A Multi-Sensor Based IoT Predictive Framework for Pediatric Asthma Exacerbations Using Environmental and Physiological Parameters

Asthma is a prevalent chronic respiratory condition in children, characterized by airway inflammation and hyperresponsiveness, which is frequently triggered by environmental and physiological causes. Children with asthma are more likely to experience exacerbations, which have a severe impact on their quality of life and need immediate medical attention. To address this concern, a device is proposed that can anticipate asthma exacerbations in children by measuring critical factors such as air quality, heart rate and SpO2 levels. The system monitors these vital parameters in already diagnosed pediatric patients to assess the possibility of an impending asthma attack. It utilizes sensors to collect real-time data and transmits it wirelessly to a mobile application using Bluetooth Low Energy (BLE) communication. This novel device will provide immediate alerts to caregivers via an Android application, allowing for early intervention and proactive asthma management to improve results and the well-being of asthmatic children.