Air pollution monitoring and prediction using IoT

The internet of Things (IoT) is a course of action interrelated computing devices, mechanical and advanced machines, objects, or people that are given unique identifiers and the capability of exchange information over a system without anticipating that human to human or human to machine communication. In this work an IoT based air pollution monitoring and prediction system is proposed. This system can be utilized for monitoring air pollutants of a particular area and to air quality analysis as well as forecasting the air quality. The proposed system will focus on the monitoring of air pollutants focus with the combination of IoT with a machine learning algorithm called Recurrent Neural Network more specifically Long Short Term Memory (LSTM).

[1]  Zhao Wei,et al.  A comprehensive evaluation of air pollution prediction improvement by a machine learning method , 2015, 2015 IEEE International Conference on Service Operations And Logistics, And Informatics (SOLI).

[2]  Byron Oviedo,et al.  IoT for Environmental Variables in Urban Areas , 2017, ANT/SEIT.

[3]  Deepak Mehetre,et al.  Wireless sensor network based pollution monitoring system in metropolitan cities , 2015, 2015 International Conference on Communications and Signal Processing (ICCSP).

[4]  Chen Xiaojun,et al.  IOT-based air pollution monitoring and forecasting system , 2015, 2015 International Conference on Computer and Computational Sciences (ICCCS).

[5]  Abdullah Kadri,et al.  Urban Air Pollution Monitoring System With Forecasting Models , 2016, IEEE Sensors Journal.

[6]  Biswajit Mishra,et al.  IoT enabled environmental monitoring system for smart cities , 2016, 2016 International Conference on Internet of Things and Applications (IOTA).