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" Guide to ambient intelligence in the IoT environment : "
Zaigham Mahmood, editor.
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BL
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| Record Number
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860266
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| Title & Author
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Guide to ambient intelligence in the IoT environment : : principles, technologies and applications /\ Zaigham Mahmood, editor.
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| Publication Statement
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Cham, Switzerland :: Springer,, [2019]
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| Series Statement
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Computer communications and networks
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| Page. NO
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1 online resource
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| ISBN
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3030041735
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: 3030041743
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: 9783030041731
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: 9783030041748
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3030041727
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9783030041724
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| Notes
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4.4 Modeling the Smart Stadium System
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| Contents
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Intro; Preface; Overview; Objectives; Organization; Target Audiences; Acknowledgements; Other Springer Books by Zaigham Mahmood; Fog Computing: Concepts, Frameworks and Technologies; Smart Cities: Development and Governance Frameworks; Data Science and Big Data Computing: Frameworks and Methodologies; Connected Environments for the Internet of Things: Challenges and Solutions; Connectivity Frameworks for Smart Devices: The Internet of Things from a Distributed Computing Perspective; Cloud Computing: Methods and Practical Approaches; Cloud Computing: Challenges, Limitations and R & D Solutions
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1.2 Ambient Intelligence1.3 Ambient Intelligence and Smart Cities; 1.4 Trends in Ambient Intelligence; 1.5 Context Awareness and Ambient Intelligence; 1.6 AmI Topologies and Information Architectures; 1.7 Issues in Smart Network Design; 1.8 Conclusion; References; 2 The State and Future of Ambient Intelligence in Industrial IoT Environments; 2.1 Introduction; 2.2 Sensing Technologies and Data Fusion in Industrial AmI; 2.3 Industrial KB Systems and Computational Intelligence; 2.3.1 Fit-for-Purpose Algorithms; 2.3.2 Context Awareness; 2.3.3 Adaptive and Anticipatory Functions
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2.4 AmI Architecture and IoT in Industrial Environments2.5 Industrial Applications of AmI; 2.5.1 Smart Mining; 2.5.2 Intelligent Manufacturing; 2.5.3 Smart Construction; 2.6 Roadmap for AmI in IIoT Environments; 2.7 Conclusion; References; 3 Ambient Intelligence in Business Environments and Internet of Things Transformation Guidelines; 3.1 Introduction; 3.2 Ambient Intelligence in the Business Environment; 3.2.1 Ambient Intelligence; 3.2.2 Improving Business with Ambient Intelligence; 3.2.3 Current Implementations of AmI; 3.2.4 Future Opportunities for Businesses
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3.3 IoT Technology Transformation Issues3.3.1 Management Issues; 3.3.2 Technical Issues; 3.3.3 Social Issues; 3.4 IoT Technology Transformation Guidelines; 3.5 Conclusion; References; 4 Runtime Adaptability of Ambient Intelligence Systems Based on Component-Oriented Approach; 4.1 Introduction; 4.2 Background; 4.2.1 Ambient Intelligence; 4.2.2 Component-Oriented Software Engineering; 4.2.3 Runtime Adaptability of Software Systems; 4.2.4 Ontology-Based Systems; 4.3 Case Study and Problem Description; 4.3.1 Case Study: A Density-Aware Density-Adaptive AmI Network; 4.3.2 Problem Description
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Continued Rise of the Cloud: Advances and Trends in Cloud ComputingSoftware Engineering Frameworks for the Cloud Computing Paradigm; Cloud Computing for Enterprise Architectures; Software Project Management for Distributed Computing: Life-Cycle Methods for Developing Scalable and Reliable Tools; Requirements Engineering for Service and Cloud Computing; User Centric E-Government: Challenges and Opportunities; Contents; Contributors; About the Editor; Principles and Technologies; 1 Ambient Intelligence in Smart City Environments: Topologies and Information Architectures; 1.1 Introduction
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| Abstract
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Ambient intelligence (AmI) is an element of pervasive computing that brings smartness to living and business environments to make them more sensitive, adaptive, autonomous and personalized to human needs. It refers to intelligent interfaces that recognise human presence and preferences, and adjust smart environments to suit their immediate needs and requirements. The key factor is the presence of intelligence and decision-making capabilities in IoT environments. The underlying technologies include pervasive computing, ubiquitous communication, seamless connectivity of smart devices, sensor networks, artificial intelligence (AI), machine learning (ML) and context-aware human-computer interaction (HCI). AmI applications and scenarios include smart homes, autonomous self-driving vehicles, healthcare systems, smart roads, the industry sector, smart facilities management, the education sector, emergency services, and many more. The advantages of AmI in the IoT environment are extensive. However, as for any new technological paradigm, there are also many open issues and limitations. This book discusses the AmI element of the IoT and the relevant principles, frameworks, and technologies in particular, as well as the benefits and inherent limitations. It reviews the state of the art of current developments relating to smart spaces and AmI-based IoT environments. Written by leading international researchers and practitioners, the majority of the contributions focus on device connectivity, pervasive computing and context modelling (including communication, security, interoperability, scalability, and adaptability). The book presents cutting-edge research, current trends, and case studies, as well as suggestions to further our understanding and the development and enhancement of the AmI-IoT vision.
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Ambient intelligence.
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Internet of things.
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Ambient intelligence.
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Internet of things.
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| Dewey Classification
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004.01/9
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| LC Classification
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QA76.9.A48G85 2019
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| Added Entry
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Mahmood, Zaigham
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