An IoT-Based System for Controlling and Monitoring Air Conditioning Energy Consumption in Building - CHEUSOKXAY, Souyaket; Thongphanh, Phutsavanh (Souphanouvong University Journal Multidisciplinary Research and Development, 2026)
Currently, electricity management within office buildings and educational institutions frequently faces energy inefficiency in air conditioning systems due to the lack of effective monitoring and control mechanisms. This paper presents the design and development of an air conditioner control and energy monitoring system integrated with Internet of Things (IoT) technology. The primary objective is to enhance energy management efficiency and monitor electrical behavior in real-time via a smartphone application. The system utilizes the ESP32 microcontroller board by Espressif Systems as the central controller, operating in conjunction with a Peace fair Electronic PZEM-004T sensor for electrical measurement, an AOSONG Electronics DHT22 sensor for environmental monitoring, and a 38 kHz infrared (IR) transmitter to deliver control commands to the air conditioner without modifying its legacy hardware structure. Additionally, MATLAB software was implemented to analyze the 24-hour load profile and energy consumption patterns. The experimental results indicated that the system achieved a 100% command execution accuracy via smartphone with an average response latency of only 1.5 seconds. Based on the statistical error analysis compared against a calibrated laboratory instrument, the proposed IoT system demonstrated high fidelity, exhibiting a percentage error of merely 0.31% for voltage and 0.76% for real power, which is well within acceptable engineering tolerances. Furthermore, when implementing the smart scheduling feature to automatically turn off the air conditioner during lunch breaks and non-working hours, the system successfully optimized power distribution, yielding an overall energy saving of 25.21% compared to traditional manual operation. In conclusion, this low-cost innovation proves highly effective as a prototype for smart building applications, providing empirical data to support scientific and efficient energy-saving policies.