance), industrial automation (e.g., material handling, fabrication), agriculture ,and power plants By leveraging advanced sensor technology, robotics, and wireless communication, the project addresses challenges in environments where precision, flexibility, and remote operation are critical.

Abstract: In recent years robots have become a vital part of technology. Surveillance robots play a important role in enhancing security and monitoring capabilities in various domains, ranging from public safety and military applications to industrial facilities and private premises. These robots are equipped with advanced sensors, cameras, and communication systems to gather real-time data and provide situational awareness in both indoor and outdoor environments. This abstract highlights the key features and benefits of surveillance robots, focusing on their capabilities, deployment scenarios, and potential challenges. Surveillance robots are designed to navigate through complex environments autonomously or remotely, collecting visual and auditory information while transmitting it to a control center or human operators. They leverage technologies such as computer vision, machine learning, and sensor fusion to detect and track objects, recognize faces, identify anomalies, and monitor critical areas. The use of surveillance robots offers numerous advantages. They can provide persistent surveillance without fatigue or distractions, cover large areas efficiently, object avoiding and respond rapidly to security incidents or emergencies. Their ability to operate in challenging conditions, such as low-light environments or areas with restricted access, enhances overall security and threat detection capabilities. Additionally, surveillance robots can be equipped with additional functionalities, such as two-way communication, integration with existing security systems, and the ability to carry out routine patrols or inspections. However, the deployment of surveillance robots also presents challenges. Ensuring reliable navigation and obstacle avoidance, maintaining continuous power supply, optimizing data transmission and storage, and addressing privacy concerns are among the key considerations. Ethical and legal frameworks must be established to define the boundaries of surveillance activities and protect individual privacy rights.

Keywords: Arduino UNO, ESP 32 CAM Wi-Fi Module, Sensor, Surveillance.

Abstract: This paper presents the design and implementation of an automatic fan regulation and smart curtain system aimed at enhancing energy efficiency and user comfort. The system integrates temperature and light intensity sensors with microcontroller-based automation to dynamically adjust fan speed and curtain positioning. The fan speed is regulated based on ambient temperature, ensuring optimal cooling while conserving energy. Simultaneously, the smart curtain responds to light intensity, adjusting its position to maintain appropriate indoor lighting conditions . The proposed system offers an affordable and sustainable solution for smart home applications, combining ease of use with significant energy savings. Experimental results demonstrate its effectiveness in achieving the desired automation objectives.

Keywords: Automatic, Sensor ,Smart Fan, Smart Curtain.

Abstract: The footstep electricity generator is a novel approach to harnessing renewable energy from human motion. This system utilizes piezoelectric transducers embedded in flooring materials to convert the mechanical energy gener-ated by footsteps into electrical energy. The generated electricity can be stored and used to power various devices, such as street lights, sensors, and even charge mobile phones. The primary components of this system include piezoe-lectric sensors, a power management unit, and an energy storage system. When a person steps on the floor, the pressure exerted is converted into electrical energy by the piezoelectric sensors. This energy is then regulated, stored, and made available for use. This technology offers a sustainable solution to energy generation, particularly in high-traffic areas such as sidewalks, train stations, and shopping malls. By capturing the otherwise wasted kinetic energy from footsteps, it contributes to reducing the dependency on traditional power sources and promotes the use of clean energy.

Keywords: Battery, Foot-step power generation, Piezoelectric sensors.

Abstract: Ghat roads have some serious issues such as landslide, sharp curves, and heavy traffic, which hamper safety and efficiency. The project here proposed an integrated system consisting of landslide detection, automatic gate con-trol, and traffic management for long curves. Landslide detection will monitor soil stability with the use of sensors and algorithms that give early warnings. Automatic gate control will regulate the entry and exit of vehicles to reduce con-gestion and unauthorized access. Traffic management: sensors and cameras collect data in real time to manage traffic flow and improve curve safety. The system uses IoT and real-time processing to enable seamless functionality.

Abstract: The proposed Smart Pepper Spray is an advanced self-defense device designed to enhance personal safety through the integration of cutting-edge technology. Unlike traditional pepper sprays, this device incorporates GPS tracking and a high-resolution camera to provide real-time location monitoring and visual evidence during emergencies. The device is equipped with sensors that activate the GPS and camera systems upon usage. The GPS feature sends the user's live location to pre-designated contacts or emergency services, ensuring immediate assistance. Simultaneously, the integrated camera captures and stores footage of the incident, which can serve as vital evidence for law enforcement. A compact and user-friendly design ensures portability and ease of use, while the system is powered by a rechargeable battery for long-term reliability.

Abstract: Management of dams today involves use of dam monitoring ecosystems that incorporate various technolo-gies such as automation of pumps, detection of cracks, as well as pollution control of water bodies The proposed ar-chitecture works as a system on top of comprehensive interfacing with the sensors and also in real time protecting the walls of a dam. Raspberry pi, ultrasonic sensor, turbidity sensor, flex strips, rain sensors are interfaced with microcon-troller to send the water level and open the walls of the gate and turn on the pump automatically and the buzzer goes before opening the walls. Flex Strips are used to detect the crack in the dam hence notify that through GSM module and send an SMS . Hence with the above working makes dam work automatically in real time application.

Abstract: This study presents the design and development of facial recognition and obstacle detection smart glasses for visually challenged people using Raspberry Pi. The proposed system utilizes a Raspberry Pi 4 Model B, a Pi 3 camera, an ultrasonic sensor and a speaker to recognize and identify pre-registered individuals along with obstacle distance measurement. The facial recognition algorithm is based on the OpenCV library. The system provides real-time audio feedback to the user, announcing the name of the recognized individual and also provides audio warning if the obstacle is less than 18 cm. Our results show that the system achieves an accuracy of 92.5% in recognizing the pre-registered individuals. User feedback and usability testing revealed significant improvements in social interactions and confidence levels among visually challenged individuals. This study demonstrates the potential of low-cost, Raspberry Pi-based facial recognition and obstacle detection systems to empower visually challenged people.

Keywords: Raspberry Pi 4, Pi 3 Camera, Real Time Face Detection, Audio feedback system, Object detection for accessibility

Abstract: The problem of gas leakage and fire is often encountered in our day-to-day life. LPG, Liquified Petroleum Gas, is highly flammable gas used as fuel in heating appliances. Leakage of this gas raises the risk of building fire, suffocation or an explosion. Most of the fire-breakouts in industries are due to gas leaks. These cause dreadful damage to the equipment, human life leading to injuries, deaths, and environment. The mentioned problem can be solved with the development of reliable techniques to detect gas leakage. We proposed a system to detect gas leakage automatically with the help of gas sensor and Arduino microcontroller and alerts the person if there is gas leakage by buzzer alarm and auto cutoff regulator..

Keywords: Gas sensor,MQ-6,Ardunio.

Abstract: Drunk driving is a significant contributor to road accidents globally, posing a serious safety concern. This project introduces a smart helmet system designed using Arduino technology to address this issue and improve rider safety. The system incorporates an alcohol detection module into the helmet, which continuously checks the rider's breath for signs of alcohol. If the alcohol level exceeds a set threshold, the system triggers a mechanism to cut off the fuel supply to the vehicle, preventing the engine from starting or operating. The helmet features a microcontroller (Arduino), an alcohol sensor (such as the MQ-3), and an optional wireless communication module. To ensure precise monitoring, the alcohol sensor is positioned close to the rider's mouth. The design emphasizes ease of use, reliability, and practicality for seamless real-world application.This smart helmet offers a practical and automated solution to mitigate accidents caused by drunk driving. By integrating advanced technology, it enhances road safety, supports adherence to traffic laws, and encourages responsible driving habits among motorcyclists.

Keywords: Smart Helmet , Alcohol Detection, Arduino Technology, Road Safety

Abstract: In current days, grass cutter machines are operated by fuel and electrical energy which are costly and requires high maintenance. Hence, in this study, a hand-held operated machine for grass cutting was designed and fabricated by using locally available materials. Important aspects such as durability, strength, and light weight were taken into design considerations for better performance characteristics. The lawn mower was powered by a12V/1.35A rechargeable battery which drives the DC motor up to a rotational speed of 19,300 RPM. As a result, the generated torque will be transferred to the cutting head mechanism for efficient grass cutting. The entire configuration set up was mounted on a wooden base which attached together with a bicycle frame and a set of wheel arrangement. This portable lawn mower can be used to maintain and trim grass in gardens, home, schools or yards.

Keywords: Grass cutter, bicycle frame, lawn mower, hand-held, battery ,portable

Abstract: Suicide prevention is a significant societal challenge, and hanging from ceiling fans has been a common method in such tragic events. This project presents an innovative approach to mitigating this issue by designing a ceiling fan equipped with a spring-loaded rod that extends when it detects the weight of a person attempting to hang. The extension of the rod prevents suffocation by reducing pressure on the person's neck, while an integrated alarm system immediately alerts family members or nearby individuals, enabling swift intervention. This system is designed to be non-intrusive and easy to install in households, offering a low cost, life-saving solution that enhances safety and protection. By combining mechanical design with automated alert technology, this project exemplifies a practical and effective method to reduce suicides and provide timely help in crisis situations.

Abstract: The Laser Security System is a revolutionary intrusion detection solution that utilizes laser technology to provide unparalleled security and protection. This system is designed to detect and alert homeowners or authorities of potential security breaches, providing a robust defense against intruders. The system operates by projecting a laser beam across a designated area, creating an invisible barrier that detects any disruptions or objections. When an intruder crosses the laser beam, the system triggers an alarm, alerting the home owner or authorities of the potential threat. The laser security system boasts several key features, including high sensitivity detection capabilities, customizable alarm setting, integration with existing security systems. The benefits of the laser security system are multifaceted. It provides homeowners with a reliable and effective means of protecting their property, reducing the risk of theft, vandalism, and other security breaches. Additionally, the system's advanced technology and customizable features make it an attractive solution for commercial and industrial applications.

Keywords: LDR module, Aurdino NANO Board, Buzzer.

Abstract: Sleep-induced accidents, particularly in transportation and industrial environments, pose a significant risk to public safety and productivity. The Anti-Sleep Alarm System is an innovative solution designed to combat driver and worker fatigue by detecting early signs of drowsiness and providing real-time alerts. This system integrates physiological monitoring, such as eyelid movement and head posture detection, with machine learning algorithms to accurately predict the onset of sleep. Additionally, it employs auditory, visual, and haptic feedback mechanisms to ensure user alertness without being intrusive. The solution is lightweight, cost-effective, and adaptable to diverse environments, making it a practical tool for enhancing safety and reducing fatigue-related accidents. This paper explores the design, implementation, and efficacy of the Anti-Sleep Alarm System, emphasizing its potential to save lives and improve operational efficiency.

Abstract: Mathematics anxiety is a pervasive issue that undermines students' academic performance, self-confidence, and engagement with mathematics. Recognizing its adverse effects, six partner countries collaborated under an Erasmus Plus project to investigate the root causes of mathematics anxiety and design an innovative intervention. Using a mixed-methods approach, surveys and interviews were conducted in five partner countries to identify key factors contributing to mathematics anxiety in primary school students. Based on these findings, a modular teaching program integrating robotics applications was developed to alleviate anxiety and promote positive engagement with mathematics. This article provides an in-depth overview of the study's methodology, findings, and the modular teaching program, emphasizing its potential for transformative change in mathematics education.

Keywords: Math anxiety, robotics in education, innovation in education.

Abstract: This project aims to develop a hardware accelerator for real-time sign language detection using Atlera DE10- Lite FPGA board. Sign language recognition is essential for bridging communication gaps between sign language users and the broader population. By leveraging the parallel processing capabilities and energy efficiency of FPGAs, the system ensures low latency and high accuracy in gesture recognition. The approach involves designing an optimized Convolutional Neural Network (CNN) architecture tailored for FPGA implementation and incorporating preprocessing techniques to enhance robustness against environmental variability.

Keywords: Hardware Accelerator, Convolutional Neural Network, Sign language detection, Altera DE10-Lite FPGA.

Abstract: In this paper,we propose automation for car wiper control.Apart from some high-end luxury vehicles all other uses manual schemes for wiper control during rainfall,which can be deadly for drivers and passengers as well as it requires proper attention to increase and decrease the wiping frequency according to rain intensity. This increases the risk of accidents; therefore, automatic rain sensing wiper system becomes a more appealing feature.The objective of this paper is to provide a cost-effective system for automatic rain sensing wiper control.This system employs a rain sensing module which senses the rain and sends an analog signal to Arduino uno which analyzes the signal and energizes the servo motor which performs the wiping operation. By implementing this automation in automobiles,we can increase the driver and passenger safety by a great margin.

Keywords: Rain sensor,Arduino UNO,servo motor.

Abstract: The growing need for sustainable and cost-effective energy solutions has led to innovative approaches to utilizing waste as a resource. This paper explores an integrated system combining automatic waste segregation, incineration, and thermoelectric energy conversion for electricity generation. Using sensors, an Arduino microcontroller, and servo motors, waste is automatically segregated into dry and wet categories, ensuring efficient handling. It also surveys the process of electricity generation from dry waste through an incineration-based system. The study focuses on the design and implementation of a system that employs the TEC 12706 Peltier module to convert heat energy generated during waste combustion into usable electrical energy. The proposed method addresses key challenges in waste management by harnessing the thermal energy from incinerated dry waste while minimizing environmental impacts. The process involves the systematic collection, purification, and combustion of dry waste, optimized to achieve maximum heat-to-electricity conversion efficiency. Through a review of existing technologies and methodologies, this paper highlights the potential of the TEC 12706 Peltier module in small-scale, decentralized energy generation. The results and findings are expected to contribute to the development of cost-effective, eco-friendly energy solutions that promote sustainable waste-to-energy conversion practices.

Keywords: Automatic Segregation, Incineration, TEC 12706 Peltier module, Waste to Energy.

Abstract: Access to healthcare in rural areas has long been hindered by limited resources and facilities, leaving many residents underserved. Telemedicine offers a promising solution, and this project introduces AI-powered Telemedicine Kiosks to bridge the gap between rural communities and healthcare providers. These kiosks enable timely medical consultations, diagnostics, and medicine dispensing, addressing accessibility and convenience challenges. By leveraging advanced technology, the project aims to enhance healthcare access, reduce costs, and improve patient satisfaction, ultimately empowering underserved populations and promoting equitable healthcare for all.

Keywords: Rural healthcare, Telemedicine, AI-powered kiosks, Healthcare accessibility, Medication dispensing, Remote medical consultation, Patient satisfaction, Health outcomes, Atmega328 Microcontroller, Python 2.7, Automated healthcare solutions.

+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 PRE-BOOKING SMART PARKING SYSTEM Christo jain, Archana M, Hitha S M, Lekhana B H

Abstract: The Pre-Booking Smart Parking System is designed to simplify parking by allowing users to book parking spots in advance, reducing the difficulty of finding available spaces. The system utilizes RFID for secure access, IR sensors to detect parking slot occupancy, automatic gates controlled by motors, and Arduino for system management. Accessible through a website, this solution reduces traffic congestion, minimizes fuel consumption, and contributes to a greener environment by improving parking efficiency and cutting down on carbon emissions.
Index Terms: parking slots, RFID card, booking, payment Downloads: | DOI: 10.17148/IARJSET.2024.111245 How to Cite: [1] Christo jain, Archana M, Hitha S M, Lekhana B H, "PRE-BOOKING SMART PARKING SYSTEM," International Advanced Research Journal in Science, Engineering and Technology (IARJSET), DOI: 10.17148/IARJSET.2024.111245 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: A surveillance camera is an essential security device used for monitoring and recording activities in a specific area. It is commonly used in various settings such as homes, businesses, public spaces, and industrial sites to deter crime, monitor behavior and ensure safety. Surveillance cameras are typically connected to a system for remote viewing and recording, allowing users to observe live footage or review past events. AI-powered surveillance cameras represent a significant advancement in security technology, integrating artificial intelligence and machine learning algorithms to provide more intelligent, automated, and accurate surveillance. Unlike traditional surveillance cameras that simply capture and record footage, AI-powered cameras have the ability to analyze data in real-time, recognize patterns, and make decisions based on predefined criteria. This leads to enhanced security, greater efficiency, and faster response times. AI-powered cameras can automatically identify and track objects or people within their field of view. Using machine learning and computer vision algorithms, these cameras can differentiate between humans, vehicles, animals, and other objects. They can also detect specific behaviors or events such as Intrusion detection, Loitering detection etc.

Keywords: Surveillance camera, Fire detection, scream detection, Arduino, Emergency services, smart security, IOT based , smart surveillance system.

Abstract: The Automated Barcode-Based Warehouse Sorting System is designed to enhance efficiency and accuracy in warehouse operations. By utilizing barcode scanning technology integrated with automated conveyors and sorting mechanisms, the system classifies and directs items to their appropriate locations. This reduces manual labor, minimizes sorting errors, and improves processing speed. The system includes barcode scanners, a centralized database for inventory tracking, and programmable controls for automation. Testing in a mid-sized warehouse demonstrated significant improvements in accuracy and operational efficiency, highlighting its potential for streamlining logistics processes.

Keywords: Warehouse Automation, Barcode Scanning, Inventory Management, Automated Sorting System, Logistics Optimization, Supply Chain Efficiency, Programmable Logic Controllers (PLCs), Real-Time Tracking.

Abstract: The development of a fire-fighting robot aims to enhance the efficiency and safety of fire response operations. This robot is designed to autonomously detect, locate, and extinguish fires in hazardous or hard-to-reach areas, reducing the risk to human firefighters. Equipped with sensors for fire detection, temperature monitoring, and real-time environmental analysis, the robot can navigate through smoke-filled or unstable environments. It is typically outfitted with an onboard fire suppression system, such as water hoses or fire retardants, to combat flames directly. The robot's design incorporates robust mobility features, such as wheels or tracks, enabling it to maneuver across various terrains..

Keywords: flame sensor,L298N motor drive.

Abstract: The "Voice Controlled Mobility Chair" is an innovative wheelchair designed for disabled individuals, utilizing Arduino technology to enable hands-free navigation. By integrating voice recognition, users can control the wheelchair's movement, enhancing independence and mobility. The system ensures ease of use, accessibility, and improved quality of life for users.

Abstract: This paper presents a GPS-based location monitoring system with geo-fencing capabilities designed to prevent vehicle theft and provide real-time tracking. The system integrates hardware components, including an ESP32 NodeMCU, a GPS module, speed sensor, tilt sensor and a Wifi receiver, with software components, namely an IoT cloud platform and integration. The GPS module tracks the vehicle's location and transmits the coordinates to the IoT platform through the NodeMCU. The system administrator can monitor the speed of the vehicle, and monitors the damage of the vehicle, any drastick changes in the weight of the load, and monitors vehicle's location and set up geo-fencing boundaries. When the vehicle enters or exits the geo-fenced area, the system triggers an email notification alert to the administrator. The prototype was tested by moving a vehicle around a geo-fenced area, and the prototype system was tested by moving the vehicle around the geo-fenced area. Results showed correct location tracking of the vehicle and phone number notifications upon exiting or entering boundaries.

Keywords: GPS tracking, vehicle security, geo-fencing, IoT platform, real-time monitoring, ESP8266 NodeMCU, Wifi

Abstract: The Solar Panel Tracking System project is designed to optimize the collection of solar energy by dynamically adjusting the orientation of a solar panel to follow the sun's movement throughout the day. This system employs a Light Dependent Resistor (LDR) sensor to detect variations in light intensity, ensuring that the solar panel consistently faces the direction of maximum sunlight. A servo motor is used to adjust the panel's angle based on the input from the LDR sensor, thereby maximizing the energy harnessed. This report provides a comprehensive overview of the project's design and implementation. It covers the selection and integration of key components, including the solar panel, LDR sensor, servo motor, and microcontroller (e.g., Arduino)

Abstract: This paper presents the development and implementation of a smart door mat utilizing face recognition technology. The primary goal of this project is to enhance improving accessibility for users, offering a hands-free entry solution, and strengthening home security by logging visitor data. The project emphasizes usability, reliability, and scalability, making it suitable for residential and commercial applications. The system integrates a face recognition algorithm implemented in Python using the OpenCV library, with adjustments controlled by an Arduino through serial communication.

Keywords: Piezoelectric Sensor, Smart Doormat, Visitor Detection, Home Automation, IoT Integration, Energy Efficiency

Abstract: Fuel adulteration and inaccurate fuel measurement are prevalent problems that affect vehicle performance, engine efficiency, and environmental health. These issues lead to significant financial losses for consumers and contribute to air pollution due to the use of contaminated fuel. This project presents a Fuel Analyzer System designed to monitor and assess fuel quality and quantity in real time. The system integrates multiple sensors, including density sensors, flow sensors, pressure sensors, and conductivity sensors, to detect fuel adulterants such as water and other contaminants, while accurately measuring fuel levels and flow. The data collected by these sensors is processed and analyzed to provide users with immediate feedback on the quality and volume of the fuel in the vehicle's tank. By leveraging advanced sensor technology, the system ensures precise fuel monitoring, enabling users to identify adulteration and discrepancies in fuel quantity. Unlike standard fuel monitoring systems, this system requires integration into the vehicle's fuel system, offering a comprehensive solution for accurate fuel analysis. The proposed system aims to enhance consumer protection, promote fair fuel distribution practices, and reduce environmental impact by encouraging the use of high-quality, unadulterated fuel. Through real-time monitoring and accurate detection, the Fuel Analyzer System contributes to greater transparency, efficiency, and sustainability in the automotive industry.

Abstract: In this literature paper we aim to review about all the attempts made to bring smart helmet in the market; their success and various attempts. The paper also speaks about the various technologies involved till date in bringing smart helmets to the market. Many helmets aim to give speeding alert, and helps the user not to violate the traffic rules and also to reduce the accident rates in the society.

Keywords: Raspberry Pi, Heart-beat sensor, microcontroller.

Abstract: The increasing demand for sustainable and environment friendly energy solutions has placed solar energy at the forefront of green power generation. This project explores the potential of solar energy as a reliable, clean, and renewable source of power to meet the growing energy needs while minimizing environmental impact. By utilizing photovoltaic (PV) technology, sunlight is directly converted into electricity, offering a scalable and efficient solution for diverse applications ranging from residential to industrial energy consumption.

Abstract: This project presents the design and implementation of a voice-controlled air purifier. The system utilizes HEPA filtration and UV technology to effectively remove pollutants and allergens from the air, ensuring a healthier indoor environment. The air purifier is equipped with voice-activated controls for power, fan speed, and real-time air quality notifications, providing a user-friendly and contactless operation. Additionally, the device features a voice-activated music player. The project aims to address common issues with existing air purifiers, such as inadequate pollutant removal, noise disturbances, and user control challenges. The proposed solution offers an innovative approach to improving air, making it a valuable addition to modern smart home environments.

Keywords: Voice Control, Air Purifier, HEPA Filtration, UV Technology, Indoor Air Quality (IAQ), Real-Time Monitoring, Machine Learning, IoT (Internet of Things), Sustainable Energy, Smart Home.

Abstract: This paper puts forward the solution to landmine detection. Detection of landmines is a serious problem in the mine prone areas. The system shown in this paper uses a robotic car equipped with different types of components like a metal detector, camera module, ultrasonic sensors, etc. for self-detection of landmines. This data or indications can be sent over a large distance using a GPS to the remote monitoring system. This monitoring system will therein be used for the exact detection of landmines

Keywords: Landmine detection, Raspberry-Pi, Metal detector, Robotic car, GPS Module.

Abstract: Most of the military organization now takes the help of robots to carry out many risky jobs that cannot be done by the soldier. These robots used in military are usually employed with the integrated system, including video screens, sensors, gripper and cameras. The military robots also have different shapes according to the purposes of each robot. Here the new system is proposed with the help of low power IOT wireless sensor network to trace out the intruders (unknown persons) and the robot will take the necessary action automatically. Thus, the proposed system, an Intelligent Unmanned Robot (IUR) using IOT saves human live and reduces manual error in defense side. This is specially designed robotic system to save human life and protect the country from enemies.

Keywords: Military robot, IOT, Wireless network, MQTT, sensors, camera, detection.

Abstract: This research investigates the design and implementation of a solar-powered automatic soil irrigation system. The system aims to optimize water usage and enhance agricultural productivity by automating the irrigation process and utilizing renewable energy. The system incorporates a microcontroller-based control unit, solar panels for power generation, a water pump, and a network of sensors to monitor soil moisture levels and environmental conditions. The system autonomously adjusts irrigation schedules based on real-time data, minimizing water wastage and ensuring optimal plant growth. The results demonstrate the effectiveness of the solar-powered system in achieving efficient and sustainable irrigation, contributing to increased crop yields and reduced environmental impact.

Keywords: solar energy, automatic irrigation, soil moisture sensor, microcontroller, water conservation, sustainable agriculture, renewable energy, IOT

Abstract: Black pepper (Piper nigrum) is a significant spice crop cultivated in Yercaud of Salem district across an area of 1680 hectares, with a productivity rate of 0.2 tonnes per hectare. Harvesting is a tedious process especially in peak seasons. Krishi Vigyan Kendra, Salem introduced unipole aluminum ladder for pepper harvesting under tribal sub plan programme in the year 2020-21. Arangam, Senthittu and Pelakkadu within the Maramangalam Panchayath of the Shervaroy Hills are the villages in Yercaud block of Salem district in which about more than 650 families are residing and all of them are small and marginal farmers cultivating pepper in an area of around 480 hectares. The process of plucking pepper presents a significant risk, with the potential for falls from bamboo ladders, leading to severe physical and health issues. To address these challenges, the Krishi Vigyan Kendra (KVK), Salem, introduced and supplied a unipole aluminum ladder under the Tribal Sub Plan. This affordable and efficient harvesting equipment is designed to be operated by any individual, aiming to enhance the effectiveness of the harvesting process. the Aluminum unipole ladder stands poised to effectively replace traditional bamboo pole harvesting methods in the Shervaroy Hills. Its multifaceted benefits, including safety, affordability, ease of use, and widespread acceptance among farmers, position it as a valuable asset in enhancing agricultural practices and productivity in the region. Hence the farmers are using the ladder without any fear of falling and efficiency of harvesting is increasing and the cost of cultivation is also reduced.

Keywords: Black Pepper, Harvesting, Unipole Aluminium Ladder, Impact Assessment

Abstract: Macro propagation is an excellent option for producing quality planting material at a lesser cost. This is a simple method because of the ease of multiplication, saves cost of producing planting material and has the potential of producing 50-60 shoots per sucker in a duration of 4-5 months. It can rapidly multiply plantlets to distribute a new variety or replace plants in disease-affected fields. It can be done locally at low cost and with little training: a private person or a farmers' organization can launch this activity very easily. An experiment was conducted during February- March 2022 and completed during May-June 2022 at Krishi Vigyan Kendra, Salem District of Tamil Nadu in India. Red banana suckers of three to four months old received from the farmers fields were taken for macro propagation techniques in different combination of growing media including soil, sand, vermi compost etc. Different treatments (T1 - Soil alone, T2 - Sand alone, T3 - Vermi compost alone, T4- Soil and sand at 1:1 ratio, T5- Soil and sand at 2:1 ratio, T6 - Soil, Sand and vermi compost at 1:1:1 ratio and T7 - Soil, Sand and vermi compost at 2:1:1 ratio) were replicated thrice in a randomized block design to find out the best suitable media for red banana plantlets production through macro propagation in Salem District. Results revealed that sand was more outstanding growing media over soil and vermicompost. This might be due to the use of reserved nutrition available in the corms and the pore spaces available in sand media is good environment for more number of good quality plantlets production.

Keywords: Suitable Growing media, Red banana, Macro propagation, Salem District

Abstract: An oil skimmer is a device designed to remove oil or other hydrocarbon substances from the surface of water, commonly used in industrial processes, environmental remediation, and oil spill cleanups. Its primary function is to separate and recover oil from water to mitigate environmental damage, enhance water quality, and reclaim valuable oil for reuse. Oil skimmers are widely used in industries like manufacturing, refineries, shipyards, and wastewater treatment plants. They are instrumental in maintaining regulatory compliance and ensuring the sustainable operation of facilities.

Keywords: Oil Skimmer, Oil Recovery, Hydrophobic, IoT, Sensors, Wastewater

Abstract: In academic institutions, the unauthorized use of chit papers during exams is a common issue, compromis-ing the integrity of the examination process. To address this, the development of an efficient chit paper detection ma-chine is crucial for ensuring fairness and transparency. This paper presents a machine learning-based system designed to detect chit papers used during college examinations. This paper proposes an innovative system for exam hall allotment using Global System for Mobile Communications (GSM) technology, aimed at automating the entire process for enhanced efficiency. The proposed system uses a GSM module to send exam hall and seat number information directly to students' mobile phones, ensuring timely and accu-rate communication. Students receive their personalized allotment details via SMS, including the designated exam hall, seat number, and any special instructions.

Abstract: Signlanguage provides an essential means of expression for people with hearing and speaking disabilities. This paper focuses on the development of a reliable method for sign language gesture detection and identification using sophisticated machine learning techniques and computer vision. It uses a combination of techniques such as hand tracking, gesture recognition, and deep neural networks to identify signs coming from video input. Inherent features include real-time processing, adaptability to varied sign languages, and the interpretative ability of complex gestures such as static and dynamic movements. Creating comprehensive datasets of annotated sign language gestures was crucial for both training and evaluation. The results of experiments have shown very high accuracy and efficiency of signs recognition in different environments and various user profiles, which make it promising for real-world application. Thus, the system can contribute to bridging the gap in communication and accessibility both in public and private realms by making technology an instrument for inclusion.

Abstract: Obstacle detection for the blind using ultrasonic sensor is an innovative approach designed to enhance the mobility and safety of visually impaired individuals. This system utilizes ultrasonic sensors to detect objects in the user's path by emitting high-frequency sound waves, which bounce off nearby obstacles and are reflected back to the sensor. The sensor processes the reflected signals to determine the distance to obstacles and provides real-time feedback to the user through auditory signals. This enables individuals to navigate their environment more effectively, avoiding potential collisions and hazards. The primary objective of this project is to assist blind individuals in navigating their surroundings safely and independently, avoiding potential hazards.

Abstract: - The present investigation explores the cultivation practices,production & health benefits of Trapa natans (commonly known as water chestnut) by farmers in Anjora village. Trapa natans L. is an annual aquatic floating plant typically found in tropical freshwater wetlands such as rivers, ponds, lakes, and streams. It is highly nutritious, containing carbohydrates and minerals like calcium, phosphate, iron, copper, and manganese, in addition to being a rich source of vitamins.The economy of the tribal population in this region largely depends on farming, and many farmers in the Gondia district cultivate Trapa natans in ponds and lakes, as the district is well-known for its abundant water bodies.In this study, four ponds were selected, and comprehensive data were collected from farmers regarding cultivation practices, covering processes from seed germination to harvesting. Parameters such as the area of each pond, actual sampling numbers, production per hectare, and market values of Trapa natans were analyzed.The findings revealed that the approximate production of Trapa natans per hectare was 2 quintals, with a market value of around ₹2,000 per quintal. Furthermore, this study summarized the medicinal and health benefits of Trapa natans based on a review of various published literature, emphasizing its significance as a nutritious and economically valuable crop.

Keywords: Trapa natus, Economic Important, Cultivation practices, farmer.

Abstract: Construction use digital technologies at a high pace in an attempt to improve efficiency, safety, and productivity. Among these is AI together with Unmanned Aerial Vehicles (UAVs or drones) as the emergent solution that transforms the method of remote construction site monitoring. This paper explores and provides several applications of AI-powered drones applied to construction, focusing on effective surveillance, monitoring of progress, and monitoring of safety with its technical methodologies, possible issues such as regulatory aspects, data privacy, along with case studies for actions. The findings thus show that combining AI with UAVs can significantly reduce costs, improve site safety, and accelerate the timelines of projects, giving a competitive edge to stakeholders in the construction industry.

Keywords: Artificial Intelligence (AI), Drones, Unmanned Aerial Vehicles (UAVs), Remote Monitoring Construction Management, Progress Tracking, Safety Monitoring, Computer Vision, Machine Learning, Building Information Modelling (BIM)

Abstract: This paper proposes an AI driven educational platform which personalises learning experiences in a dynamic way to cater to different learning styles. The platform then harnesses the power of advanced machine learning algorithms to offer user interactions, preferences and performance insight to personalize educational content such as interactive lessons, gamified assessments and real time feedback. Multimodal resources are integrated - videos, quizzes, hands on projects - which increased engagement and helped learn. Comprehensive analytics also allow educators to improve their teaching and drill down on support. Future improvements will include augmented and virtual reality supplementary to our optimization, and multi lingual support in the isolets as well. This platform shows promise as a revolutionary educational model, one that is inclusive, scalable and educated to different learners.

Keywords: Traffic Signal Optimization, Traffic Density Estimation, Vehicle Counting, Canny Edge Detection, YOLOv8, Real-Time Traffic Management, Intelligent Transportation Systems.

Abstract: This research focuses on the increased usage and importance of social media in human trafficking: how traffickers use the platforms for recruitment, advertisement, and evading detection by law enforcement. The approach will be using data mining and social network analysis to define patterns and networks and to understand vulnerabilities associated with trafficking activities. The research will employ a mixed-method approach that combines quantitative analysis of the content of social media with qualitative insights from interviews with law enforcement, NGOs, and survivors. Major sources of data are expected to include user-generated content, advertisements, and public posts on major social media. The study will correlate how online behaviors relate to incidents of trafficking, identify which particular platforms and communication channels are preferred by traffickers, and thus allow the identification of critical indicators of activity in social media interactions. Findings from this study contribute to the development of prevention strategies, like enhancement of monitoring systems, targeted community awareness campaigns, and collaborations between social media companies and advocacy groups. Knowing the digital footprint of trafficking allows research to highlight the potential for social media to use it as an intervention and awareness tool. Ultimately, it will produce strategic frameworks to encourage stakeholders to collaborate and strengthen communities to identify and react to situations of trafficking in the complexities of human trafficking in the digital age.

Abstract: Preferences and availability are connected with tribal food culture and choices. The purpose of this study is to investigate the food consumption habits of the Toda tribes in Nilgiris, Tamil Nadu. Around 352 adult Toda tribe members were chosen, and their food intake patterns were examined using a semi-structured food frequency questionnaire. Rice became a staple cereal for all Todas, wheat was consumed two to three times a week. Pulses like moong dal and toor dal were consumed several times a week and were a vital part of the Toda diet. Green leafy vegetables such as Malabar spinach, creeping wood sorrel, amaranthus, palak, and cabbage were commonly consumed by all the Toda people twice a week. Vegetables like cauliflower, ladies finger, cluster beans, cucumber, various gourds, brinjal, and drumstick were consumed by the selected Todas twice or thrice a week, depending on availability. Nearly 45% of the selected Todas consumed tapioca, yam, and sweet potato twice a week, depending on availability. Ginger was used by the majority (89%) of the selected Todas. Plums, mulberries, pears, and wild mangoes were regularly consumed by the Toda people. Milk was a central component of the Toda diet, with all 352 selected Toda tribes consuming it daily. Palm oil was fundamental and widely used oil in the Toda tribe's daily cooking. Eggs, fish, crab, poultry, and mutton were preferred by only 11% of the Toda tribe, with these individuals likely consuming them on an occasional basis. The remaining 89% did not consume these items, as they were not staple foods for the Toda people. Around 6% of the Toda tribe consumed biscuits daily and 5% consumed fast foods such as puffs, pizza, burgers, and chat items once a month. Nearly 1% reported the preference for purchasing instant food products such as idli-dosa batter, masala powders, vermicelli, and pickles. It was found that only one percent preferred outside food once or twice a week, when they left their munds due to their occupation. An ongoing nutritional transition is indicated by this move from nutrient-rich traditional diets to energy-dense market foods, a trend seen not only among other indigenous populations in India but also around the world.

Keywords: food frequency, food culture, food consumption, toda tribes, nutrition transition

Abstract: Intelligent Traffic Rules Violation Detector uses artificial intelligence and deep learning techniques to detect vehicle violating traffic rules. The increasing number of vehicles on the road has led to a rise in traffic congestion and accidents. To address this issue, we propose an Intelligent Traffic Rules Violation Detector (ITRVD) system that uses computer vision and machine learning techniques to detect traffic rule violations in real-time. The system consists of cameras installed at traffic intersections, which capture images of vehicles and pedestrians. These images are then processed using object detection algorithms to identify vehicles, pedestrians, and traffic signals. Machine learning algorithms are used to analyse the behaviour of vehicles and pedestrians and detect traffic rule violations such as running red lights, speeding, and pedestrian non- compliance. The system alerts authorities in real-time, enabling swift action to be taken against violators. Experimental results show that the ITRVD system achieves high accuracy in detecting traffic rule violations, making it a valuable tool for improving road safety and reducing traffic congestion.

Keywords: Intelligent Transportation Systems, Traffic Rule Violation Detection, Computer Vision, Machine Learning, Road Safety.

Abstract: Inclusive growth empowers people belonging to vulnerable sections depend on financial inclusion, which is promoting inclusive growth and helps in reducing poverty by providing regular and reliable sources of finance. In this direction, the drive for financial inclusion has taken several measures to increase the access to and availing of formal financial services by un-banked households. The purpose of this study is to assess the nature and extent of financial inclusion and its effect on the socio-economic status of households focusing on inclusive growth. It has been analyzed with the theoretical background on financial access and economic growth and by evaluating the existing literature on financial inclusion in the country and outside. The results show that there is a disparity in nature and extent of financial inclusion. Facilitating access to and availing of formal financial services pave the way to positive changes in the socio-economic status of households which are correlated, leading to inclusive growth based on which the study proposes to make the financial system more inclusive and pro-poor.

Keywords: Financial Inclusion, Financial services, Banking, Inclusive Growth.