Sensor Networks Physical and Social Sensing in the IoT

This reprint presents a collection of original research and survey articles that tackle the practical challenges in large-scale and rapid deployment of sensors for diverse applications as well as the resulting Big Data processing. The complexity of the generated data ranges from large-scale sensor n...

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Bibliographic Details
Other Authors: De, Suparna (Editor), Moessner, Klaus (Editor)
Format: Electronic Book Chapter
Language:English
Published: Basel MDPI - Multidisciplinary Digital Publishing Institute 2023
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DOAB: description of the publication
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245 1 0 |a Sensor Networks  |b Physical and Social Sensing in the IoT 
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520 |a This reprint presents a collection of original research and survey articles that tackle the practical challenges in large-scale and rapid deployment of sensors for diverse applications as well as the resulting Big Data processing. The complexity of the generated data ranges from large-scale sensor networks to smartphone-enabled citizen sensing data from social networks and personal health devices, which requires advanced data processing, mining and fusion methods. Solutions listed in this book include those that address issues of the interoperability of IoT solutions and data fragmentation through crawling, indexing and searching IoT data sources and the predictive maintenance of sensors. Social networks are also in scope, through a visualisation system for the analysis of anomalies in social graphs, detecting context-aware sociability patterns and assessing the effectiveness of fine tuning and pretrained word embedding in generating interpretable topics from short texts in social networks. Applications in scope include smart tourism, fall detection through personal health sensors and an energy management expert assistant. 
540 |a Creative Commons  |f https://creativecommons.org/licenses/by/4.0/  |2 cc  |4 https://creativecommons.org/licenses/by/4.0/ 
546 |a English 
650 7 |a Technology: general issues  |2 bicssc 
650 7 |a History of engineering & technology  |2 bicssc 
653 |a anomaly detection 
653 |a visualization 
653 |a social communication 
653 |a egocentric network 
653 |a internet of things 
653 |a mental health 
653 |a pervasive computing 
653 |a context awareness 
653 |a sociability 
653 |a social behavior 
653 |a sociability pattern 
653 |a fall detection 
653 |a wearable sensors 
653 |a sampling rate 
653 |a data preprocessing 
653 |a feature extraction 
653 |a Machine Learning 
653 |a Internet of Things 
653 |a search 
653 |a security 
653 |a privacy 
653 |a reliability 
653 |a IoT search framework 
653 |a IoT data sources 
653 |a home energy management systems (HEMS) 
653 |a Internet of Things (IoT) 
653 |a artificial intelligence (AI) 
653 |a Voice Assistant 
653 |a machine learning (ML) 
653 |a big data 
653 |a fault detection 
653 |a sensor data 
653 |a industry 4.0 
653 |a data reduction 
653 |a feature analysis 
653 |a feature selection 
653 |a indicators 
653 |a artificial neural network 
653 |a location privacy 
653 |a perturbation mechanism 
653 |a proximity detection 
653 |a digital contact tracing 
653 |a multi-floor areas 
653 |a short-text data 
653 |a neural-topic model 
653 |a pretrained word embedding 
653 |a coherent topic 
653 |a fine-tuning 
653 |a smart tourism 
653 |a social sensing 
653 |a sensors 
653 |a e-tourism 
653 |a distributed-architecture 
653 |a Spark 
653 |a Zenoh 
653 |a FaaS 
653 |a Elasticsearch 
653 |a industrial revolution 4.0 (IR 4.0) 
653 |a computer networks 
653 |a network security 
653 |a wireless sensor networks (WSN) 
653 |a systematic literature review (SLR) 
653 |a state-of-the-art 
653 |a aggregation 
653 |a authentication 
653 |a key management 
653 |a smart home 
653 |a smart meter 
653 |a n/a 
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856 4 0 |a www.oapen.org  |u https://directory.doabooks.org/handle/20.500.12854/100804  |7 0  |z DOAB: description of the publication