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

Abstract

The most debated phenomena of the 21st century which might change the global landscape for living organisms. The samephenomena could even threaten climate pattern. Because of this, the earth may experience a highly unstable natural disasterlike 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 techniquereferred to as the Air pollution monitoring system with Swarm Intelligence (CASI-CSA-IAFSA) that will do the clusteringof sensor nodes and the assortment of sensor nodes. Then the aggregated data would transmit the optimal route to the basestation designated employing the artificial fish swarm technique. The proposed research technique by the introduction of thestrategy referred to as the bandwidth allocation aware Air pollution monitoring system with cuckoo and fish swarm approach(BA-APMS-CSFSO).

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)