Rail Safety explores the integration of sensor technology and AI in modern railway systems to enhance both safety and efficiency. It argues that a strategic approach to these technologies, combined with a deep understanding of railway operations, is key to improving overall system performance. The book uniquely addresses predictive maintenance, automated threat detection, and real-time operational optimization using sensors and AI, vital for reducing downtime and enhancing safety records.
The book begins by introducing fundamental concepts and transitions into the core areas of predictive maintenance, automated threat detection, and real-time operational optimization. For example, AI can identify potential equipment failures before they occur, enabling proactive maintenance. Case studies, experimental data, and expert interviews support the book's argument, highlighting both the benefits and limitations of AI in railways. This approach provides a balanced view, emphasizing the importance of human oversight and ethical considerations.
Rail Safety is valuable for railway engineers, policymakers, and technologists seeking to modernize and sustainably advance the railway sector, including addressing ongoing debates around automation and cybersecurity.
