Thesis Abstract

Abstract
The increasing demand for energy conservation and sustainable practices in residential buildings has led to a growing interest in the development of smart energy management systems. This thesis presents the design and implementation of a smart energy management system tailored for residential buildings, with the aim of optimizing energy usage, reducing costs, and minimizing environmental impact. The system incorporates advanced technologies such as Internet of Things (IoT), artificial intelligence, and data analytics to monitor, control, and optimize energy consumption in real-time. The research begins with a comprehensive literature review that explores existing energy management systems, smart technologies, and their applications in residential settings. The methodology chapter outlines the research approach, data collection methods, system design process, and implementation strategy. The system design includes the selection of sensors, communication protocols, data processing algorithms, and user interface features to ensure efficient and user-friendly operation. Through field testing and data analysis, the smart energy management system demonstrated significant improvements in energy efficiency, cost savings, and user convenience. The findings chapter presents detailed results and discussions on energy consumption patterns, system performance, user feedback, and future enhancements. The conclusion highlights the success of the system in achieving its objectives and addresses potential challenges and opportunities for further research and development. Overall, this thesis contributes to the advancement of smart energy management technologies in residential buildings, providing a practical solution for homeowners to monitor and optimize their energy consumption effectively. The implementation of such systems can lead to tangible benefits in terms of energy savings, reduced environmental impact, and improved quality of life for residents.

Thesis Overview