Pedestrian flow counting-based intelligent detection method for indoor dynamic cold load

Abstract

The invention discloses a pedestrian flow counting-based intelligent detection method for an indoor dynamic cold load. The number of residual pedestrians is obtained by counting the flow of pedestrians who enter or exit from a room; and finally, a dynamic cold load is calculated by combining the current time, the indoor temperature, a clustering coefficient of places, the labor intensity of pedestrians and the total time of the pedestrians detained in the room. The pedestrian flow is counted by video mounting of inlet and outlet areas of the room. The pedestrian flow counting-based intelligent detection method comprises the following steps of: firstly, detecting an area of an object by adopting a moving object detection algorithm; secondly, tracking a motion curve of the object by adopting a tracking algorithm; and finally, analyzing the behavior of the object according to the motion curve and the layout of the room. According to the pedestrian flow counting-based intelligent detection method disclosed by the invention, the pedestrian flow can be counted more accurately, accurate and reliable real-time cold load data are provided for the operation of an indoor air conditioner and the optimized energy-saving control is realized.

Description

technical field [0001] The invention relates to a detection method for indoor dynamic cooling loads, in particular to an intelligent detection method for indoor dynamic cooling loads based on people flow statistics. Background technique [0002] At present, the technical research on indoor static cooling load detection is quite mature. For example, the application number is CN201010610670.7, and the invention patent titled "Real-time Cooling Load Determination Method for Air-Conditioned Room". However, as the number of people in the room changes, the cooling load in the room should also change accordingly. If the air conditioner only considers the static cooling load factor, then the cooling effect will be insufficient if there are too many people, and energy will be wasted if there are few people. Therefore, it is not enough to detect the cooling load only by the indoor equipment environment, and the factors of the indoor flow of people must be fully considered. [0003] ...

AI Technical Summary

Problems solved by technology

However, it is not comprehensive to identify targets only by human head features

First of all, if you want to obtain the head features of people well, the camera is required to have a certain height and tilt angle, which has a certain space limit for the deployment of camera equipment; secondly, the head features cannot represent all of the people. people may have similar head features, which can lead to object tracking errors

Images