Exploiting Big Data Analytics for Smart Urban Planning

Abstract

Air pollution is a major environment issue in smart cities. Millions of people around the world are at health risk due to the air pollution. Real- time monitoring of Air Quality helps to identify the current situation of city which helps the government and inhabitants to take precautionary measures. Internet of things (IoT) based sensors have changed the way for monitoring of Air Quality Index (AQI). However, requirements of architecture for analyzing and monitoring of large data generated by the IoT devices are not fulfilled. In this article, we have proposed Apache Spark based architecture for smart urban planning which makes use of the big data analytics in classifying the air quality. The proposed architecture is implemented on the data set of vehicles pollution of Aarhus city in Denmark. The results show that the proposed architecture is efficient and accurate for analyzing and classifying the AQI.