The Cognitive Approach in Cloud Computing and Internet of Things Technologies for Surveillance Tracking Systems discusses the recent, rapid development of Internet of things (IoT) and its focus on research in smart cities, especially on surveillance tracking systems in which computing devices are widely distributed and huge amounts of dynamic real-time data are collected and processed. Efficient surveillance tracking systems in the Big Data era require the capability of quickly abstracting useful information from the increasing amounts of data. Real-time information fusion is imperative and part of the challenge to mission critical surveillance tasks for various applications.
This book presents all of these concepts, with a goal of creating automated IT systems that are capable of resolving problems without demanding human aid.
1. 2.1 Introduction - p. 17 2. 2.2 Preliminaries - p. 19 3. 2.3 Security Model - p. 20 4. 2.4 Provably Secure Identity-Based Authenticated Key Agreement Protocol for V2V Communications - p. 23 5. 2.5 Security Analysis - p. 24 6. 2.6 Analysis of Dang et al.’s Identity-Based Authenticated Key Agreement Protocol - p. 29 7. 2.7 Efficiency Analysis - p. 31 8. 2.8 Conclusion - p. 33 9. Acknowledgment - p. 34 10. References - p. 34 11. Chapter 3. Dynamic Self-Aware Task Assignment Algorithm for an Internet of Things-Based Wireless Surveillance System - p. 37 12. Chapter 4. Smart Vehicle Monitoring and Tracking System Powered by Active Radio Frequency Identification and Internet of Things - p. 51 13. Chapter 5. An Efficient Framework for Object Tracking in Video Surveillance - p. 65 14. Chapter 6. Development of Efficient Swarm Intelligence Algorithm for Simulating Two-Dimensional Orthomosaic for Terrain Mapping Using Cooperative Unmanned Aerial Vehicles - p. 75 15. Chapter 7. Trends of Sound Event Recognition in Audio Surveillance: A Recent Review and Study - p. 95 16. Chapter 8. Object Classification of Remote Sensing Image Using Deep Convolutional Neural Network - p. 107 17. Chapter 9. Compressive Sensing-Aided Collision Avoidance System - p. 121 18. Chapter 10. Review of Intellectual Video Surveillance Through Internet of Things - p. 141 19. Chapter 11. Violence Detection in Automated Video Surveillance: Recent Trends and Comparative Studies - p. 157 20. Chapter 12. FPGA-Based Detection and Tracking System for Surveillance Camera - p. 173 21. Index - p. 181
The Cognitive Approach in Cloud Computing and Internet of Things Technologies for Surveillance Tracking Systems discusses the recent, rapid development of Internet of things (IoT) and its focus on research in smart cities, especially on surveillance tracking systems in which computing devices are widely distributed and huge amounts of dynamic real-time data are collected and processed. Efficient surveillance tracking systems in the Big Data era require the capability of quickly abstracting useful information from the increasing amounts of data. Real-time information fusion is imperative and part of the challenge to mission critical surveillance tasks for various applications.
This book presents all of these concepts, with a goal of creating automated IT systems that are capable of resolving problems without demanding human aid.
1. 2.1 Introduction - p. 17 2. 2.2 Preliminaries - p. 19 3. 2.3 Security Model - p. 20 4. 2.4 Provably Secure Identity-Based Authenticated Key Agreement Protocol for V2V Communications - p. 23 5. 2.5 Security Analysis - p. 24 6. 2.6 Analysis of Dang et al.’s Identity-Based Authenticated Key Agreement Protocol - p. 29 7. 2.7 Efficiency Analysis - p. 31 8. 2.8 Conclusion - p. 33 9. Acknowledgment - p. 34 10. References - p. 34 11. Chapter 3. Dynamic Self-Aware Task Assignment Algorithm for an Internet of Things-Based Wireless Surveillance System - p. 37 12. Chapter 4. Smart Vehicle Monitoring and Tracking System Powered by Active Radio Frequency Identification and Internet of Things - p. 51 13. Chapter 5. An Efficient Framework for Object Tracking in Video Surveillance - p. 65 14. Chapter 6. Development of Efficient Swarm Intelligence Algorithm for Simulating Two-Dimensional Orthomosaic for Terrain Mapping Using Cooperative Unmanned Aerial Vehicles - p. 75 15. Chapter 7. Trends of Sound Event Recognition in Audio Surveillance: A Recent Review and Study - p. 95 16. Chapter 8. Object Classification of Remote Sensing Image Using Deep Convolutional Neural Network - p. 107 17. Chapter 9. Compressive Sensing-Aided Collision Avoidance System - p. 121 18. Chapter 10. Review of Intellectual Video Surveillance Through Internet of Things - p. 141 19. Chapter 11. Violence Detection in Automated Video Surveillance: Recent Trends and Comparative Studies - p. 157 20. Chapter 12. FPGA-Based Detection and Tracking System for Surveillance Camera - p. 173 21. Index - p. 181
