Description
With the ever-increasing use of AI technologies, ethical considerations take on greater importance. Human-centric AI emphasizes transparency, making sure that AI systems work in a way that users can comprehend and trust. Additionally, it addresses bias and discrimination issues, ensuring fairness and inclusion in the design and implementation of AI apps. By emphasizing user experience, security, and human-centric AI, the goal is to improve collaboration between people and machines, rather than replacing human decisions, creating a future where technology is a force for good, benefiting both businesses and society. Written from a technological point of view, Industry 5.0 for Society 5.0 explores the impact of cutting-edge technologies, including the Internet of Things, cloud, artificial intelligence, and digital twin, on individuals and community, and considers how they can be used to solve societal problems. The book considers how these technologies can positively affect industry, healthcare, agriculture, design and manufacture, contributing to the development of a sustainable environment that ultimately creates a positive and mutually beneficial relationship between people and AI. - Presents the fundamentals, challenges and advancements in AI required for Industry 5.0 to be beneficial to society - Focuses on human-centric AI and how it can be used to create more sustainable industry - Explores the ethical considerations and regulatory aspects of Edge AI, helping readers navigate the responsible use of this technology
Table of Contents
ContentsContributors xiiiForeword xvPreface xviiPart ITransformation towards Industry 5.01. Transitioning from traditional artificial intelligence to emerging trends: Exploring paradigm shifts, challenges, and opportunitiesAnamika Anu, Jagrati Nagdiya and Sheril Thomas1.1. Introduction1.2. Paradigm shifts1.3. Technology1.4. Computational power1.5. Cognitive understanding1.6. Traditional artificial intelligence approaches1.7. Limitations of early artificial intelligence systems1.8. Emerging trends in artificial intelligence1.9. Artificial intelligence-powered solutions1.10. Challenges and ethical considerations1.11. Data privacy, security, and interpretability1.12. Challenges and opportunities in the transition1.13. ConclusionReferences2. Human-machine collaboration in Industry 5.0 using Big Data analyticsSamiksha Khule, Muskan Sihare, Rakhi Arora, Nitin Dixit, Gaurav Dubey and Yogesh Kumar Sharma2.1. Introduction2.2. Technologies of Industry 5.02.3. Creative applications of Industry 5.02.4. The role of vision transformers in industry 4.0 and Industry 5.02.5. Principles of Industry 5.02.6. Literature review2.7. Challenges in Industry 5.02.8. Limitations in Industry 5.02.9. ConclusionReferences3. Implications of Industry 5.0 for Society 5.0: A systematic literature reviewGanesh Narkhede, Gajanan Ghuge and Madahavi Mohite3.1. Introduction3.2. Literature review3.3. Results and discussion3.4. ConclusionReferences4. Cloud security through robust cryptographic measures: Overview, advances, and applicationRadha Nishant Deoghare, Prachi Nishant Shah-Bahekar, Shradha Nishant Tawade and Sapana Nishant Kolambe4.1. Introduction4.2. Related Work4.3. Proposed Approach4.4. Result Analysis4.5. ConclusionReferences5. Mesocaps: Enhancing deepfake detection 1Umesh Pranjal Shirsat, Shivani Joshi, Siddhi Shinde, Vaibhav Garje, Amit Joshi and Suraj Sawant5.1. Introduction5.2. Literature review5.3. Deepfake generation5.4. Deepfake detection5.5. Gap analysis5.6. Methodology5.7. Model architecture5.8. MesoNet5.9. Capsule network5.10. Results and discussion5.11. Experimental setup5.12. Performance metrics and comparison5.13. Conclusion and future scopeReferencesPart IITransformation in Healthcare 5.06. Digital health evaluation: A roadmap aheadPranali Chavhan, Namrata Kharate, Prashant Anerao and Gajanan Chavhan6.1. Introduction6.2. Current Approaches to Digital Health Evaluation6.3. A Roadmap for Future Evaluation6.4. Case Studies6.5. Digital Health: Barrier and Solution6.6. ConclusionReferences7. Adapting online medical services for the well-being diverse patientsJyoti Deshmukh, Vijay Rathod, Nilesh Sable and Gitanjali Shinde7.1. Introduction7.2. Telemedicine Strategy Implementation in 2019 During the COVID-19 Era7.3. Technological Solutions for Telemedicine7.4. Related Information7.5. COVID-19 Pandemic: The Remote Medication Network for Neurorehabilitation7.6. ConclusionReferences8. Revolutionizing healthcare using digital twins: Monitoring, analysis, and advancementRakhi Arora, Nitin Dixit, Jigyasa Mishra, Muskan Sihare, Samiksha Khule and Yogesh Kumar Sharma8.1. Introduction8.2. Literature Survey8.3. Enabling Technologies and Data Sources8.4. Digital Twin In Healthcare—Applications8.5. Integration of Artificial Intelligence in Human Digital Twins8.6. Limitations Associated with Healthcare Digital Twins8.7. ConclusionReferences9. Wellbeing of working mothers based on decision making: A data science approach 1Jyoti Deshmukh, Vijay Rathod, Nilesh Sable and Gitanjali Shinde9.1. Introduction9.2. Exploration of Wearable Devices9.3. Experimental Methods9.4. Monitoring of Fetal Movement9.5. The Wearable Device Design9.6. The Patient Data Possession9.7. Energy Assessment9.8. Fetal Movement Extraction of Feature9.9. Design of Phantom—The Simulation System for Fetal Movement9.10. ConclusionReferencesPart IIITransformation in agriculture10. Navigating the agricultural landscape: Artificial intelligence and Industry 5.
