There’s no denying that CI is on its way to change the world as we know it. There are various social domains such as Environment, Education, Information Security, Healthcare, Crisis Response, Human Behavior and Bias, Disaster Management, Industrial management and most recently Epidemics and Outbreaks are highly in need of Intelligent Technologies to address their issues. This book presents the views on how Computational Intelligent and ICT technologies can be applied to ease or solve social problems by sharing examples of research results from studies of social anxiety, environmental issues, mobility of the disabled, and problems in social safety. As with most changes in life, there will be positive and negative impacts on society as artificial intelligence continues to transform the world, we live in. With the idea of future scope in research, the book focuses on the challenges that might be faced (and we should be thinking about how to address them now) as well as several of the positive impacts artificial intelligence will have on society.
1. Cover image - p. i 2. Table of Contents - p. iii 3. Copyright - p. iii 4. Contributors - p. iii 5. Preface - p. xiii 6. Chapter One: Why is implementing computational intelligence for social good so challenging? Principles and its application - p. 1 7. Chapter Two: Smart crisis management system for road accidents based on Modified Convolutional Neural Networks–Particle Swarm Optimization hybrid algorithm - p. 19 8. Chapter Three: Residential energy management system (REMS) using machine learning - p. 33 9. Chapter Four: Text-based personality prediction using XLNet - p. 49 10. Chapter Five: Articulating the power of reasoning and gathering data for information security and justice - p. 67 11. Chapter Six: Bayesian network-based quality assessment of blockchain smart contracts - p. 96 12. Chapter Seven: Short-term wind power prediction using deep learning approaches - p. 111 13. Chapter Eight: Cyber data trend and intelligent computing - p. 146 14. Chapter Nine: Reshaping agriculture using intelligent edge computing - p. 167 15. Chapter Ten: An automatic path navigation for visually challenged people using deep Q learning - p. 205 16. Chapter Eleven: Delineating computational intelligence during epidemic emergencies and outbreaks - p. 219 17. Chapter Twelve: ClubNet: Deep learning model for computation, calibration and estimation of biotic stress in crops - p. 235 18. Chapter Thirteen: Automatic programming (source code generator) based on an ontological model - p. 251
There’s no denying that CI is on its way to change the world as we know it. There are various social domains such as Environment, Education, Information Security, Healthcare, Crisis Response, Human Behavior and Bias, Disaster Management, Industrial management and most recently Epidemics and Outbreaks are highly in need of Intelligent Technologies to address their issues. This book presents the views on how Computational Intelligent and ICT technologies can be applied to ease or solve social problems by sharing examples of research results from studies of social anxiety, environmental issues, mobility of the disabled, and problems in social safety. As with most changes in life, there will be positive and negative impacts on society as artificial intelligence continues to transform the world, we live in. With the idea of future scope in research, the book focuses on the challenges that might be faced (and we should be thinking about how to address them now) as well as several of the positive impacts artificial intelligence will have on society.
1. Cover image - p. i 2. Table of Contents - p. iii 3. Copyright - p. iii 4. Contributors - p. iii 5. Preface - p. xiii 6. Chapter One: Why is implementing computational intelligence for social good so challenging? Principles and its application - p. 1 7. Chapter Two: Smart crisis management system for road accidents based on Modified Convolutional Neural Networks–Particle Swarm Optimization hybrid algorithm - p. 19 8. Chapter Three: Residential energy management system (REMS) using machine learning - p. 33 9. Chapter Four: Text-based personality prediction using XLNet - p. 49 10. Chapter Five: Articulating the power of reasoning and gathering data for information security and justice - p. 67 11. Chapter Six: Bayesian network-based quality assessment of blockchain smart contracts - p. 96 12. Chapter Seven: Short-term wind power prediction using deep learning approaches - p. 111 13. Chapter Eight: Cyber data trend and intelligent computing - p. 146 14. Chapter Nine: Reshaping agriculture using intelligent edge computing - p. 167 15. Chapter Ten: An automatic path navigation for visually challenged people using deep Q learning - p. 205 16. Chapter Eleven: Delineating computational intelligence during epidemic emergencies and outbreaks - p. 219 17. Chapter Twelve: ClubNet: Deep learning model for computation, calibration and estimation of biotic stress in crops - p. 235 18. Chapter Thirteen: Automatic programming (source code generator) based on an ontological model - p. 251
