Internet of Things and Artificial Intelligence in Transportation Revolution

The advent of Internet of Things offers a scalable and seamless connection of physical objects, including human beings and devices. This, along with artificial intelligence, has moved transportation towards becoming intelligent transportation. This book is a collection of eleven articles that have s...

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Year of Publication:2021
Language:English
Physical Description:1 electronic resource (232 p.)
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520 |a The advent of Internet of Things offers a scalable and seamless connection of physical objects, including human beings and devices. This, along with artificial intelligence, has moved transportation towards becoming intelligent transportation. This book is a collection of eleven articles that have served as examples of the success of internet of things and artificial intelligence deployment in transportation research. Topics include collision avoidance for surface ships, indoor localization, vehicle authentication, traffic signal control, path-planning of unmanned ships, driver drowsiness and stress detection, vehicle density estimation, maritime vessel flow forecast, and vehicle license plate recognition. High-performance computing services have become more affordable in recent years, which triggered the adoption of deep-learning-based approaches to increase the performance standards of artificial intelligence models. Nevertheless, it has been pointed out by various researchers that traditional shallow-learning-based approaches usually have an advantage in applications with small datasets. The book can provide information to government officials, researchers, and practitioners. In each article, the authors have summarized the limitations of existing works and offered valuable information on future research directions. 
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653 |a decision-making 
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653 |a collision avoidance 
653 |a scene division 
653 |a deep reinforcement learning 
653 |a maritime autonomous surface ships 
653 |a internet of things 
653 |a crowdsourcing 
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653 |a driver drowsiness 
653 |a driver stress 
653 |a multi-objective genetic algorithm 
653 |a multiple kernel learning 
653 |a urban freeway 
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653 |a unknown inputs observer 
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653 |a deep learning 
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653 |a histogram of oriented gradients 
653 |a artificial neural networks 
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653 |a time-frequency 
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653 |a road anomalies 
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700 1 |a Chui, Kwok Tai  |4 edt 
700 1 |a Liu, Ryan Wen  |4 edt 
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700 1 |a Chui, Kwok Tai  |4 oth 
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