NFC Interface for Standalone Data Acquisition Device**This work was supported by the project SP2016/162, “Development of algorithms and systems for control, measurement and safety applications II” of Student Grant System, VSB-TU Ostrava.

Prauzek, Michal; Konecny, Jaromír; Venclikova, Marketa; Baranek, Vojtech

doi:10.1016/j.ifacol.2016.12.051

Cited by 2 publications

(1 citation statement)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…With the development of wireless communication technology, NFC, which evolved from non-contact radio frequency identification, has gradually developed, which can establish a wireless network more quickly and automatically, and can establish a connection between surrounding WIFI and Bluetooth to realize the connection between electronic devices. Communication within [28]. NFC greatly reduces the overall security authentication and security identification process, making the connection between electronic devices faster.…”

Section: Overview Of Common Communication Technologiesmentioning

confidence: 99%

Research on secure Internet of things gateway technology based on multi-communication methods

Ying

Yang

Shi

et al. 2023

Applied Mathematics and Nonlinear Sciences

View full text Add to dashboard Cite

The Internet of Things, as an important part of important data aggregation, forwarding and control, often leads to objectivity errors due to the huge and complex received data. Based on this, this paper introduces GRU, LSTM, SRU deep learning to optimize the data received by the Internet of Things, and selects the most suitable communication mode optimization algorithm. The experimental results show that the accuracy errors of GRU, LSTM, and SRU algorithms show a downward trend, from 0.024 to 0.010%; the training time is reduced by 254 minutes, and the training speed is increased to 86%, indicating the excellent performance of SRU deep learning in IoT gateways.

show abstract

Section: Overview Of Common Communication Technologiesmentioning

confidence: 99%