IoT-AI Based Air Quality and Hazardous Gases Advisory System to Mitigate Effect of Climate Change on Public Health
Keywords:
AQI Gadget, AI and IoT, Advisory System, Hazardous Gases, Sustainable Development GoalsAbstract
Today, air pollution has become a major concern lowering the average life expectancy [1], causing a wide range of diseases including stroke, heart disease, lung cancer, and both chronic and acute respiratory diseases, including asthma [2]. In Pakistan, the hazards of noxious gases contamination have been reported throughout the country leading to a high number of casualties, specifically heater/car/indoor gas contamination-related deaths [3], the release of toxic industrial gas into the environment (more than 300 people reported sudden difficulty in breathing and several deaths in south Karachi in 2020 due to gas leakage from industry [4][5]). Such concerns are not only a threat to human life but also not complying with UN sustainable development goals and also impacting the ecosystem. In this study, we proposed the design solution and a working prototype based on a low-cost life-saving IoT gadget in combination with an AI-enabled mobile app to cope with the existing problem of airborne diseases, life-threatening contamination of hazardous gases and to mitigate climatic change related to Air Pollution. The gadget contains sensors to detect air pollutants including fine particulate matter (PM2.5, PM10), Carbon Dioxide (CO2), Sulphur, Nitrogen Dioxide (NO2), Flammable hazardous gases like Methane (CH₄), and LPG Gases (hydrocarbons), and life-endangering Carbon Monoxide (CO) and Smoke along with basic humidity, temperature and air pressure in real-time, buzzer for an alarm in case of hazardous gas crossing the threshold, integrated WiFi module for data replication to the database (Firebase) and colorful TFT screen to display the real-time measurements of air quality and other pollutants. On the backend, the real-time data from the gadget is logged into the cloud-based database, where a machine learning algorithm, ‘Random Forest’, is deployed and performs the task of air quality prediction for the next few hours. Our solution with mobile application aims to target the public healthcare and abrupt climatic change effect where GUI assist users with recommendations, public alerts, and possible solutions for prevention.
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