ew 18: e25

Research Article

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

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  • @ARTICLE{10.4108/eai.13-7-2018.165522,
        author={Murali Subramanian and Jaisankar Natarajan and Rajkumar Rajasekaran},
        title={Energy-aware and Bandwidth Allocation for Air Pollution Monitoring System using Data Analytics},
        journal={EAI Endorsed Transactions on Energy Web: Online First},
        volume={},
        number={},
        publisher={EAI},
        journal_a={EW},
        year={2020},
        month={7},
        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)},
        doi={10.4108/eai.13-7-2018.165522}
    }
    
  • Murali Subramanian
    Jaisankar Natarajan
    Rajkumar Rajasekaran
    Year: 2020
    Energy-aware and Bandwidth Allocation for Air Pollution Monitoring System using Data Analytics
    EW
    EAI
    DOI: 10.4108/eai.13-7-2018.165522
Murali Subramanian1,*, Jaisankar Natarajan1, Rajkumar Rajasekaran1
  • 1: Vellore Institute of Technology, Vellore, Tamil Nadu, India
*Contact email: murali.s@vit.ac.in

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).