An Evolving TinyML Compression Algorithm for IoT Environments Based on Data Eccentricity

Currently, the applications of the Internet of Things (IoT) generate a large amount of sensor data at a very high pace, making it a challenge to collect and store the data. This scenario brings about the need for effective data compression algorithms to make the data manageable among tiny and batter...

詳細記述

書誌詳細

主要な著者:	Gabriel Signoretti, Marianne Silva, Pedro Andrade, Ivanovitch Silva, Emiliano Sisinni, Paolo Ferrari
フォーマット:	Artigo
言語:	Inglês
出版事項:	MDPI AG 2021-06-01
シリーズ:	Sensors
主題:	internet of things online data compression TinyML eccentricity evolving algorithm LPWAN
オンライン･アクセス:	https://www.mdpi.com/1424-8220/21/12/4153
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