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

出版年:	Sensors
主要な著者:	Gabriel Signoretti, Marianne Silva, Pedro Andrade, Ivanovitch Silva, Emiliano Sisinni, Paolo Ferrari
フォーマット:	論文
言語:	英語
出版事項:	MDPI AG 2021-06-01
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