Pervasive Computing in IoT

In the era of Internet of Things (IoT) that we have entered, the “Monitoring–Decision–Execution” cycle of typical autonomic and automation systems is extended to include distributed developments that might scale from a smart home or greenhouse to a smart city, and from autonomous driving to emergenc...

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Wydane: MDPI - Multidisciplinary Digital Publishing Institute 2024
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collection Directory of Open Access Books
description In the era of Internet of Things (IoT) that we have entered, the “Monitoring–Decision–Execution” cycle of typical autonomic and automation systems is extended to include distributed developments that might scale from a smart home or greenhouse to a smart city, and from autonomous driving to emergency management. In such highly distributed and scalable architectures, each of the three processes can be situated at any physical or virtual computing system and located, ideally, at any place. Hence, communication and interoperation between the subsystems that comprise the total IoT system, namely extreme edge, edge, fog, and cloud deployments, are of critical importance. This reprint presents a collection of high-quality, state-of-the-art research papers, each introducing challenging issues in pervasive computing across the different domains of the IoT ecosystem. It comprises four papers focusing on customized application frameworks, three papers dealing with issues of ambient intelligence and assisted living of the aging population, three papers considering blockchain technology in various IoT applications, and two survey papers related to sensors and their applications.
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publisher MDPI - Multidisciplinary Digital Publishing Institute
publisherStr MDPI - Multidisciplinary Digital Publishing Institute
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spelling doab-20.500.12854ir-1437652024-09-06T08:20:42Z Pervasive Computing in IoT Panagiotakis, Spyros Markakis, Evangelos K. activity recognition posture transitions inertial sensor feature selection support vector machine ambient intelligence human behavior monitoring smart homes activities of daily living elderly population machine learning internet of things ubiquitous computing big data indoor localization ambient assisted living indoor location human–computer interaction assistive technology blockchain records non-fungible tokens transparency Internet of Things sensor computational intelligence data analytics data pre-processing capacitive sensing low cost tangible sensing interactive surface tactile sensing human-computer interaction (HCI) IoT pervasive computing healthcare smart cities cyber security cyber-physical systems zero-trust ABAC IPFS edge device framework application server platform SEMAR neural networks federated learning learning on the edge device identification unsupervised machine learning remote laboratory Arduino microcontroller programming xAPI LRS assessment types pervasive learning supervised learning n/a thema EDItEUR::U Computing and Information Technology thema EDItEUR::U Computing and Information Technology::UY Computer science In the era of Internet of Things (IoT) that we have entered, the “Monitoring–Decision–Execution” cycle of typical autonomic and automation systems is extended to include distributed developments that might scale from a smart home or greenhouse to a smart city, and from autonomous driving to emergency management. In such highly distributed and scalable architectures, each of the three processes can be situated at any physical or virtual computing system and located, ideally, at any place. Hence, communication and interoperation between the subsystems that comprise the total IoT system, namely extreme edge, edge, fog, and cloud deployments, are of critical importance. This reprint presents a collection of high-quality, state-of-the-art research papers, each introducing challenging issues in pervasive computing across the different domains of the IoT ecosystem. It comprises four papers focusing on customized application frameworks, three papers dealing with issues of ambient intelligence and assisted living of the aging population, three papers considering blockchain technology in various IoT applications, and two survey papers related to sensors and their applications. 2024-09-06T08:20:33Z 2024-09-06T08:20:33Z 2024 book ONIX_20240906_9783725814879_127 9783725814879 9783725814886 https://directory.doabooks.org/handle/20.500.12854/143765 eng application/octet-stream Attribution-NonCommercial-NoDerivatives 4.0 International https://mdpi.com/books/pdfview/book/9496 https://mdpi.com/books/pdfview/book/9496 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-1488-6 10.3390/books978-3-7258-1488-6 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783725814879 9783725814886 open access
spellingShingle activity recognition
posture transitions
inertial sensor
feature selection
support vector machine
ambient intelligence
human behavior monitoring
smart homes
activities of daily living
elderly population
machine learning
internet of things
ubiquitous computing
big data
indoor localization
ambient assisted living
indoor location
human–computer interaction
assistive technology
blockchain
records
non-fungible tokens
transparency
Internet of Things
sensor
computational intelligence
data analytics
data pre-processing
capacitive sensing
low cost
tangible sensing
interactive surface
tactile sensing
human-computer interaction (HCI)
IoT
pervasive computing
healthcare
smart cities
cyber security
cyber-physical systems
zero-trust
ABAC
IPFS
edge device
framework
application server platform
SEMAR
neural networks
federated learning
learning on the edge
device identification
unsupervised machine learning
remote laboratory
Arduino microcontroller programming
xAPI
LRS
assessment types
pervasive learning
supervised learning
n/a
thema EDItEUR::U Computing and Information Technology
thema EDItEUR::U Computing and Information Technology::UY Computer science
Pervasive Computing in IoT
title Pervasive Computing in IoT
title_full Pervasive Computing in IoT
title_fullStr Pervasive Computing in IoT
title_full_unstemmed Pervasive Computing in IoT
title_short Pervasive Computing in IoT
title_sort pervasive computing in iot
topic activity recognition
posture transitions
inertial sensor
feature selection
support vector machine
ambient intelligence
human behavior monitoring
smart homes
activities of daily living
elderly population
machine learning
internet of things
ubiquitous computing
big data
indoor localization
ambient assisted living
indoor location
human–computer interaction
assistive technology
blockchain
records
non-fungible tokens
transparency
Internet of Things
sensor
computational intelligence
data analytics
data pre-processing
capacitive sensing
low cost
tangible sensing
interactive surface
tactile sensing
human-computer interaction (HCI)
IoT
pervasive computing
healthcare
smart cities
cyber security
cyber-physical systems
zero-trust
ABAC
IPFS
edge device
framework
application server platform
SEMAR
neural networks
federated learning
learning on the edge
device identification
unsupervised machine learning
remote laboratory
Arduino microcontroller programming
xAPI
LRS
assessment types
pervasive learning
supervised learning
n/a
thema EDItEUR::U Computing and Information Technology
thema EDItEUR::U Computing and Information Technology::UY Computer science
topic_facet activity recognition
posture transitions
inertial sensor
feature selection
support vector machine
ambient intelligence
human behavior monitoring
smart homes
activities of daily living
elderly population
machine learning
internet of things
ubiquitous computing
big data
indoor localization
ambient assisted living
indoor location
human–computer interaction
assistive technology
blockchain
records
non-fungible tokens
transparency
Internet of Things
sensor
computational intelligence
data analytics
data pre-processing
capacitive sensing
low cost
tangible sensing
interactive surface
tactile sensing
human-computer interaction (HCI)
IoT
pervasive computing
healthcare
smart cities
cyber security
cyber-physical systems
zero-trust
ABAC
IPFS
edge device
framework
application server platform
SEMAR
neural networks
federated learning
learning on the edge
device identification
unsupervised machine learning
remote laboratory
Arduino microcontroller programming
xAPI
LRS
assessment types
pervasive learning
supervised learning
n/a
thema EDItEUR::U Computing and Information Technology
thema EDItEUR::U Computing and Information Technology::UY Computer science
url ONIX_20240906_9783725814879_127