Thesis Abstract

Abstract
This thesis presents the design and implementation of an Intelligent Energy Management System (IEMS) for Smart Homes, aimed at optimizing energy consumption and enhancing energy efficiency in residential settings. The rapid advancement of smart technologies has facilitated the integration of various devices and systems within homes to enable automation and remote control. However, the efficient management of energy resources remains a critical challenge in achieving sustainability and cost-effectiveness. The proposed IEMS leverages Internet of Things (IoT) technology, data analytics, and machine learning algorithms to monitor, analyze, and control energy usage within smart homes. The research begins with a comprehensive review of existing literature on smart home technologies, energy management systems, IoT platforms, and machine learning algorithms. Through a detailed analysis of the current state-of-the-art solutions, the study identifies gaps and opportunities for developing a more intelligent and adaptive energy management system tailored for residential environments. The research methodology encompasses the design and development of the IEMS prototype, consisting of sensor nodes, actuators, a central control unit, and a user interface for real-time monitoring and control. The system architecture integrates data collection, processing, and decision-making modules to enable automated energy optimization based on user preferences, occupancy patterns, and external environmental factors. A series of experiments and simulations are conducted to evaluate the performance and effectiveness of the IEMS in reducing energy consumption, optimizing peak load management, and enhancing user comfort. The results demonstrate significant improvements in energy efficiency, cost savings, and overall system reliability compared to conventional manual control methods. The thesis concludes with a comprehensive discussion of the findings, highlighting the key contributions, limitations, and future research directions in the field of intelligent energy management for smart homes. The significance of the proposed system lies in its ability to adapt to changing user preferences, environmental conditions, and energy tariffs to achieve optimal energy utilization while ensuring user comfort and convenience. Overall, the Design and Implementation of an Intelligent Energy Management System for Smart Homes represents a significant advancement in the field of smart home automation and energy efficiency, with practical implications for sustainable living, reduced carbon footprint, and enhanced quality of life for residents.

Thesis Overview