Enhanced data fusion model for wireless sensor networks

Abstract

newline Wireless Sensor Networks (WSN) have been used as the newlineinevitable technology in critical applications like environment newlinemonitoring such as air pollution and fire detection etc. The energy newlineconsumption issue in WSN is very crucial as it affects the efficiency of newlinethe network severely. Since sensors are deployed in a large newlineenvironment, sensors have restricted energy backup and also battery newlinerecharge and replacement are very difficult to achieve. Thus, energy newlineconsumption is a prominent challenge for WSN. Data fusion is the most newlineefficient way to conserve energy in WSN. Through data fusion, missing newlinedata imputation, the redundant data removal, and noisy data acquired newlinefrom the sensor can be reduced, which can reduce the overall network newlineenergy consumption and thereby extend the lifetime of the sensor newlinenetwork. This will reduce the burden of processing entire data at the newlineBase Station (BS). Now, these fused data in the BS are considered to newlinemake any decision. The second issue is uncertainties in the incoming