title: Improved particle swarm optimization algorithm for android medical care IOT using modified parameters.
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.
authors.affiliation: Department 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
authors.forename: Wen-Tsai
authors.initials: WT
authors.lastname: Sung
authors.forename: Yen-Chun
authors.initials: YC
authors.lastname: Chiang
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D001330:Electronic Data Processing / Q000379:methods*; D020407:Internet; D058998:Remote Sensing Technology / Q000295:instrumentation*; D014584:User-Computer Interface