This paper improve the original particle swarm optimization (PSO) algorithm in the fixed inertia weight, this study analyzed the value of inertia weight factor in (PSO) algorithm, and proposed a non-linear weights with decreasing strategy to implement the Improvement PSO (IPSO) algorithm and estimate the weighted factor in the data fusion of multi-sensors network. This FLAG Programmable System On Chip (SoC) Developing System 1605A (FLAG-the PSoC-1605A) as an experimental platform, using various types of sensors, combined with ZigBee wireless sensor networks, the TCP / IP network and the GPRS / SMS long-range wireless network will sense the measured data analysis and evaluation, to create a more effective monitoring and observing regional environment to achieve a things and things, and automated exchange of information between persons and things, processing an intelligent network. Finally, the IPSO applied the IOT system in monitoring environment is better than other existing PSO method in computing precise and convergence rate for excellent fusion result.
