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230811 ||| eng |
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|a 9783036577517
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|a 9783036577500
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|a books978-3-0365-7750-0
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| 100 |
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|a Lavric, Alexandru
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| 245 |
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|a IoT Multi Sensors
|h Elektronische Ressource
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| 260 |
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|a Basel
|b MDPI - Multidisciplinary Digital Publishing Institute
|c 2023
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| 300 |
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|a 1 electronic resource (404 p.)
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| 653 |
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|a lightweight privacy
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|a piezoelectric sensors
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| 653 |
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|a SPA
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| 653 |
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|a smart health
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| 653 |
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|a healthcare and wellness
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| 653 |
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|a genetic algorithm
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| 653 |
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|a RCL-bridges
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|a routing
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| 653 |
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|a smart grid monitoring
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| 653 |
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|a impedance meter
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| 653 |
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|a greenhouse gas
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| 653 |
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|a privacy
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| 653 |
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|a quarantine monitoring
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| 653 |
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|a IoT
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|a BEEA
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| 653 |
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|a deep learning
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|a combinatorial optimization
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|a chicken swarm optimization
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| 653 |
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|a health cable monitoring
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| 653 |
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|a IoT wearable device
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| 653 |
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|a edge intelligence
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| 653 |
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|a service provisioning
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| 653 |
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|a long-term monitoring
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| 653 |
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|a Technology: general issues / bicssc
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| 653 |
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|a industrial Internet of Things
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| 653 |
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|a predictive maintenance
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| 653 |
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|a last-mile emission
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| 653 |
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|a wide area networks
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|a cluster
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| 653 |
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|a Health 4.0
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|a artificial neural network
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| 653 |
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|a WSN
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|a scalability
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|a wireless sensor networks
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| 653 |
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|a IoMT
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| 653 |
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|a clustering
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| 653 |
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|a healthcare architectures
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| 653 |
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|a security
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| 653 |
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|a malicious node detection
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| 653 |
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|a power consumption
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| 653 |
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|a input impedance (S11)
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| 653 |
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|a remote healthcare
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| 653 |
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|a modules
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| 653 |
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|a telemedicine
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| 653 |
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|a internet of things
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| 653 |
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|a transceiver
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| 653 |
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|a supply chain
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| 653 |
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|a IoT applications
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| 653 |
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|a Message Queue Telemetry Transport (MQTT)
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| 653 |
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|a energy optimization
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| 653 |
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|a Internet of Things (IoT)
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| 653 |
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|a mesh networks
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| 653 |
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|a small patch antenna
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| 653 |
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|a anomaly detection
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| 653 |
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|a LEACH protocol
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| 653 |
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|a wireless sensor network
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| 653 |
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|a IoT devices
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| 653 |
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|a low-cost
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| 653 |
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|a AVR® micro-controller
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| 653 |
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|a ADP
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| 653 |
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|a FPGA
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| 653 |
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|a LoRaWAN
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| 653 |
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|a cryptography
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| 653 |
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|a PKCs
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| 653 |
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|a modular addition and subtraction
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| 653 |
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|a mixed integer programming
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| 653 |
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|a energy efficiency
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| 653 |
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|a secure data management
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| 653 |
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|a IoT gateway
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| 653 |
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|a History of engineering and technology / bicssc
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| 653 |
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|a self-sovereign identity
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| 653 |
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|a consensus mechanisms
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| 653 |
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|a LPWANs
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|a load balancing
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| 653 |
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|a sewer network
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| 653 |
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|a interplanetary file system
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| 653 |
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|a Hypertext Transfer Protocol (HTTP)
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| 653 |
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|a LoRa
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| 653 |
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|a LPWAN
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| 653 |
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|a Internet of Things
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| 653 |
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|a multi-sensor
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| 653 |
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|a antenna impedance matching
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| 653 |
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|a technical cable coefficient
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| 653 |
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|a SigFox
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| 653 |
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|a authentication
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| 653 |
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|a prime field
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| 653 |
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|a smart grid
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| 653 |
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|a modular inversion
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| 653 |
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|a data storage
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| 653 |
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|a blockchain
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| 653 |
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|a sustainable logistics
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| 653 |
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|a cable diagnostics
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| 653 |
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|a surgical practice
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| 653 |
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|a partial discharge
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| 653 |
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|a sensors
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| 653 |
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|a smart campus
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| 653 |
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|a portable instrument
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| 653 |
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|a NodeMCU
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| 653 |
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|a COVID-19 sensors
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| 653 |
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|a optimization
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| 653 |
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|a Internet of Surgical Things
|
| 700 |
1 |
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|a Anchidin, Liliana
|
| 700 |
1 |
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|a Petrariu, Adrian I.
|
| 700 |
1 |
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|a Lavric, Alexandru
|
| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b DOAB
|a Directory of Open Access Books
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| 500 |
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|a Creative Commons (cc), https://creativecommons.org/licenses/by/4.0/
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| 024 |
8 |
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|a 10.3390/books978-3-0365-7750-0
|
| 856 |
4 |
2 |
|u https://directory.doabooks.org/handle/20.500.12854/100901
|z DOAB: description of the publication
|
| 856 |
4 |
0 |
|u https://www.mdpi.com/books/pdfview/book/7369
|7 0
|x Verlag
|3 Volltext
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|a This reprint focuses on state-of-the-art technologies, the latest findings and current challenges in IoT with emphasis on healthcare, transportation, antenna design and disease detection. The included papers cover numerous topics of interest that include:IoT communication protocols;LPWAN for IoT (Sigfox, LoRa, etc.);Antenna design for IoT applications;Large-scale, high-density IoT networks and architectures;IoT applications and multi-sensors for transportation and traffic control;IoT convergence for Smart Health;Machine-learning/deep-learning algorithms for sensing IoT;Machine-learning-based healthcare applications and disease detection using IoT architectures;Applications and examples of use.
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