A Review on Various IOT Analytics Techniques for Air Pollution Detection in Fog Computing

Abstract

Atmospheric contamination has deteriorated the health of plants and animals all over the globe. In particular, pollutants such as benzene(C6H6) has accelerated the rate of cancer among human beings. Therefore, accurate evaluation of the pollutant in the atmosphere is necessary by traffic supervision in urban areas. To reduce atmospheric contamination, an effective mobile strategy planning must be developed. Currently, the atmospheric contamination is measured using spatially scattered networks with limited sensors. Although, these networks and sensors can evaluate the air pollution accurately, however the sensor expenses and size might limit the operational efficiency. In this paper we discuss about the various techniques of IOT and also discuss the detection of air pollution in fog computing. The overall objective of this paper is to detect the air pollution in IOT and we analyze IOT performs better than other techniques.

Air2Day: An Air Quality Monitoring Adviser in Morocco

“…To Cover a wide geographic area, A sensor-based network is the general solution, as seen in other parts of the world (China, Europe, the USA [3]). usually, the network is comprised of multiple IoT devices and sensors connected to the internet to deliver rich local data to central servers to be cleaned, preprocessed, and visualized on web or mobile interfaces as in the form of numerical inferred measurements that describe the weather and pollution based on the users' GPS location, this IoT approach is expensive and very hard to establish given the limited resources and difficult procedures one needs to go through to install the sensors to cover Morocco, because of that, a relatively novel concept is proposed that's based on the idea of using satellite measurements and imagery to tackle the problem of pollution monitoring in Africa and especially Morocco.…”