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Improved particle swarm optimization algorithm for android medical care IOT using modified parameters
Wen-Tsai Sung1, Yen-Chun Chiang
1Department of Electrical Engineering, National Chin-Yi University of Technology, Taiwan, No.57, Sec. 2, Zhongshan Rd., Taiping Dist., Taichung 41170, Taiwan. songchen@ncut.edu.tw
Abstract:
This study examines wireless sensor network with real-time remote identification using the Android study of things (HCIOT) platform in community healthcare. An improved particle swarm optimization (PSO) method is proposed to efficiently enhance physiological multi-sensors data fusion measurement precision in the Internet of Things (IOT) system. Improved PSO (IPSO) includes: inertia weight factor design, shrinkage factor adjustment to allow improved PSO algorithm data fusion performance. The Android platform is employed to build multi-physiological signal processing and timely medical care of things analysis. Wireless sensor network signal transmission and Internet links allow community or family members to have timely medical care network services.
