TESTING GROUND CONDITIONS FOR EFFECTIVE BURIED SENSOR WIRELESS LORAWAN SIGNAL TRANSMISSION
Abstract. Long-range, low-power, wide-area network modulation technique (LoRa) is already used in a variety of fields, such as agriculture and healthcare, to reliably transmit a small amount of data above ground. Research measuring the reliability and signal strength of LoRa devices underground, however, is rare. The purpose of this study is to test the signal strength from LoRa devices in a variety of shallow-depth, underground conditions. The experiments are divided into two parts. The first experiment tries to determine the relationship between signal strength and device depth underground. The second experiment tries to determine the relationship between signal strength and soil moisture content. The experimental results are compared with the Modified-Friis model and CRIM-Fresnel model. The results show a decreasing trend in signal strength with increasing depth. The signal strength of LoRa devices in clay is weaker than in sand. However, soil moisture experiments demonstrate that as the soil moisture in sand increases the signal strengthens. In clay, as the soil moisture increases the signal weakens.
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource
- Language
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Englisch
- Bibliographic citation
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TESTING GROUND CONDITIONS FOR EFFECTIVE BURIED SENSOR WIRELESS LORAWAN SIGNAL TRANSMISSION ; volume:XLVIII-4/W5-2022 ; year:2022 ; pages:83-89 ; extent:7
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ; XLVIII-4/W5-2022 (2022), 83-89 (gesamt 7)
- Creator
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Lai, Y.
Lin, J.
Zhang, Z.
Zhu, H.
Narsilio, G.
Tomko, M.
Jowett, K.
- DOI
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10.5194/isprs-archives-XLVIII-4-W5-2022-83-2022
- URN
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urn:nbn:de:101:1-2022102005364837541672
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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15.08.2025, 7:33 AM CEST
Data provider
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Lai, Y.
- Lin, J.
- Zhang, Z.
- Zhu, H.
- Narsilio, G.
- Tomko, M.
- Jowett, K.
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