An energy efficient and traffic aware data fusion scheme for water pollution monitoring

Abstract

Background/Objectives: One of the main application of underwater wireless sensor network is water pollution monitoring. Therefore it is proposed to use an energy efficient and traffic aware data fusion scheme (ETDFS) for this kind of application. Methods: Data fusion comprises preprocessing and processing steps. In the preprocessing step, a probabilistic data structure entitled bloom filter is used to reduce the number of transmissions and save precious energy. In the processing step, a cost effective data fusion scheme called fuzzy logic is utilized to process the gathered data at sink and determine the level of pollution. Findings: ETDFS is superior than other proposed techniques for water pollution monitoring since it reduces the number of transmissions and eliminates redundancy hence the precious energy is saved and water pollution monitoring can be done for longer time. Application/Improvements: ETDFS enhance energy efficiency and network lifetime further it reduces network load and loss rate. It can be used in deep waters like sea and ocean.