Smart Urban Computing Applications

This edited book is a collection of quality research articles reporting research advances in the area of deep learning, IoT and urban computing. It describes new insights based on deep learning and IoT for urban computing and is useful for architects, engineers, policymakers, facility managers, academicians, and researchers who are interested in expanding their knowledge of the applications of deep learning trends involving urban computing.

Table of Contents:
1. Requirements Analysis of Data Analytics Software Within the Scope of a Smart University 2. Performance Analysis of Deep Learning Models for Reidentification of a Person in Public Surveillance Systems 3. Crash Recovery and Accident Prediction Using an IoT Based Black Box System 4. Exploiting Trajectory Data to Improve Smart City Services 5. An End–End Framework for Autonomous Driving Cars in a CARLA Simulator 6. IoT and Artificial Intelligence Techniques for Public Safety and Security 7. Deep Learning Approaches for the Classification of IoT Based Hyperspectral Images 8. Artificial Intelligence and IoT for a Smart City 9. Intelligent Facility Management System for Self-sustainable Homes in Smart Cities: An Integrated Approach 10. Low-cost Embedded System for The Monitoring Of Environmental Pollution 11. Case Study on Urban Computing with AI and IOT 12. Emerging Technology for Smart Living

About the Author :
M.A. Jabbar is a Professor and Head of the Department AI&ML, Vardhaman College of Engineering, Hyderabad and Telangana, India. He obtained his Doctor of Philosophy (PhD) from JNTUH, Hyderabad and Telangana, India. He has been teaching for more than 20 years. His research interests include artificial intelligence, big data analytics, bio-informatics, cyber security, machine learning, attack graphs, and intrusion detection systems. He has published more than 57 papers in various journals and conferences. He has served as a technical committee member for more than 70 international conferences, and has edited 5 books with various leading publishers. He is a senior Member of IEEE and Senior member of ACM, Governing body member, Internet Society India Hyderabad Chapter. Presently he is acting as a Chair, IEEE CS chapter, Hyderabad Section. Sanju Tiwari is a Senior Researcher at Universidad Autonoma de Tamaulipas (70-year-old University), Mexico. She is a DAAD Post-Doc-Net AI Fellow for 2021. She is an Adjunct Professor at Vardhman Engineering College, Hyderabad in the Computer Science department. She has also been appointed as PhD co-supervisor at Rai University, Gujarat, India. She is a senior member of IEEE as a SMIEEE. She has worked as a Post-Doctoral Researcher in the Ontology Engineering Group, Universidad Polytecnica De Madrid, Spain. Prior to this, she worked as a Research Associate for a sponsored research project "Intelligent Real-time Situation Awareness and Decision Support System for Indian Defence" funded by DRDO, New Delhi in the Department of Computer Applications, National Institute of Technology, Kurukshetra. In this project, she has developed and evaluated a Decision Support System for Indian Defence. Her current research interests include ontology engineering, knowledge graphs, linked data generation and publication, semantic web, reasoning with SPARQL, and machine intelligence. Fernando Ortiz-Rodriguez is a full professor at Tamaulipas Autonomous University, Member of National Research Council level C, and director of the Social Research Centre at UAT, Mexico. He is a member of the Information Technology research group and part of the Knowledge Graph and Semantic Web Community. He has published, journal articles, book chapters, and has acted as a book editor for reputed editorials. He has also presented many conference articles in Europe, the United States, and Mexico and is the main chair and organizer of the KGSWC multiseries conference.