The Research And Implementation Of Fall Monitoring System Based On WSN

Wireless sensor network (WSN) which is a new wireless network with data-centric andapplication-oriented. It is regarded as a ubiquitous sensor technology in the low-speed field.Meanwhile, it integrates Internet and mobile communications network, which will changesthe interactive way of man-reality. Fall among the elderly has become an important factor toharm people’s health. The most effective way to reduce harm is to monitor and judge fallevent effectively. The article illustrates the application of WSN technology in the fallmonitoring system, researches the fall recognition rate and develops sensor-driven based onTinyOS and nesC language.This paper introduces performances of the Wireless Sensor Network and fall monitoringsystem, studies and proposes a monitoring model based on the combination of accelerationand pressure sensors, and sends information after integration judgment of processor by theGPRS communication module. On the basis of summarizing and drawing the existingalgorithms, the article proposed twice-judgment algorithm based on classification analysis oflife events, which combines threshold and vote algorithm fusion. The article proposed designsketch of hardware and software of the system and developed sensor driver based on nesClanguage. Besides, the article completes the implementation and verification of the designalgorithm. By testing the RSSI value and the system packet loss rate, the article verifies thestability of the system. Then the article obtained the appropriate classification threshold andempirical probability through the acquisition of real-time human data analysis andimplements the fall test in a reasonable environment.The experimental results verify the stability and effectiveness of the system, indicatingthe integrity and rationality. The last part is summary of the paper, which makes a briefanalysis of research prospects.