The book emphasizes the predictive models of Big Data, Genetic
Algorithm, and IoT with a case study. The book illustrates the
predictive models with integrated fuel consumption models for smart and
safe traveling. The text is a coordinated amalgamation of research
contributions and industrial applications in the field of Intelligent
Transportation Systems. The advanced predictive models and research
results were achieved with the case studies, deployed in real
transportation environments.
Features:
- Provides a smart traffic congestion avoidance system with an
integrated fuel consumption model.
- Predicts traffic in short-term and regular. This is illustrated with a
case study.
- Efficient Traffic light controller and deviation system in accordance
with the traffic scenario.
- IoT based Intelligent Transport Systems in a Global perspective.
- Intelligent Traffic Light Control System and Ambulance Control System.
- Provides a predictive framework that can handle the traffic on
abnormal days, such as weekends, festival holidays.
- Bunch of solutions and ideas for smart traffic development in smart
cities.
- This book focuses on advanced predictive models along with offering an
efficient solution for smart traffic management system.
- This book will give a brief idea of the available
algorithms/techniques of big data, IoT, and genetic algorithm and
guides in developing a solution for smart city applications.
- This book will be a complete framework for ITS domain with the
advanced concepts of Big Data Analytics, Genetic Algorithm and IoT.
This book is primarily aimed at IT professionals. Undergraduates,
graduates and researchers in the area of computer science and
information technology will also find this book useful.
