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ABOUT THE BOOK

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.