Abstract
<jats:p>Aircraft Accident Forensics for Black Box Signal Decoding and Predictive Analytics presents a comprehensive exploration of modern aviation accident investigation through the integration of black box data analysis, digital forensics, artificial intelligence, and predictive analytics. The book examines the principles, technologies, and methodologies involved in recovering, processing, and interpreting Flight Data Recorder (FDR) and Cockpit Voice Recorder (CVR) information for accurate accident reconstruction and safety improvement. It covers aircraft investigation frameworks, flight data acquisition, signal processing, machine learning, deep learning, reinforcement learning, digital twins, IoT-based monitoring, and cloud-enabled aviation analytics. By combining traditional forensic approaches with advanced intelligent technologies, this book provides valuable insights into predictive fault detection, aircraft health monitoring, and proactive aviation safety management. It serves as a useful reference for aerospace engineers, aviation researchers, forensic investigators, AI professionals, and postgraduate students working in intelligent transportation and aviation safety systems.</jats:p>