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

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Editors: Muhammad Zeeshan Shakir 1 ; Naeem Ramzan 2
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Publication Year: 2020

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.

Inspec keywords: affective computing; cellular radio; robots; medical computing; sensors; learning (artificial intelligence); 5G mobile communication

Other keywords: artificial neural networks; emotion recognition; robot intelligence; human-robot networking; data reduction; autonomous robotic grasping; indoor classification; perceptual video quality metrics; beyond-5G wireless networks; predictive mobility management; 5G wireless networks; adaptive feature selection; quadrotor; deterministic compressed sensing; deep Q-network-based coverage hole detection; early hyperkalaemia detection; artificial intelligence; ECG monitoring; multitask learning; visual object tracking; ultrawide bandwidth sensor node localization; cascaded machine learning; fuzzy logic controller; large-scale distributed SOM-based architecture; affective computing; soft end-effectors; EEG-based biometrics; indoor localization; autonomous driving; deep learning; large-scale scalable SOM-based architecture; human manipulation modelling; template ageing; connected health; human-robot sensing; human-horse interaction; cellular networks; Internet of Things; human-robot computing; affect detection; data analytics; surface water pollution monitoring

Subjects: Sensing devices and transducers; Robotics; General and management topics; Expert systems and other AI software and techniques; Transducers and sensing devices; Mobile radio systems; Biology and medical computing; General electrical engineering topics

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