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Full Description
This book covers challenges and solutions in establishing Industry 4.0 standards for Internet of Things. It proposes a clear view about the role of Internet of Things in establishing standards. The sensor design for industrial problem, challenges faced, and solutions are all addressed. The concept of digital twin and complexity in data analytics for predictive maintenance and fault prediction is also covered. The book is aimed at existing problems faced by the industry at present, with the goal of cost-efficiency and unmanned automation. It also concentrates on predictive maintenance and predictive failures. In addition, it includes design challenges and a survey of literature.
Contents
Part I - Smart sensing in Industries.- Sensor design and rapid prototyping for industrial problems.- Technology, protocols and new innovations in IIoT.- Predictive analytics for critical machines using deep learning and machine intelligence.- Smart object recognition for warehouse logistics and security.- Digital Twin creating, challenges and solutions.- Part II - Machine Intelligence and automation.- Machine Health monitoring and fool proof diagnosis.- Role of AI and bio inspired computing in decision making.- Deep learning concepts aiding Industrial applications.- Energy harvesting methodologies and experimentation of sensors and actuators.- Reliability analysis and fault tolerant architecture for IIoT and Edge Computing.- Delay tolerant system for critical machine monitoring.- Part III - Role of robotics in smart production.- Automation solution for smart development applications.- UAV, UGV solutions for warehouse logistics.- Customer interaction and feedback collection robots usingdeep learning.- Smart recognition system for Business predictions.- Role of RFID in industry 4.0.- Conclusion.
