Project Abstract

Abstract
The implementation of an Automated Energy Management System (AEMS) in smart buildings has gained significant attention in recent years due to the increasing demand for energy efficiency and sustainability. This research project aims to design, develop, and evaluate an AEMS for optimizing energy usage in smart buildings. The system will utilize advanced technologies such as Internet of Things (IoT), artificial intelligence, and data analytics to monitor, control, and optimize energy consumption within the building environment. The research will begin with a comprehensive introduction to the concept of smart buildings and the need for effective energy management systems. The background of the study will explore the current state of energy management in buildings and highlight the limitations of existing systems in achieving optimal energy efficiency. The problem statement will identify the challenges faced in traditional energy management practices and emphasize the importance of implementing automated solutions to address these challenges. The objectives of the study include designing an AEMS that can monitor energy consumption patterns in real-time, optimizing energy usage based on occupancy and environmental conditions, and providing actionable insights for building managers to make informed decisions regarding energy efficiency. The limitations of the study will be acknowledged, including potential constraints in data availability, technology integration, and system scalability. The scope of the study will focus on the development and implementation of the AEMS in a simulated smart building environment, utilizing a combination of sensors, actuators, and control algorithms to manage energy consumption effectively. The significance of the study lies in its potential to reduce energy costs, minimize environmental impact, and enhance overall building performance through intelligent energy management practices. The structure of the research will be outlined, detailing the organization of the subsequent chapters, including a literature review that discusses relevant studies and technologies related to energy management in smart buildings. The research methodology will describe the approach and methods used to design, implement, and evaluate the AEMS, including data collection, analysis, and validation procedures. The discussion of findings will present the results of the AEMS implementation, highlighting its effectiveness in optimizing energy consumption, reducing costs, and improving building sustainability. The conclusions drawn from the research will summarize the key insights, implications, and recommendations for future research and practical applications of automated energy management systems in smart buildings. In conclusion, this research project aims to contribute to the advancement of energy-efficient practices in smart buildings through the development of an innovative Automated Energy Management System. By leveraging cutting-edge technologies and data-driven approaches, the AEMS has the potential to revolutionize energy management practices, leading to significant improvements in building sustainability, operational efficiency, and environmental conservation.

Project Overview