OCCUPANCY ESTIMATION SYSTEM BASED ON CARBON DIOXIDE CONCENTRATION USING DYNAMIC NEURAL NETWORK

摘要

The present invention relates to a system for estimating a number of people in a room based on carbon dioxide concentration using dynamic neural network. The system comprises: a sensor unit for measuring the concentration of carbon dioxide contained in the indoor air; a storage unit for storing the concentration of carbon dioxide, measured by the sensor unit, in real time; at least one dynamic neural network unit for estimating a number of residual people positioned in a room using the concentration of carbon dioxide stored in the storage unit; and a neural network learning unit for comparing the number of residual people estimated by the dynamic neural network unit with a reference value previously inputted for the number of residual people, comparing an error between the number of residual people and the reference value with a predetermined threshold, and adjusting a weighted value and a deflection value of a transfer function which configures the dynamic neural network unit in a direction in which the error of the reference value decreases, and proposes a technique of efficiently grasping people in a building room. Thus, installation and maintenance costs can be cheaper than those of a conventional method for checking the number of people in a room using video cameras or motion recognition sensors, and reliability can be improved by removing a dead zone. [Reference numerals] (100) Sensor unit; (200) Storage unit; (300) Dynamic neural network unit; (400) Neural network learning unit