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R.Sathiyaraj,A. Bharathi,B. Balamurugan

Advanced Intelligent Predictive Models for Urban Transportation

Advanced Intelligent Predictive Models for Urban Transportation

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The book focuses on advanced predictive models and research results in the field of Intelligent Transportation Systems, with case studies illustrating their applications in smart traffic management. It covers topics such as Big Data, Genetic Algorithm, IoT, and their integration with fuel consumption models for smart and safe traveling. The book is aimed at IT professionals and students in the computer science and information technology fields.

Format: Hardback
Length: 132 pages
Publication date: 28 March 2022
Publisher: Taylor & Francis Ltd


The book delves into the realm of predictive models, encompassing Big Data, Genetic Algorithm, and IoT, through a comprehensive case study. It vividly showcases these models by integrating fuel consumption models for smart and safe traveling. This text serves as a harmonious blend of scholarly research contributions and practical applications in the field of Intelligent Transportation Systems. Through meticulous case studies, advanced predictive models and groundbreaking research outcomes have been achieved, successfully deployed in real transportation environments.

Key Features:
1. Offers a cutting-edge smart traffic congestion avoidance system equipped with an integrated fuel consumption model.
2. Predicts traffic in both short-term and regular intervals, exemplified through a case study.
3. Implements an efficient Traffic light controller and deviation system tailored to the prevailing traffic scenario.
4. Embraces IoT-based Intelligent Transport Systems on a global scale.
5. Develops an intelligent Traffic Light Control System and Ambulance Control System utilizing IoT technologies.
6. Provides a predictive framework capable of handling traffic on abnormal days, such as weekends and festival holidays.
7. Offers a plethora of solutions and ideas for fostering smart traffic development within smart cities.
8. Focuses on advanced predictive models while providing an efficient solution for smart traffic management systems.
9. Offers a concise introduction to the available algorithms/techniques of Big Data, IoT, and Genetic Algorithm, guiding the development of solutions for smart city applications.
10. Serves as a comprehensive framework for the ITS domain, encompassing advanced concepts of Big Data Analytics, Genetic Algorithm, and IoT.
11. Primarily intended for IT professionals, this book also caters to undergraduates, graduates, and researchers in the domains of computer science and information technology.

Weight: 453g
Dimension: 254 x 178 (mm)
ISBN-13: 9781032108513

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