A1 Journal article (refereed)
Efficiency of temporal sensor data compression methods to reduce LoRa-based sensor node energy consumption (2022)

Väänänen, O., & Hämäläinen, T. (2022). Efficiency of temporal sensor data compression methods to reduce LoRa-based sensor node energy consumption. Sensor Review, 42(5), 503-516. https://doi.org/10.1108/sr-10-2021-0360

JYU authors or editors

Publication details

All authors or editors: Väänänen, Olli; Hämäläinen, Timo

Journal or series: Sensor Review

ISSN: 0260-2288

eISSN: 1758-6828

Publication year: 2022

Publication date: 28/06/2022

Volume: 42

Issue number: 5

Pages range: 503-516

Publisher: Emerald

Publication country: United Kingdom

Publication language: English

DOI: https://doi.org/10.1108/sr-10-2021-0360

Publication open access: Openly available

Publication channel open access: Partially open access channel

Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/82093


Minimizing the energy consumption in a wireless sensor node is important for lengthening the lifetime of a battery. Radio transmission is the most energy-consuming task in a wireless sensor node, and by compressing the sensor data in the online mode, it is possible to reduce the number of transmission periods. This study aims to demonstrate that temporal compression methods present an effective method for lengthening the lifetime of a battery-powered wireless sensor node.

In this study, the energy consumption of LoRa-based sensor node was evaluated and measured. The experiments were conducted with different LoRaWAN data rate parameters, with and without compression algorithms implemented to compress sensor data in the online mode. The effect of temporal compression algorithms on the overall energy consumption was measured.

Energy consumption was measured with different LoRaWAN spreading factors. The LoRaWAN transmission energy consumption significantly depends on the spreading factor used. The other significant factors affecting the LoRa-based sensor node energy consumption are the measurement interval and sleep mode current consumption. The results show that temporal compression algorithms are an effective method for reducing the energy consumption of a LoRa sensor node by reducing the number of LoRa transmission periods.

This paper presents with a practical case that it is possible to reduce the overall energy consumption of a wireless sensor node by compressing sensor data in online mode with simple temporal compression algorithms.

Keywords: Internet of things; energy efficiency; energy saving; electricity consumption; sensors; accumulators; batteries; algorithms

Free keywords: internet of things; energy efficiency; compression; sensor data; edge computing

Contributing organizations

Ministry reporting: Yes

Reporting Year: 2022

Preliminary JUFO rating: 1

Last updated on 2023-10-01 at 13:49