Smart Work Scene System Design, Implementation And Performance Analysis

With the development of concept of "Internet of Things" and its core technology, the intelligent systems have gradually entered the people's lives.These applications will greatly improve the efficiency of work and quality of life.In these intelligent systems, ZigBee networks are low-level wireless sensor networks due to their own advantage.Z-Stack application framework is the core solution of the wireless sensor network.Although most of the intelligent systems have the same low-level technology, the different intelligent systems have the different application backgrounds and different requirement to the core performance.In addition,the Z-Stack as a sensor network solution running on the specific hardware platforms has its own limitations.We need to research,analysis and design for the specific application.The smart work scene system is an application system based on the core technology of internet of things to the specific requirement of people's work and life.It uses computer, internet of things-related technology to get the information involved in the work scene and process the information in order to intelligent monitoring. This paper analysis and studies the smart work scene system based on the ZigBee networks.In this paper, we use the Z-Stack application framework provided by TI (Texas Instruments) company as the fundament, give the detailed design.According to the ZigBee network, we proposed an improved sink node design plan in order to increase the ZigBee network data processing ability. To the need of smart work scene system,we propose the number of network nodes, node power consumption and location accuracy as the core indicators.We research the three core indicators, give the calculating modes to the node numbers of smart work scene system,analysis the factors and provide a plan to increase the node numbers.We research the dynamic power management and RSSI (Received Signal Strength Indication)-based positioning used in the system.We further study the node energy consumption and RSSI positioning accuracy, we propose an experience-based location forecasting mode for system and give a plan to meet the system requirements in both node energy consumption and positioning accuracy. At last,we implement the whole system.