Soil monitoring represents an essential aspect of agriculture nowadays. It is known, indeed, that soil parameters serve as important indicators of the growth of plants and field conditions, and their analysis is particularly useful to avoid waste of resources, such as water. In this paper, we propose a novel Sensing-without-Sensors System that has been specifically designed to measure the soil moisture without sensors but based on underground wireless transmission. As a matter of fact, radio waves propagation is affected by the soil moisture content; therefore, it is possible to estimate it based on the propagation characteristics. To do so, we exploit supervised machine learning algorithms that are able to derive the soil moisture starting from the Received Signal Strength Indicator (RSSI) measured by End Devices (EDs) transmitting underground using LoRa modulation. The benefits provided by our system lie in the reduction of the cost with respect to standard monitoring solutions, which would require actual sensors deployed over radio transceiver, and in the possibility to estimate the soil moisture of a volume of the soil and not of a single point, as done by state-of-the-art systems.

A Sensing-without-Sensors System for Soil Moisture Estimation

Marini R.
;
Testi E.;Buratti C.;Giorgetti A.;Verdone R.
2021

Abstract

Soil monitoring represents an essential aspect of agriculture nowadays. It is known, indeed, that soil parameters serve as important indicators of the growth of plants and field conditions, and their analysis is particularly useful to avoid waste of resources, such as water. In this paper, we propose a novel Sensing-without-Sensors System that has been specifically designed to measure the soil moisture without sensors but based on underground wireless transmission. As a matter of fact, radio waves propagation is affected by the soil moisture content; therefore, it is possible to estimate it based on the propagation characteristics. To do so, we exploit supervised machine learning algorithms that are able to derive the soil moisture starting from the Received Signal Strength Indicator (RSSI) measured by End Devices (EDs) transmitting underground using LoRa modulation. The benefits provided by our system lie in the reduction of the cost with respect to standard monitoring solutions, which would require actual sensors deployed over radio transceiver, and in the possibility to estimate the soil moisture of a volume of the soil and not of a single point, as done by state-of-the-art systems.
2021 IEEE International Workshop on Metrology for Agriculture and Forestry, MetroAgriFor 2021 - Proceedings
192
196
Marini R.; Testi E.; Buratti C.; Giorgetti A.; Verdone R.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/854382
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