Artificial Intelligence and Industry 4.0: The Next Frontier in Industry

Artificial Intelligence and Industry 4.0
Copyright
Contributors
Influence and implementation of Industry 4.0 in health care
	Introduction
	Industry 1.0 to 4.0
	Healthcare 1.0 to 4.0
	Literature review
	Big data in health care
	Internet of Things in the healthcare sector
	Blockchain technology in the healthcare sector
	Applications in healthcare 4.0
		Observing physiological and pathological signals
		Self-management, wellness monitoring, and prevention
		Smart pharmaceuticals and monitoring of medication intake
		Personalized healthcare system
		Cloud-based health information systems
		Telepathology, telemedicine, and disease monitoring
		Assisted living
		Rehabilitation
	Case studies
	Conclusion
	The recent innovations and research solutions of Industry 4.0 in healthcare sector
	References
Impact of artificial intelligence in the healthcare sector
	Introduction
	Literature review
		AI in health care
		Utilization of AI in health care in India
			Hospitals
			Pharmaceuticals
			Diagnostics
			Medical equipment and supplies
			Health insurance
			Telemedicine
	Research framework and development of hypotheses
		Technological perspective (TP)
			Cost-effectiveness (CE)
			Relative advantage (RA)
			Security and privacy concerns (SPC)
			Complexity (COMP)
		Organizational perspective (OP)
			HR readiness (HRR)
			Top management support (TMS)
			Organizational readiness (ORR)
		Environmental perspective (EP)
			Competitive pressure (CP)
			Support from technology vendors (STV)
			Environmental uncertainty (EU)
	Research methodology
		Demographics of the respondents
	Data analysis
		Reliability and validity
			Cronbachs alpha
			Composite reliability
		Harman test
		Exploratory factor analysis (EFA)
		Construct validity (CV)
		Structural equation modeling
	Discussion
		Technological perspective (TP)
		Organizational perspectives (OP)
		Environmental perspectives (EP)
	Conclusion
	Limitations and future scope of the study
	Appendix A. Measurement items
	Appendix B. Questionnaire
	References
Embedded system for model characterization developing intelligent controllers in industry 4.0
	Introduction
	Theoretical framework
		Processing unit Raspberry PI
		Analogic digital converter ADS1115
		Genetic algorithms
			Population
			Selection
			Crossover operation
			Mutation
		Transfer function
			First-order systems
			Second-order systems
	Methods
		General description of the identification process
		Time analysis for the transfer functions
		Fitness function for characterizing TFs
			First-order systems fitness function
			Second-order systems fitness function
	Results and discussion
		Design of experiment
		Results
			Configuration of parameters in the optimization algorithm
			First-order transfer function
			Second-order transfer function
		Discussion
			Integration of the proposed algorithm into industry 4.0
	Conclusions
		Future work
	References
Industry 4.0 multiagent system-based knowledge representation through blockchain
	Introduction
	Literature survey
	What is industry 4.0
		Virtual Sensors in Intelligent industry
		Intelligent model virtual sensor description
			Clustering
			Opinion analysis
			Trends
		Industry 4.0 vertical integration
	What is blockchain
	Blockchain as the industry engine 4.0
	Blockchain-based conventional networks
	Decision making concept
	What is ambient intelligence
		Industry as a smart environment
		Sensors
		Decision-making in ambient intelligence
		Better decision-making in industry
	Multiagent systems
	Blockchain for the representation of knowledge from multiagent systems
		Multiagent systems in industry
		Model presentation
	Comparison between the existing model and our proposed model
	Country-wise comparison of multiagent-based industry 4.0
	Conclusion and future work
	References
Artificial Intelligence: A tool to resolve thermal behavior issues in disc braking systems
	Introduction
	Artificial Intelligence in the automobile sector
	AI in automobile disc braking systems
	Notable brake complaints observed at servicing centers
	Literature survey
	Application of AI to resolve thermal problems during long braking
	Results and conclusion
	Future scope
	References
Proposal of a smart framework for a transportation system in a smart city
	Introduction
	Literary review
	Spider monkey optimization
		Structure of fission-fusion culture
		Spider monkey conduct
		Social conduct
		Spider monkey optimization process
		Application methodology SMO
			SMO parameters
	Practical application
		Initial conditions
		SMO control parameters
	Discussion of results
	Conclusions
	References
Society 5.0: Effective technology for a smart society
	Introduction
	Literature review
	Industrial revolutions
		Industry 1.0
		Industry 2.0
		Industry 3.0
		Industry 4.0
	The concept of Society 5.0 and artificial intelligence
		The transition process from Industry 4.0 to Society 5.0
		The concept of Society 5.0
		The factors that reveal Society 5.0
		The goals of Society 5.0
		The innovations provided by Society 5.0
		The relationship between Society 5.0 and artificial intelligence
		The obstacles to Society 5.0
	Conclusions
	Recommendations and future scope
	References
Big data analytics for strategic and operational decisions
	Introduction
	Overview
		Business analytics
		Type of analytics
		Big data analytics
		Enterprise Big data sources
	Opportunities
	Challenges
	Proposed solution
	Case study
	Results and discussion
	Conclusion
	References
Person-based automation with artificial intelligence Chatbots: A driving force of Industry 4.0
	Introduction
		Chatbots
		Role of Chatbots in Industry 4.0
		Importance of Chatbots
		Key concepts
			Pattern matching
			Artificial Intelligence Markup Language (AIML)
			Latent semantic analysis (LSA)
			Chat script
			Natural language unit (NLU)
		Popular Chatbots
	NBC Chatbot
	A.L.I.C.E
		Chapter organization
	Related work
		History of Chatbots
		Machine learning and artificial intelligence algorithms in Chatbots
		Models of Chatbots
			The selective model
			The generative model
		Selective vs. generative models
		Challenges in Chatbot implementation
		Machine learning in Chatbots for sentiment analysis
	Proposed work
		The general architecture of Chatbots
			Analyzing user request
		Proposed model
	Applications of Chatbots
	Weaknesses of Chatbots and scope for improvement
	Results and discussion
	Conclusion and future work
	References
Index