| Abstract |
The 'Smart Occupancy Detection and Activity Recognition' project aims to develop an innovative solution for monitoring and managing occupancy and activities within indoor environments, focusing on enhancing energy efficiency and promoting smart building technologies. The project leverages advanced sensors such as passive infrared (PIR) or radio frequency (RF) sensors for occupancy detection, combined with activity recognition algorithms, to provide real-time insights into the presence and actions of individuals in a room. This system is designed to function in various settings, including healthcare facilities, offices, educational institutions, and residential buildings, ensuring that energy usage is optimized by dynamically controlling devices such as lighting, HVAC systems, and other utilities based on occupancy and activity data. The primary goal of this system is to reduce energy waste and ensure that energy-consuming devices operate only when needed, thereby improving energy efficiency. This is achieved through automated control mechanisms that adjust the power consumption of equipment in response to real-time occupancy and activity patterns, ensuring a sustainable and cost-effective approach to building management. Additionally, the system is designed to be scalable and easily integrated with existing infrastructure, offering versatility and applicability across various sectors. The potential applications of this technology are vast, particularly in the context of smart cities, where energy efficiency is a critical concern. By automating building management tasks based on real-time data, this project contributes to the broader goals of sustainability and resource optimization, supporting the ongoing transition towards smart, energy-efficient infrastructures. © 2025 IEEE. |
