An infrastructure of multi-pollutant air quality deterioration early warning system in spark platform

摘要

In recent years, the increase of multi-pollutant air pollution index has a direct impact on people's health. Relevant studies have pointed out that the exposure of air pollutants has a strong connection with asthma and other unhealthy diseases such as the lungs. The air pollution has brought health issue, but also caused a huge medical costs each year derived from the disease. Although there are many different approaches to forecasting air pollution, most of them are based on historical data and the environment of local server devices. Some of the data records may differ from those of real-time situations and those limitation of traditional hardware devices. Therefore, this project tries to adopt Azure, a cloud computing platform with advantages of scalability, reliability and agility, to set up a multi-pollutant air quality deterioration warning system. This project is divided into three parts. The first part is the collection of multi-pollutant data and the prediction of multi-pollutant air pollution quality. After the government and private data are collected and integrated into the database, the air quality of multi-pollutant are predicted. The second part is big data analysis of air quality indicators for pollutants indicator AQI, AAQI, and HAQI AIDE, a real-time deterioration warning system for deteriorating, was popularized in Spark for big data analytics framework and various reports were generated. The third part will be a combination of blockchain and perpetual system performance assessment. The overall system will integrate with the blockchain and conduct a continuous evaluation of the system.