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Direct lightweight temporal compression for wearable sensor data

Authors :
Klus, Lucie
Klus, Roman
Lohan, Elena Simona
Granell, Carlos
Talvitie, Jukka
Valkama, Mikko
Nurmi, Jari
Tampere University
Electrical Engineering
Research group: System-on-Chip for GNSS, Wireless Communications and Cyber-Physical Embedded Computing
Research group: Wireless Communications and Positioning
Source :
Repositori Universitat Jaume I, Universitat Jaume I, IEEE Sensors Letters
Publication Year :
2021
Publisher :
IEEE, 2021.

Abstract

Emerging technologies enable massive deployment of wireless sensor networks across many industries. Internet of Things (IoT) devices are often deployed in critical infrastructure or health monitoring and require fast reaction time,reasonable accuracy, and high energy efficiency. In this letter, we introduce a lossy compression method for time-seriesdata, named direct lightweight temporal compression (DLTC), enabling energy-efficient data transfer for power-restricteddevices. Our method is based on the lightweight temporal compression method, targeting further reconstruction errorminimization and complexity reduction. This letter highlights the key advantages of the proposed method and evaluates themethod’s performance on several sensor-based, time-series data types. We prove that DLTC outperforms the consideredbenchmark methods in compression efficiency at the same reconstruction error level.

Details

Database :
OpenAIRE
Journal :
Repositori Universitat Jaume I, Universitat Jaume I, IEEE Sensors Letters
Accession number :
edsair.doi.dedup.....e340c9de6711d8a4cfdc7671ecac671b