Soft fuzzy computing to medical image compression in wireless sensor network-based tele medicine system

Wireless sensor network can be used to construct a telemedicine scheme to bring together the patient data and expansion of medical conveniences when disaster occurs. The Remote Medical Monitoring (RMM) scheme of the disaster period can be constructed using the Health care center (CC), Wireless sensor nodes and a few Primary health care centers (PHC). The sensor nodes possess the capacity of making communication between patients and PHCs. This type of WSN experiences limited lifetime problem due to the limited battery energy and transmission of medical data in large quantity. This paper proposes a new and novel WSN based Disaster Rescue Telemedicine Scheme to minimize energy consumption and to maximize network lifetime. The proposed method reaches this milestone using three novel algorithms namely ‘ Network clustering using Non-border CH oriented Genetic algorithm, Fuzzy rules and Kernel FCM (NCNBGF) ’, ‘ High gain MDC algorithm (HGMDC) ’ and ‘ Critical node handling using job limiting and job shifting (CJLS) ’. The principal technologies used in this paper are Network node clustering, Medical image compression and Critical state node energy management to elongate the life period of WSN. The Simulation results prove that the proposed method amplifies the WSN topology lifetime to a significant level than the earlier versions. The Existing methods compared in this paper holds only 20% energy at the round 80,the proposed method stays with 43% of energy.

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