Optimization of Public Building Monitoring System Based on Human Behavior

Abstract

In recent years, with the rapid development of the economy, China s building energy consumption has increased year by year, and energy conservation has become an inevitable requirement for development. Among them, the impact of human settlements on building energy consumption is obvious, and the study of building energy consumption by human settlements has certain social significance. At present, the research on the model of human behavior is obtained under certain assumptions, resulting in inaccurate results. Therefore,a set of energy consumption monitoring system platform based on personnel behavior was developed, and the number acquisition device was developed. The cumulative error estimation algorithm was used to optimize it, which provided a data foundation for solving the problem of energy-saving optimization of intelligent buildings based on human settlements. Introduction Our large-scale public construction area of less than 4% of the total area of the town, but the total energy consumption accounts for 22% of total electricity consumption in cities and towns. Domestic and foreign companies and scholars have conducted a lot of research on energy of building consumption monitoring[1]. The Pacific Northwest National Laboratory has developed a software (WBD) that can be used to diagnose building energy savings, which provides a statistical analysis of the overall energy use in the building. The above results have been researched and applied in terms of building energy conservation, but few of them consider building energy conservation from the perspective of human behavior. So we independently developed a monitoring system based on the Habitat building behavior. The focus has been on improving the number of people collecting devices. The high-precision camera is used on the hardware. The algorithm uses the cumulative error estimation algorithm to improve the accuracy of the number-collecting device, and provides a data foundation for building energy-saving optimization for the subsequent settlement of human behavior. Human Behavior Monitoring System The system[2] consists of slave nodes, master nodes, and a host computer. The node group part are different carrier maters for data acquisition and status monitoring; the concentrator is responsible for communicating with the node group and the host computer, acquiring the downlink node group data in real time and timing and storing, and uploading the data timing to the upper computer, and capable of receive the host computer command to control the indoor electrical equipments[3-7]. The LabVIEW software used by the host computer software implements functions such as receiving, displaying, storing, and controlling power devices. Figure 1 shows the structure of the building automation monitoring system. 2nd International Conference on Electrical and Electronic Engineering (EEE 2019) Copyright © 2019, the Authors. Published by Atlantis Press. This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/). Advances in Engineering Research, volume 185