Zigbee Network Monitoring System Based On Neural Network Prediction Algorithm Design

The traditional wired method for networked control system has several shortcomings such as wiring difficulty, inconvenient maintenance and management, poor expansibility. Therefore, developing a wireless networked monitoring system based on ZigBee, controlled by central server has the significant meaning from both the perspectives of control system theory and engineering practice.In this thesis, we design the ZigBee monitoring system. And the design intention of central server aims at data storage, processing, maintenance and management. Moreover, we propose a novel Artificial Neural Network (ANN) based on Multi-Subgroup Parallel Genetic Algorithm (MSPGA).The MSPGA neural network is adopted in the error detecting and data recovery mechanism to enhance the stability and reliability of monitoring system. The mechanism employs ANN data forecasting as its solution for data lost and system error.The thesis describes requirement analysis of the control system, function designing and module developing thoroughly. A ZigBee monitoring system is developed based on Client/Server architecture. Meanwhile, we test and evaluate functions of the ZigBee monitoring system. The results indicate that the system performs very well on system stability and reliability, and the developed functions match our requirement perfectly.