Artificial Intelligence of Things (AIoT): Current and Future Trends brings together researchers and developers from a wide range of domains to share ideas on how to implement technical advances, create application areas for intelligent systems, and how to develop new services and smart devices connected to the Internet. Section One covers AIoT in Everything, providing a wide range of applications for AIoT methods and technologies. Section Two gives readers comprehensive guidance on AIoT in Societal Research and Development, with practical case studies of how AIoT is impacting cultures around the world. Section Three covers the impact of AIoT in educational settings.
The book also covers new capabilities such as pervasive sensing, multimedia sensing, machine learning, deep learning, and computing power. These new areas come with various requirements in terms of reliability, quality of service, and energy efficiency.
1. Cover image - p. i 2. Title page - p. ii 3. Table of Contents - p. iii 4. Copyright - p. iv 5. Dedication - p. iv 6. List of contributors - p. xvii 7. About the editors - p. xxi 8. Section I: AIoT in everything - p. 1 9. 1. Current developments and trends in video surveillance - p. 3 10. 2. Application of artificial intelligence in mobile networks: a survey - p. 15 11. 3. Metaverse technology in education: an enhancement for the future - p. 23 12. 4. Web-based brain tumor classification app using convolutional neural network - p. 37 13. 5. Traffic management system using different Internet of Things devices: literature review - p. 47 14. 6. Wireless sensor networks DV-Hop positioning based on artificial intelligence in the IoT era - p. 55 15. 7. Cassava leave disease image classification based on deep convolutional neural network - p. 65 16. 8. Cybersecurity using artificial intelligence - p. 73 17. 9. Transformers in wildfire detection - p. 83 18. 10. Distributed mobile cloud computing services and the internet of things - p. 93 19. 11. Internet of Things and mobile cloud computing service models - p. 105 20. Section II: AIoT in societal research and development - p. 119 21. 12. Beyond smart networking - p. 121 22. 13. The pros and cons of community-based tourism - p. 133 23. 14. Data compression approaches in WSN and IoT applications: a comprehensive survey - p. 139 24. 15. Utilizing Mamdani fuzzy inference system for automated hepatitis B and D diagnosis - p. 167 25. Section III: AIoT in education - p. 177 26. 16. Technologies used for visually impaired individuals in the museum environment: a systematic review - p. 179 27. 17. Integration of digital education into environmental education: raising environmental awareness through the media - p. 193 28. 18. The implications of technology integration in the classroom - p. 203 29. 19. How to improve the academic performance of Okaikrom Basic School with technology - p. 211 30. 20. Detection of plant leaf diseases using sequential convolutional neural network - p. 221 31. 21. Deepfakes development using long short-term memory-based deep neural networks - p. 229 32. 22. Deep learning−based histopathological image analysis for lung cancer diagnosis - p. 239 33. 23. Colon adenocarcinoma diagnosis on histopathological images using deep learning - p. 247 34. 24. Smart quality control of Industry 4.0 by artificial intelligence-powered robot vision, a review - p. 255 35. Index - p. 287
Artificial Intelligence of Things (AIoT): Current and Future Trends brings together researchers and developers from a wide range of domains to share ideas on how to implement technical advances, create application areas for intelligent systems, and how to develop new services and smart devices connected to the Internet. Section One covers AIoT in Everything, providing a wide range of applications for AIoT methods and technologies. Section Two gives readers comprehensive guidance on AIoT in Societal Research and Development, with practical case studies of how AIoT is impacting cultures around the world. Section Three covers the impact of AIoT in educational settings.
The book also covers new capabilities such as pervasive sensing, multimedia sensing, machine learning, deep learning, and computing power. These new areas come with various requirements in terms of reliability, quality of service, and energy efficiency.
1. Cover image - p. i 2. Title page - p. ii 3. Table of Contents - p. iii 4. Copyright - p. iv 5. Dedication - p. iv 6. List of contributors - p. xvii 7. About the editors - p. xxi 8. Section I: AIoT in everything - p. 1 9. 1. Current developments and trends in video surveillance - p. 3 10. 2. Application of artificial intelligence in mobile networks: a survey - p. 15 11. 3. Metaverse technology in education: an enhancement for the future - p. 23 12. 4. Web-based brain tumor classification app using convolutional neural network - p. 37 13. 5. Traffic management system using different Internet of Things devices: literature review - p. 47 14. 6. Wireless sensor networks DV-Hop positioning based on artificial intelligence in the IoT era - p. 55 15. 7. Cassava leave disease image classification based on deep convolutional neural network - p. 65 16. 8. Cybersecurity using artificial intelligence - p. 73 17. 9. Transformers in wildfire detection - p. 83 18. 10. Distributed mobile cloud computing services and the internet of things - p. 93 19. 11. Internet of Things and mobile cloud computing service models - p. 105 20. Section II: AIoT in societal research and development - p. 119 21. 12. Beyond smart networking - p. 121 22. 13. The pros and cons of community-based tourism - p. 133 23. 14. Data compression approaches in WSN and IoT applications: a comprehensive survey - p. 139 24. 15. Utilizing Mamdani fuzzy inference system for automated hepatitis B and D diagnosis - p. 167 25. Section III: AIoT in education - p. 177 26. 16. Technologies used for visually impaired individuals in the museum environment: a systematic review - p. 179 27. 17. Integration of digital education into environmental education: raising environmental awareness through the media - p. 193 28. 18. The implications of technology integration in the classroom - p. 203 29. 19. How to improve the academic performance of Okaikrom Basic School with technology - p. 211 30. 20. Detection of plant leaf diseases using sequential convolutional neural network - p. 221 31. 21. Deepfakes development using long short-term memory-based deep neural networks - p. 229 32. 22. Deep learning−based histopathological image analysis for lung cancer diagnosis - p. 239 33. 23. Colon adenocarcinoma diagnosis on histopathological images using deep learning - p. 247 34. 24. Smart quality control of Industry 4.0 by artificial intelligence-powered robot vision, a review - p. 255 35. Index - p. 287
