Air Pollution Monitoring and Prediction using Multi View Hybrid Model
A.Sivasangari1, P.Ajitha2, K.Indira3
1A. Sivasangari, Assistant Professor, Sathyabama Institute of Science and Technology, Chennai (TamilNadu), India.
2P. Ajitha, Assistant Professor, Sathyabama Institute of Science and Technology, Chennai (TamilNadu), India.
3K. Indira, Assistant Professor, Sathyabama Institute of Science and Technology, Chennai (TamilNadu), India.
Manuscript received on 13 April 2019 | Revised Manuscript received on 20 April 2019 | Manuscript Published on 26 July 2019 | PP: 1370-1372 | Volume-8 Issue-6S4 April 2019 | Retrieval Number: F12770486S419/19©BEIESP | DOI: 10.35940/ijitee.F1277.0486S419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Pollution monitoring system is used to monitor the air pollution throughout the city, which cause pollution over a specified limit. The sensor nodes are attached to the lamp post. The sensors are organized into clusters and form a mesh network of nodes that provide both single hop and multihop connectivity with the base station. The GPS enabled sensor nodes finds location in order to detect the pollution occurring place. A hybrid model is proposed in this work which combines the spatial and temporal features for prediction. This model use the real time air quality information in a city by measuring the pollution information using sensors and data sets.
Keywords: Spatial Features, Temporal Features, AQI.
Scope of the Article: Health Monitoring and Life Prediction of Structures