Internet of Multimedia Things (IoMT): Techniques and Applications disseminates research efforts in the security and resilience of intelligent data-centric critical systems to support advanced research in this area. Sections cover the background of IoMT Architectures and Technologies, describe the problems that arise in IoMT Computing and protocols, and illustrate the application of IoMT on Industrial applications. The book will be beneficial for engineers, developers, solution designers, architects, system engineers and specialists from professional environments interested in the IoMT to seek appropriate solutions to their specific problems.
1. Internet of Multimedia Things (IoMT) - p. Page i 2. Cover - p. Page i 3. Front Matter - p. Page i 4. Table of Contents - p. Page iii 5. Copyright - p. Page iii 6. Contents - p. Page v 7. Contributors - p. Page v 8. List of Illustrations - p. Page viii 9. List of Tables - p. Page ix 10. Chapter 1 : A review on Internet of Multimedia Things (IoMT) routing protocols and quality of service - p. Page ix 11. Chapter 2 : Energy efficient data communication in Internet of Multimedia Things (IoMT) - p. Page 27 12. Chapter 3 : Visual information processing and transmission in Wireless Multimedia Sensor Networks: a deep learning based practical approach - p. Page 44 13. Chapter 4 : Cognitive radio-medium access control protocol for Internet of Multimedia Things (IoMT) - p. Page 60 14. Chapter 5 : Multimedia nano communication for healthcare – noise analysis - p. Page 95 15. Chapter 6 : The use of deep learning in image analysis for the study of oncology - p. Page 130 16. Chapter 7 : Automatic analysis of the heart sound signal to build smart healthcare system - p. Page 148 17. Chapter 8 : Efficient single image haze removal using CLAHE and Dark Channel Prior for Internet of Multimedia Things - p. Page 182 18. Chapter 9 : A supervised and unsupervised image quality assessment framework in real-time☆ - p. Page 200 19. Chapter 10 : A computational approach to understand building floor plan images using machine learning techniques - p. Page 229 20. Index - p. Page 256
Internet of Multimedia Things (IoMT): Techniques and Applications disseminates research efforts in the security and resilience of intelligent data-centric critical systems to support advanced research in this area. Sections cover the background of IoMT Architectures and Technologies, describe the problems that arise in IoMT Computing and protocols, and illustrate the application of IoMT on Industrial applications. The book will be beneficial for engineers, developers, solution designers, architects, system engineers and specialists from professional environments interested in the IoMT to seek appropriate solutions to their specific problems.
1. Internet of Multimedia Things (IoMT) - p. Page i 2. Cover - p. Page i 3. Front Matter - p. Page i 4. Table of Contents - p. Page iii 5. Copyright - p. Page iii 6. Contents - p. Page v 7. Contributors - p. Page v 8. List of Illustrations - p. Page viii 9. List of Tables - p. Page ix 10. Chapter 1 : A review on Internet of Multimedia Things (IoMT) routing protocols and quality of service - p. Page ix 11. Chapter 2 : Energy efficient data communication in Internet of Multimedia Things (IoMT) - p. Page 27 12. Chapter 3 : Visual information processing and transmission in Wireless Multimedia Sensor Networks: a deep learning based practical approach - p. Page 44 13. Chapter 4 : Cognitive radio-medium access control protocol for Internet of Multimedia Things (IoMT) - p. Page 60 14. Chapter 5 : Multimedia nano communication for healthcare – noise analysis - p. Page 95 15. Chapter 6 : The use of deep learning in image analysis for the study of oncology - p. Page 130 16. Chapter 7 : Automatic analysis of the heart sound signal to build smart healthcare system - p. Page 148 17. Chapter 8 : Efficient single image haze removal using CLAHE and Dark Channel Prior for Internet of Multimedia Things - p. Page 182 18. Chapter 9 : A supervised and unsupervised image quality assessment framework in real-time☆ - p. Page 200 19. Chapter 10 : A computational approach to understand building floor plan images using machine learning techniques - p. Page 229 20. Index - p. Page 256
