Estimating Soil Moisture with COTS Hardware using BLE’s Angle-of-Arrival Feature

Measuring soil moisture for agriculture is currently a hot research topic. Wireless sensor networks, that transmit readings from moisture sensors are a main contender for this task. However, sensors used in these networks often suffer from corrosion. Here, we propose a more scalable solution, using Commercial Off-The-Shelf (COTS) Bluetooth Low Energy (BLE) beacons with no additional sensor. Because of the variety of their application areas, they are available at smaller unit costs. In comparison to many moisture sensors, they can be fully encapsulated in a case for protection against corrosion. Similar solutions have been proposed using Received Signal Strength Indicator (RSSI) readings of the sensor nodes. We propose to instead use the Angle-of-Arrival (AoA), model the influence of different error sources, and calculate the expected measurement accuracy.

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Publication Details

Published
2024-09-09
DOI
https://doi.org/10.1109/lcn60385.2024.10639811
Primary Topic
Soil Moisture and Remote Sensing
Type
article
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article

Estimating Soil Moisture with COTS Hardware using BLE’s Angle-of-Arrival Feature

Lennart Kaiser, Thomas Hänel
Soil Moisture and Remote Sensing
article

Estimating Soil Moisture with COTS Hardware using BLE’s Angle-of-Arrival Feature

Lennart Kaiser, Thomas Hänel
article en

Abstract

Measuring soil moisture for agriculture is currently a hot research topic. Wireless sensor networks, that transmit readings from moisture sensors are a main contender for this task. However, sensors used in these networks often suffer from corrosion. Here, we propose a more scalable solution, using Commercial Off-The-Shelf (COTS) Bluetooth Low Energy (BLE) beacons with no additional sensor. Because of the variety of their application areas, they are available at smaller unit costs. In comparison to many moisture sensors, they can be fully encapsulated in a case for protection against corrosion. Similar solutions have been proposed using Received Signal Strength Indicator (RSSI) readings of the sensor nodes. We propose to instead use the Angle-of-Arrival (AoA), model the influence of different error sources, and calculate the expected measurement accuracy.

Openalex Percentile: Top 86%
Soil Moisture and Remote Sensing
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