Sensor Networks: Physical and Social Sensing in the IoT

Edited by
May 2023
316 pages
  • ISBN978-3-0365-7468-4 (Hardback)
  • ISBN978-3-0365-7469-1 (PDF)

This book is a reprint of the Special Issue Sensor Networks: Physical and Social Sensing in the IoT that was published in

Chemistry & Materials Science
Environmental & Earth Sciences

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.

  • Hardback
© 2022 by the authors; CC BY-NC-ND license
anomaly detection; visualization; social communication; egocentric network; internet of things; mental health; pervasive computing; context awareness; sociability; social behavior; sociability pattern; fall detection; wearable sensors; sampling rate; data preprocessing; feature extraction; Machine Learning; Internet of Things; search; security; privacy; reliability; IoT search framework; IoT data sources; home energy management systems (HEMS); Internet of Things (IoT); artificial intelligence (AI); Voice Assistant; machine learning (ML); big data; fault detection; sensor data; industry 4.0; data reduction; feature analysis; feature selection; indicators; artificial neural network; location privacy; perturbation mechanism; proximity detection; digital contact tracing; multi-floor areas; short-text data; neural-topic model; pretrained word embedding; coherent topic; fine-tuning; smart tourism; social sensing; sensors; e-tourism; distributed-architecture; Spark; Zenoh; FaaS; Elasticsearch; Internet of Things (IoT); industrial revolution 4.0 (IR 4.0); computer networks; network security; wireless sensor networks (WSN); systematic literature review (SLR); state-of-the-art; aggregation; authentication; key management; privacy; smart home; smart meter; n/a