Energy-aware and Bandwidth Allocation for Air Pollution Monitoring System using Data Analytics

Authors

  • Murali Subramanian Vellore Institute of Technology University image/svg+xml
  • Jaisankar Natarajan Vellore Institute of Technology University image/svg+xml
  • Rajkumar Rajasekaran Vellore Institute of Technology University image/svg+xml

DOI:

https://doi.org/10.4108/eai.13-7-2018.165522

Keywords:

Air pollution, Bandwidth allocation, optimal path, Energy, Cluster head selection, Cuckoo Search Algorithm (CSA), Distributed Wireless Sensor Cluster Algorithm (DWCA), Improved Artificial Swarm Optimization Algorithm (IASA)

Abstract

The most debated phenomena of the 21st century which might change the global landscape for living organisms. The same phenomena could even threaten climate pattern. Because of this, the earth may experience a highly unstable natural disaster like flooding, cyclone, earthquake, tsunami, severe drought and inhabitant environment like the highly polluted atmosphere, intolerable rise in temperature, acid rain, etc, This issue is solved in this research work by the introduction of the technique referred to as the Air pollution monitoring system with Swarm Intelligence (CASI-CSA-IAFSA) that will do the clustering of sensor nodes and the assortment of sensor nodes. Then the aggregated data would transmit the optimal route to the base station designated employing the artificial fish swarm technique. The proposed research technique by the introduction of the strategy referred to as the bandwidth allocation aware Air pollution monitoring system with cuckoo and fish swarm approach (BA-APMS-CSFSO).

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Published

17-07-2020

How to Cite

1.
Subramanian M, Natarajan J, Rajasekaran R. Energy-aware and Bandwidth Allocation for Air Pollution Monitoring System using Data Analytics. EAI Endorsed Trans Energy Web [Internet]. 2020 Jul. 17 [cited 2024 Dec. 22];8(31):e10. Available from: https://publications.eai.eu/index.php/ew/article/view/839