Utilizing the Improved QPSO Algorithm to Build a WSN Monitoring System

This research uses the improved Quantum Particle Swarm Optimization (QPSO) algorithm to build an Internet of Things (IoT) life comfort monitoring system based on wireless sensing networks. The purpose is to improve the quality of intelligent life. The functions of the system include automatic basketball court lighting system, monitoring of infants’ sleeping posture and accidental falls of the elderly, human thermal comfort measurement and other related life comfort services, etc. On the hardware system of the IoT, this research is based on the latest version of ZigBee 3.0, which uses optical sensors, 3-axis accelerometers, and temperature/humidity sensors in the IoT perception layer. In the network transmission layer, the central network architecture is used for connection. In the application layer, we have designed a graphical interface for real-time values and information that can be read at any time and place using mobile devices. In this study, authors use the improved QPSO algorithm in the calculation part, so that the target can be effectively positioned outside the numerous surveillance data. This study uses various sensor data fusion technologies to make the IoT system becomes able to provide more extensive and even better services than ever before. In short, this research work has proven to be an effective way to reduce power consumption, improve medical quality and provide higher comfort for intelligent lift level.