Air Quality Monitoring and Predicting the People to be Affected using LSTM for Hospitals (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2021)
Air pollution is one of the major concerns in the modern era , around 4.6 million people die in a year due to air pollution , with over 91% of the world population living in unhealthy surroundings which does not meet the standards of the World health organization(WHO). In India around 1.2 million people die early due to air pollution and 9 out of 10 people in India live in unhealthy environments. Though the world is developing at a rapid pace, solutions for such a problem are still unknown, many systems are available to monitor the air pollution around the world but nothing has been done to the healthcare field. This system not only monitors the air pollution but also can predict the number of people going to get affected in a particular area and inform nearby hospitals through which the hospitals can approximately buy medicine for the patients. The Novel Air Quality Monitoring System-Artificial Intelligence( NAQMS-AI) is proposed, which implements artificial intelligence to predict the number of people going to get affected using Long Short Term Memory also known as LSTM algorithm. The air quality of a particular area is calculated based on the location of the device which is computed with the help of Google API , it also helps in finding the nearby hospitals and filter the sensors based on their location. The data which is got from the sensors are stored in cloud which is Google Drive in the form of excel sheet. Thus the proposed system helps the hospitals to keep track of how many people are going to get affected on monthly basis and can approximately estimate the cost for treating all the patients.