Simulation framework for assessing VWC performance in low-cost smart agriculture sensors

Nicola Papini, Andrea Scorzoni, Pisana Placidi, Manuela Cecconi, Chiara Petroselli, Carmine Villani Delle Vergini, Domenico Caputo, Nicola Lovecchio, Alessandro Tarantino

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

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Abstract

The use of Internet of Things (IoT) devices in agriculture is increasing over time due to the benefits of productivity and resources. Several technologies and sensors may be found on the market to investigate parameters of interest such as the soil salinity and water content. PCB sensors are widely used due to their limited cost, making them suitable for large-scale applications. However, their performances are strictly related to several factors, for example, their installation inside the soil. Due to the sensor placing procedure, air gaps are usually present at the soil/sensor interface reducing significantly their performance. The case may be even worse in wet soils at high water content, in which the air gaps may be filled by free water. In this paper, the effect of air gaps is investigated through Finite Element Method (FEM) with a common commercial sensor: the SKU:SEN0193. Two types of "gap" profiles have been implemented in FEM simulations: a parallelepiped gap along the whole sensor and an exponential-profiled gap. Results are obtained at four frequencies of interest in the range 10 kHz - 100 kHz showing a significant impact in all the considered cases. In the best-considered case, the relative errors range from 0.7% to 26%.
Original languageEnglish
Title of host publication2025 IEEE Sensors Applications Symposium (SAS)
PublisherIEEE
Pages1-6
Number of pages6
ISBN (Electronic)979-8-3315-1193-7
ISBN (Print)979-8-3315-1194-4
DOIs
Publication statusPublished - 13 Aug 2025

Publication series

Name2025 IEEE Sensors Applications Symposium (SAS)
PublisherIEEE
ISSN (Print)2994-9300
ISSN (Electronic)2766-3078

Keywords

  • Soil Water Content Sensor
  • Finite Element Method (FEM)
  • Low-cost Capacitive Sensor
  • IoT Sensor
  • Smart Agriculture

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