Personalised Asthma Prediction by Early Detection

Abstract: This study proposes a prototype for an asthma monitoring system that consists of a band and a smart inhaler that may be utilised by asthma sufferers via the Internet of Things. The band is a little gadget that detects various irritants in the environment surrounding the patient in order to identify any indicators of asthma episodes or an unhealthy environment. As a result, asthma patients may determine whether or not the atmosphere around them is safe, allowing them to take necessary action. Additionally, the gadget has the capacity to send data to a physician for follow-up on the patient's situation, as well as a display that shows the ambient condition around the patient. Furthermore, using ThingSpeak, the band gadget shows data reordered in daily testing, allowing the patient and physician to assess improvement from prior days. According to the suggestions of physicians and telemedicine professionals, the band gadget is also linked with medical criteria. Finally, the smart bronchodilator is linked to the band to make it easier to locate.

Keywords: Asthma, IOT, Arduino, ESP32, Sensors, ThingSpeak, Machine Learning.