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Direct lightweight temporal compression for wearable sensor data
- 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.
- Subjects :
- internet of things (IoT)
Computer science
benchmark testing
Real-time computing
Wearable computer
upper bound
Sensor signal processing, data compression, direct lightweight temporal compression (DLTC), Internet of Things (IoT), lightweight temporal compression (LTC), redundancy reduction, time series
complexity theory
Lossy compression
01 natural sciences
Critical infrastructure
characterization
Electrical and Electronic Engineering
Instrumentation
data compression
direct lightweight temporal compression (DLTC)
213 Electronic, automation and communications engineering, electronics
sensor signal processing
010401 analytical chemistry
0104 chemical sciences
performance evaluation
lightweight temporal compression (LTC)
Key (cryptography)
Benchmark (computing)
sensor phenomena
time series
Wireless sensor network
redundancy reduction
Data transmission
Data compression
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- Repositori Universitat Jaume I, Universitat Jaume I, IEEE Sensors Letters
- Accession number :
- edsair.doi.dedup.....e340c9de6711d8a4cfdc7671ecac671b