Air pollution prediction through internet of things technology and big data analytics. (26th September 2019)

• Record Type: Journal Article
• Authors: Alaoui, Safae Sossi; Aksasse, Brahim; Farhaoui, Yousef
• Is Part Of: International journal of computational intelligence studies. Volume 8:Number 3(2019)
• Page Start: 177
• Page End: 191
• Publication Date: 2019-09-26
• Subjects: internet of things -- IoT -- wireless sensor networks -- WSNs -- air pollution -- air quality index -- AQI -- big data analytics -- Apache Spark; Computational intelligence -- Periodicals; 006.305
• Languages: English
• ISSNs: 1755-4985

Abstract

Air pollution is one of the biggest and serious challenges facing our planet nowadays. In fact, the need to develop models to predict this issue is considered so crucial. Indeed, our work aimed at building an accurate model to predict air quality of US country by using a dataset collected from connected devices of internet of things (IoT), namely from wireless sensor networks (WSN). Therefore, the huge amount of data captured by these sensors (approximately 1.4 million observations) brings about a highly complex data that necessitates new form of advanced analytic; it is about big data analytics. In this paper, we examine the possibility to make a fusion between the two new concepts big data and internet of things; in the context of predicting air pollution that occurs when harmful substances; like NO2, SO2, CO and O3, are introduced into Earth's atmosphere.