TDD LoRa and Delta Encoding in Low-Power Networks of Environmental Sensor Arrays for Temperature and Deformation Monitoring
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Published:2023-03-22
Issue:7
Volume:95
Page:831-843
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ISSN:1939-8018
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Container-title:Journal of Signal Processing Systems
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language:en
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Short-container-title:J Sign Process Syst
Author:
Wielandt StijnORCID, Uhlemann SebastianORCID, Fiolleau SylvainORCID, Dafflon BaptisteORCID
Abstract
AbstractDensely distributed sensor networks can revolutionize environmental observations by providing real-time data with an unprecedented spatiotemporal resolution. However, field deployments often pose unique challenges in terms of power provisions and wireless connectivity. We present a framework for wirelessly connected distributed sensor arrays for near-surface temperature and/or deformation monitoring. Our research focuses on a novel time division duplex implementation of the LoRa protocol, enabling battery powered base stations and avoiding collisions within the network. In order to minimize transmissions and improve battery life throughout the network, we propose a dedicated delta encoding algorithm that utilizes the spatial and temporal similarity in the acquired data sets. We implemented the developed technologies in a AA battery powered hardware platform that can be used as a wireless data logger or base station, and we conducted an assessment of the power consumption. Without data compression, the projected battery life for a data logger is 4.74 years, and a wireless base stations can last several weeks or months depending on the amount of network traffic. The delta encoding algorithm can further improve this battery life with a factor of up to 3.50. Our results demonstrate the viability of the proposed methods for low-power environmental wireless sensor networks.
Funder
Biological and Environmental Research
Publisher
Springer Science and Business Media LLC
Subject
Hardware and Architecture,Modeling and Simulation,Information Systems,Signal Processing,Theoretical Computer Science,Control and Systems Engineering
Reference34 articles.
1. Ho, C. K., Robinson, A., Miller, D. R., & Davis, M. J. (2005). Overview of sensors and needs for environmental monitoring. Sensors, 5(1), 4–37. https://doi.org/10.3390/s5010004 2. Strachan, S., Kelsey, E. P., Brown, R. F., Dascalu, S., Harris, F., Kent, G., Lyles, B., McCurdy, G., Slater, D., & Smith, K. (2016). Filling the Data Gaps in Mountain Climate Observatories Through Advanced Technology, Refined Instrument Siting, and a Focus on Gradients. Mountain Research and Development, 36(4), 518–527. https://doi.org/10.1659/MRD-JOURNAL-D-16-00028.1 3. Cable, W. L., Romanovsky, V. E., & Jorgenson, M. T. (2016). Scaling-up permafrost thermal measurements in western alaska using an ecotype approach. The Cryosphere, 10(5), 2517–2532. https://doi.org/10.5194/tc-10-2517-2016 4. Léger, E., Dafflon, B., Robert, Y., Ulrich, C., Peterson, J. E., Biraud, S. C., Romanovsky, V. E., & Hubbard, S. S. (2019). A distributed temperature profiling method for assessing spatial variability in ground temperatures in a discontinuous permafrost region of alaska. The Cryosphere, 13(11), 2853–2867. https://doi.org/10.5194/tc-13-2853-2019 5. Ramesh, M. V. (2014). Design, development, and deployment of a wireless sensor network for detection of landslides. Ad Hoc Networks, 13, 2–18. https://doi.org/10.1016/j.adhoc.2012.09.002
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