Enhancing Energy Efficiency in Commercial Office Buildings: A Smart IoT and Machine Vision Approach

Commercial office buildings often waste substantial energy due to the inefficient use of HVAC and lighting systems. This paper introduces an innovative Internet of Things (IoT) and Machine Vision-based system to combat this issue and improve energy efficiency. The system combines real-time occupancy detection using the You Only Look Once (YOLO) object detection method with CCTV footage obtained through the ESP32 cam module. Additionally, machine vision technology evaluates ambient light conditions. Leveraging the gathered occupancy and lighting data, the system autonomously controls lighting and employs a novel algorithm to regulate HVAC activation for cooling, factoring in indoor and outdoor temperatures. Our approach achieved an impressive accuracy rate of 96.31%. Specifically designed for office environments where occupants typically prioritize energy conservation less, this system offers a discreet solution that dynamically adjusts to real-time occupancy patterns. By implementing this system, commercial buildings have the potential to reduce energy consumption while ensuring occupant comfort is maintained significantly.