MULTIVERSE CROW CONSCIOUS CLUSTERING ROUTING AND COVERAGE OPTIMIZATION HEALTH MONITORING ALGORITHM DURING COVID-19 PANDEMIC

Abstract

Covid-19 crisis has put the healthcare system under stress due to the shortage of healthcare workers in hospitals, the hour of the need is a highly flexible but dependable as well as an sys- tem which can alert hospital authorities immediately through centralized relay about the status of a patient if he/she becomes critical. Such a system may be built using a Big Data enabled Wireless Sensor Networks, which may be set up to monitor patients inside a hospital which shall be monitored through live channel feed by hospital monitoring authorities. The data from the sensors, through big data monitoring and analytics layer, will give crucial and timely results which will surely save many patients lives. In order to implement such a robust system, there is a need to build constant coverage and optimized clustering and routing algorithms which would solve this vital problem. This paper presents a novel energy-conscious clustering routing and coverage algorithm for both equal and unequal distribution in the wireless sensor system and is called as Multiverse Crow Conscious Clustering Routing and Coverage Optimization Algo- rithm. The algorithm has been able to successfully attain the equilibrium of Wireless Sensor Network community energy consumption, enhance energy efficiency, and extend lifespan of the entire network. From the coverage point of view, the algorithm has been able to attain the distribution optimization at a greater rate with a decrease cost, and increase the efficacy of this algorithm. To prove its effectiveness, we have compared the proposed algorithms to multiple Nature Inspired Optimized WSN scenarios.