Fostering Air Pollution using Cloud Computing and IoT-based Methods

Each year, the number of people dying from pollution rises, and air pollution is the main factor in these deaths. Car pollution is a key contributor to air pollution (AP) caused by various sources. Most cities have poor air quality that does not meet health standards. The major issue in the contemporary civilised world is AP, which hurts human health and the environment. With numerous emission sources, motor vehicles and industrial processes are the principal causes of air pollution. Both short-term and long-term exposure to airborne toxicants can have various toxicological consequences on people, including long-term chronic disorders including cancer, neuropsychiatric issues, skin diseases, eye irritation, and respiratory and cardiovascular illnesses. Using the Internet of Things (IoT), track air pollutants in a given area and analyse and forecast air quality. This article will combine cloud computing with the AP-IoT strategy to deliver these services more swiftly and in real time. The area of town where the intended system will be installed is very polluted. The concentrations of each hazardous contaminant are monitored regularly. A mechanism is in place for monitoring and reducing traffic in areas with high pollution levels. The answer in this situation is a sensor-based hardware module that can be positioned beside roads. These gadgets mounted on lampposts may wirelessly send information about air quality to a remote server. For traffic control, this information may be used. This technology will be developed further so consumers can get weekly or monthly air quality reports via an easier-to-use mobile app. Commuters can choose routes where the air quality is good thanks to a smartphone application that provides information about it. The experimental results show that, in comparison to other approaches already in use, the suggested AP-IoT model improves prediction ratios of 98.9%, accuracy ratios of 95.6%, stability ratios of 97.85, efficiency ratios of 96.7%, and air quality detection ratios of 97.9% while lowering the RMSE value to 9.8%.