Energy Aware Routing Based on Multi-sensor Data Fusion for Wireless Sensor Networks

In this paper a multi-sensor data fusion approach for wireless sensor system based on Bayesian strategies and Ant Colony Optimization procedures have been recommended. In this methodology, every node is furnished with various sensors (i.e. temperature and humidity sensors). Usage of more than one sensor gives additional information about the environmental conditions. The data fusion based on the competitive type hierarchical processing has been considered for experimentation. In the data fusion, the data gathered by the sensors are set in the sensing fields and afterward the data fusion probabilities are registered. In our suggested approach, the gathered temperature and humidity information are prepared by multi-sensor data fusion strategies, which then helps in diminishing the energy utilization and also communication cost through accumulation of the repetitive information. The multiple information merging process is reliable and accurate in addition to being energy-efficient which our primary goal is. The proposed algorithms were simulated utilizing Matlab. The implementation of the proposed algorithms were conducted with and without multi-sensor data fusion and the outcomes demonstrate that the proposed algorithms could reduce the energy-consumption, rather save additional energy, thus enhance the entire lifetime of the system.