Thesis Abstract

Abstract
This thesis presents a comprehensive study on the development and implementation of a Smart Energy Management System (SEMS) for residential buildings. The increasing demand for energy efficiency and sustainability in the built environment has led to the need for innovative solutions to optimize energy consumption and reduce carbon emissions. The SEMS proposed in this study aims to address these challenges by utilizing advanced technologies such as Internet of Things (IoT), artificial intelligence, and data analytics to monitor, control, and optimize energy usage in residential buildings. The research begins with an introduction to the concept of smart energy management and its significance in the context of residential buildings. The background of the study highlights the current state of energy consumption in buildings and the need for more intelligent and efficient systems. The problem statement identifies the key challenges and limitations faced in existing energy management practices, emphasizing the need for a smarter and more integrated approach. The objectives of the study include the design and development of a SEMS prototype that can effectively monitor energy usage, identify patterns and trends, and provide actionable insights for energy optimization. The scope of the study covers the implementation of the SEMS in a real-world residential building setting, enabling data collection, analysis, and performance evaluation. A comprehensive literature review is conducted to explore existing research and technologies related to smart energy management systems, IoT applications in buildings, energy monitoring and control systems, and data analytics for energy optimization. The review establishes the theoretical framework for the development of the SEMS and provides insights into best practices and successful case studies. The research methodology section outlines the approach taken to design, develop, and test the SEMS prototype. It includes details on the system architecture, sensor deployment, data collection methods, and algorithm development for energy optimization. The methodology also covers the evaluation criteria and performance metrics used to assess the effectiveness of the SEMS in achieving energy efficiency goals. The discussion of findings chapter presents the results of the SEMS implementation in a residential building, including energy consumption patterns, system performance, user feedback, and energy savings achieved. The analysis highlights the benefits of the SEMS in optimizing energy usage, reducing costs, and enhancing user comfort and convenience. In conclusion, the study demonstrates the feasibility and effectiveness of a Smart Energy Management System for residential buildings in improving energy efficiency and sustainability. The SEMS prototype offers a practical and scalable solution for homeowners, building managers, and policymakers to achieve energy savings and environmental benefits. The research contributes to the growing field of smart building technologies and provides valuable insights for future research and development in this area.

Thesis Overview