An Evolving Multivariate Time Series Compression Algorithm for IoT Applications

The Internet of Things (IoT) is transforming how devices interact and share data, especially in areas like vehicle monitoring. However, transmitting large volumes of real-time data can result in high latency and substantial energy consumption. In this context, Tiny Machine Learning (TinyML) emerges...

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Vydáno v:	Sensors (Basel, Switzerland) Ročník 24; číslo 22; s. 7273
Hlavní autoři:	Costa, Hagi, Silva, Marianne, Sánchez-Gendriz, Ignacio, Viegas, Carlos M. D., Silva, Ivanovitch
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Switzerland MDPI AG 14.11.2024 MDPI
Témata:	Algorithms Case studies Data analysis Data compression Data processing Data transmission Datasets Embedded systems Energy consumption Energy efficiency Environmental monitoring Equipment and supplies evolving algorithm Internet of Things IoT Machine learning OBD-II edge Sensors Teaching Time series TinyML Vehicles Wavelet transforms United States New Jersey data compression evolving algorithm TinyML OBD-II edge IoT
ISSN:	1424-8220, 1424-8220
On-line přístup:	Získat plný text
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