Thesis Abstract

**Abstract
** The rapid urbanization and technological advancements in smart cities have led to the need for efficient and sustainable solutions to enhance urban living. One critical aspect of urban infrastructure is street lighting, which plays a crucial role in ensuring safety and security for citizens. Traditional street lighting systems are often inefficient and costly to maintain. Therefore, there is a growing interest in implementing intelligent street lighting systems using Internet of Things (IoT) technology to improve energy efficiency, reduce maintenance costs, and enhance overall functionality. This thesis focuses on the design and implementation of an intelligent street lighting system using IoT technology in smart cities. The research aims to address the limitations of traditional street lighting systems by leveraging IoT to create a more efficient, automated, and data-driven solution. The proposed system will incorporate sensors, actuators, and communication devices to monitor and control street lights based on real-time data and environmental conditions. Additionally, advanced analytics and machine learning algorithms will be utilized to optimize energy consumption and enhance system performance. The thesis begins with an introduction that provides an overview of the research problem, objectives, scope, significance, and structure of the thesis. The background of the study highlights the importance of smart cities and the role of IoT in urban infrastructure development. The problem statement identifies the shortcomings of traditional street lighting systems and the need for intelligent solutions. The objectives of the study outline the specific goals and outcomes that the research intends to achieve. The literature review chapter explores existing research and developments in intelligent street lighting systems, IoT technology, and smart city initiatives. The chapter provides a comprehensive analysis of the current state-of-the-art technologies, trends, and challenges in the field, laying the foundation for the proposed system design. The research methodology chapter outlines the approach and methodology used to design, implement, and evaluate the intelligent street lighting system. It includes details on the system architecture, hardware components, software development, data collection methods, simulation techniques, and evaluation criteria. The discussion of findings chapter presents the results and analysis of the intelligent street lighting system implementation. It includes performance metrics, energy savings, system reliability, user feedback, and potential future enhancements. The chapter also discusses the implications of the findings and their contribution to the field of smart city infrastructure. In conclusion, the thesis summarizes the key findings, highlights the significance of the research, and outlines recommendations for future work. The proposed intelligent street lighting system demonstrates the potential to transform urban lighting infrastructure, improve energy efficiency, reduce operational costs, and enhance the overall quality of life in smart cities. Keywords Intelligent street lighting system, Internet of Things (IoT), smart cities, energy efficiency, urban infrastructure, sensor networks, machine learning, sustainability.

Thesis Overview