Machine Learning Techniques for Smart City Applications: Trends and Solutions

This book discusses the application of different machine learning techniques to the sub-concepts of smart cities such as smart energy, transportation, waste management, health, infrastructure, etc. The focus of this book is to come up with innovative solutions in the above-mentioned issues with the purpose of alleviating the pressing needs of human society. This book includes content with practical examples which are easy to understand for readers. It also covers a multi-disciplinary field and, consequently, it benefits a wide readership including academics, researchers, and practitioners.

Presents an in-depth coverage on different variety of applications related with smart cities Maximizes reader's insights about the role of machine learning in different applications of smart cities Includes contents with set-up/protocols/procedural flow necessary for research and practical implementations

Autorentext
Dr. D. Jude Hemanth received his B.E degree in ECE from Bharathiar University in 2002, M.E degree in communication systems from Anna University in 2006, and Ph.D. from Karunya University in 2013. His research areas include computational intelligence and image processing. He has authored more than 140 research papers in reputed SCIE indexed International Journals and Scopus Indexed International Conferences. His cumulative impact factor is more than 200. He has published 33 edited books with reputable publishers such as Elsevier, Springer, and IET. Currently, he works as Associate Professor in Department of ECE, Karunya University, Coimbatore, India.

Inhalt

Applying Deep Learning to Predict Civic Purpose Development: Within the Smart City Context.- Convolution Neural Network Scheme for Detection of Electricity Theft in Smart Grids.- Helping Hand: A GMM Based Real time Assistive Device for Disabled Using Hand Gestures.- A Review on Hand Gesture and Sign Language Techniques for Hearing Impaired Person.- DriveSense: Adaptive System for Driving Behaviour Analysis and Ranking.- Classification and Tracking of Vehicles Using Videos Captured by Unmanned Aerial Vehicles.- Tracking Everyone and Everything in Smart Cities with an ANN Driven Smart Antenna.- Wavelet based Saliency and Ensemble Classifier for Pedestrian Detection in Infrared Images.- A Survey of Emerging Applications of Machine Learning in the Diagnosis and Management of Sleep Hygiene and Health in the Elderly Population.- Smart City Traffic Patterns Prediction Using Machine Learning.