AI for Emerging Verticals Human-robot computing, sensing and networking

• Main Authors: Shakir, Muhammad Zeeshan, Ramzan, Naeem
• Format: eBook
• Language: English
• Published: Stevenage The Institution of Engineering and Technology 2021; Institution of Engineering and Technology (The IET); Institution of Engineering & Technology; Institution of Engineering and Technology
• Edition: 1
• Series: Computing and Networks
• Subjects: Artificial intelligence; Automation; Computational intelligence; COMPUTERS; General Engineering & Project Administration; General References; Intelligence (AI) & Semantics; sensors; 5G mobile communication; affective computing; robots; learning (artificial intelligence); medical computing; cellular radio
• ISBN: 1785619829; 9781785619823
• DOI: 10.1049/PBPC034E

By specializing in a vertical market, companies can better understand their customers and bring more insight to clients in order to become an integral part of their businesses. This approach requires dedicated tools, which is where artificial intelligence (AI) and machine learning (ML) will play a major role. By adopting AI software and services, businesses can create predictive strategies, enhance their capabilities, better interact with customers, and streamline their business processes. This edited book explores novel concepts and cutting-edge research and developments towards designing these fully automated advanced digital systems. Fostered by technological advances in artificial intelligence and machine learning, such systems potentially have a wide range of applications in robotics, human computing, sensing and networking. The chapters focus on models and theoretical approaches to guarantee automation in large multi-scale implementations of AI and ML systems; protocol designs to ensure AI systems meet key requirements for future services such as latency; and optimisation algorithms to leverage the trusted distributed and efficient complex architectures. The book is of interest to researchers, scientists, and engineers working in the fields of ICTs, networking, AI, ML, signal processing, HCI, robotics and sensing. It could also be used as supplementary material for courses on AI, machine and deep learning, ICTs, networking signal processing, robotics and sensing.