Automatic Human Detection System for Air Conditioner Using Integration of Sensors

Abstract

Modern buildings rely on Heating, Ventilation, and Air Conditioning (HVAC) systems to control indoor temperature and air conditions. Traditional HVAC systems tend to run without interruption for heating or cooling operations, even when the rooms remain unoccupied. The strict fixed operation of these systems causes substantial energy loss because they keep running while occupying spaces such as empty offices, conference rooms, and residential areas. This study presents an automated AC control system that operates based on real-time human occupancy to enhance energy efficiency. The proposed platform employs sensor tools coupled with artificial intelligence methods to boost energy performance together with maintaining satisfactory indoor comfort. PIR sensors detect body heat for motion detection and IR sensors scan thermal signatures to identify stationary people. These two sensor types work harmoniously to watch room occupancy. The system uses microcontrollers as its central processing unit to receive data from sensors in real-time. A microcontroller evaluates occupancy patterns through its specialized algorithm to automatically control AC operations. When there is no detected activity the automated system either activates its low-energy state or disables air conditioner operation. People entering the room initiate the system to restore heating or cooling functions to the set comfort parameters. The system design eliminates unneeded energy consumption during empty time because it provides comfort control at strategic times. Scientists performed field experiments with the proposed model in both office areas and private living spaces to demonstrate its value relative to standard HVAC equipment. The practical evaluation showed a 40% decrease in power usage while users experienced identical comfort levels.