TY - BOOK
T1 - AI-Based Statistical Modeling for Road Traffic Surveillance and Monitoring
AU - Pandey, Jay Kumar
AU - Rai, Mritunjay
AU - Ahmad, Faizan
N1 - Publisher Copyright:
© 2025, Bentham Books imprint.
PY - 2025/1/1
Y1 - 2025/1/1
N2 - Positioned at the intersection of intelligent transportation systems (ITS), computer vision, and machine learning, this book presents a comprehensive examination of how artificial intelligence and statistical techniques are reshaping traffic monitoring, management, and urban mobility in the era of smart cities. The book begins with the core principles of AI and traffic systems, introducing statistical modeling, data acquisition, and image processing for traffic analysis. Midway, it transitions into deep learning-powered applications such as object detection, vehicle tracking, congestion forecasting, and real-time incident recognition. Later sections address legal, regulatory, and ethical frameworks, while concluding chapters highlight IoT-enabled models and future trajectories in AI-powered traffic management.
AB - Positioned at the intersection of intelligent transportation systems (ITS), computer vision, and machine learning, this book presents a comprehensive examination of how artificial intelligence and statistical techniques are reshaping traffic monitoring, management, and urban mobility in the era of smart cities. The book begins with the core principles of AI and traffic systems, introducing statistical modeling, data acquisition, and image processing for traffic analysis. Midway, it transitions into deep learning-powered applications such as object detection, vehicle tracking, congestion forecasting, and real-time incident recognition. Later sections address legal, regulatory, and ethical frameworks, while concluding chapters highlight IoT-enabled models and future trajectories in AI-powered traffic management.
KW - Demonstrates applications of deep learning in congestion prediction, incident detection, and vehicle tracking
KW - Evaluates security, data privacy, and legal considerations in AI-based traffic surveillance
KW - Examines AI-driven traffic optimization, urban mobility solutions, and self-driving technologies
KW - Highlights future directions and policy implications for sustainable and ethical traffic management
KW - Integrates AI with IoT frameworks for real-time monitoring in smart city infrastructure
KW - Introduces principles of AI, machine learning, and statistical modeling for traffic systems
UR - https://www.scopus.com/pages/publications/105025875991
U2 - 10.2174/97988988111121250101
DO - 10.2174/97988988111121250101
M3 - Book
AN - SCOPUS:105025875991
SN - 9798898811112
BT - AI-Based Statistical Modeling for Road Traffic Surveillance and Monitoring
PB - Bentham Science Publishers
ER -
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