Design And Implementation Of The Portable And Online Indoor Environment Monitoring System

Economic development brings improvement of housing and working conditions,and people spend longer time in the interior, bearing the impact of environmental issues on health problems. Facing of the present situation of indoor environment pollution, it is a topic worthy of study that introducing technology of internet of things and artificial intelligence into indoor environment monitoring, doing real-time monitoring of indoor pollutants while docking with the ventilation system and other equipment, and realizing automatic control of peripherals according to real-time environmental data. According to the above background, based on an old version of the environmental monitoring system to achieve a set of both network and portable indoor environment monitoring system.In terms of system architecture, this thesis studies and analyzes the schema of SCADA systems and workflow, combined with the functional requirements of the project, based on the old hardware joined the wireless WiFi module, put forward a set of networking and portable monitoring system architecture. Collectors can be connected to each other and to the server, realizing a larger scope of environmental monitoring and control within the LAN. Collectors can also work independently, self-contained,cooperated with the Mobile App software, realizing environmental monitoring of a single point.In the area of system automatic control, this thesis studies and analyzes the theory of human comfort, Introducing the BP neural network algorithm which belongs to artificial intelligence technology into the PMV modek, and finally realized online prediction of thermal comfort of human body. Meanwhile, combined with alarm information of analog and switch and configuration information of output control, the thesis achieves the goal of realizing intelligent control of peripherals such as fresh air systems, sound and light alarm.In respects of system function module, this thesis does reconstruction and extension on the programs of collectors and server, and completes the overall design and implementation of the Mobile App. The common aims of reconstruction and extension is to enable the output control of peripheral device and dynamic configuration of monitoring elements. Different from the server, the hardware on the collector is extended and the functionality of caching historical data is added to meet the needs of portable mode monitoring. Mobile App is developed to establish a point-to-point connection with the collector in portable mode and realize the data view, configuration ofparameters and control of peripheral devices.Finally, after testing and verification, results show that the architecture of system is reasonable and functions are comprehensive.Based on PMV model and neural network algorithm, the system realizes online prediction of human confort, and achieve a "monitoring-control" of closed-loop according to the alarm information. Elements can be dynamically configured in the system, and having two network mode makes the system be better adapted to the market demand. The system has a high study and market value.