Reprint

Smart Sensor Technologies for IoT

Edited by
November 2021
270 pages
  • ISBN978-3-0365-2462-7 (Hardback)
  • ISBN978-3-0365-2463-4 (PDF)

This book is a reprint of the Special Issue Smart Sensor Technologies for IoT that was published in

Chemistry & Materials Science
Engineering
Environmental & Earth Sciences
Summary

The recent development in wireless networks and devices has led to novel services that will utilize wireless communication on a new level. Much effort and resources have been dedicated to establishing new communication networks that will support machine-to-machine communication and the Internet of Things (IoT). In these systems, various smart and sensory devices are deployed and connected, enabling large amounts of data to be streamed.

Smart services represent new trends in mobile services, i.e., a completely new spectrum of context-aware, personalized, and intelligent services and applications. A variety of existing services utilize information about the position of the user or mobile device. The position of mobile devices is often achieved using the Global Navigation Satellite System (GNSS) chips that are integrated into all modern mobile devices (smartphones). However, GNSS is not always a reliable source of position estimates due to multipath propagation and signal blockage. Moreover, integrating GNSS chips into all devices might have a negative impact on the battery life of future IoT applications. Therefore, alternative solutions to position estimation should be investigated and implemented in IoT applications.

This Special Issue, “Smart Sensor Technologies for IoT” aims to report on some of the recent research efforts on this increasingly important topic. The twelve accepted papers in this issue cover various aspects of Smart Sensor Technologies for IoT.

Format
  • Hardback
License
© 2022 by the authors; CC BY-NC-ND license
Keywords
Internet of Things (IoT); ReRoute; Multicast Repair (M-REP); internet of things (IoT); Fast Reroute; bit repair (B-REP); failure repair; WSN; MANET; DRONET; multilayered network model; 5G; IoT; smart sensors; smart sensor; IoT system; Velostat; pressure sensor; convolutional neural network; data classification; position detection; magnetometer; traffic; vehicle; classification; measurement; detection; Internet of Things; Bluetooth; indoor tracking; mobile localization; optical sensors; vibration sensing; quality of service differentiation; wireless optical networks; free space optics; multiwavelength laser; optical code division multiple access (OCDMA); underwater wireless sensor network; energy-efficient; clustering; depth-based routing; mm-wave radars; GNSS-RTK positioning; wireless technology; electromagnetic scanning; point cloud; localization; IMU; Wi-Fi; positioning; dead reckoning; particle filter; fingerprinting; Wi-Fi sensing; human activity recognition; location-independent; meta learning; metric learning; few-shot learning; ACR; H.264/AVC; H.265/HEVC; QoE; subjective assessment; n/a