| Abstract |
The growing need for sustainable energy management in commercial buildings has led to the exploration of advanced technologies such as the Internet of Things (IoT). This thesis investigates the application of IoT-based systems to optimize energy consumption in commercial buildings, with a particular focus on integrating occupant behavior analysis through computer vision techniques and sensor data. The study begins by highlighting the significance of energy management in commercial buildings, emphasizing the economic, environmental, and regulatory benefits. It also explores the potential of IoT in enhancing energy efficiency through real-time monitoring, automated control systems, and predictive maintenance. The research methodology involves a mixed-methods approach, combining quantitative data from temperature, light sensors, and electric meters with qualitative insights from CCTV footage analysis. The study also considers the role of occupant behavior in energy consumption and the potential for IoT systems t
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