Development and Field Validation of WaziSense, a Low-Cost Solar-Powered IoT Smart Tensiometer for Soil-Water Monitoring and Irrigation Scheduling in Semi-Arid Agriculture.

Hassine Ben Abdallah, Liliya Naui, Mourad Bakri, Felix Markwordt, Mohamed Abdur Rahim, Corentin Dupont, Mohamed Ali Ben Abdallah, Mourad Rezig

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Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

8 authors.

Hassine Ben AbdallahNational Institute for Research in Rural Engineering, Water and Forestry (INRGREF), University of Carthage, Ariana 2080, Tunisia.ORCID 0000-0002-4627-6526

Liliya NauiNational Institute for Research in Rural Engineering, Water and Forestry (INRGREF), University of Carthage, Ariana 2080, Tunisia.ORCID 0009-0003-3072-806X

Mourad BakriNational Institute for Research in Rural Engineering, Water and Forestry (INRGREF), University of Carthage, Ariana 2080, Tunisia.ORCID 0009-0002-9759-9832

Felix MarkwordtWaziup e.V., Räcknitzhöhe 50/52, 01217 Dresden, Germany.ORCID 0009-0006-4514-4085

Mohamed Abdur RahimWaziup e.V., Räcknitzhöhe 50/52, 01217 Dresden, Germany.

Corentin DupontWaziup e.V., Räcknitzhöhe 50/52, 01217 Dresden, Germany.ORCID 0000-0002-9076-7613

Mohamed Ali Ben AbdallahNational Institute for Research in Rural Engineering, Water and Forestry (INRGREF), University of Carthage, Ariana 2080, Tunisia.ORCID 0000-0003-4699-6483

Mourad RezigNational Institute for Research in Rural Engineering, Water and Forestry (INRGREF), University of Carthage, Ariana 2080, Tunisia.ORCID 0000-0003-0908-7598

Funding

EcofertiS project PRIMA 2 ANR-24-P013-0010OSIRRIS project TUNGER 2+2 20_046

6 · The paper itself

Abstract

Water scarcity in semi-arid regions makes efficient irrigation scheduling a priority, yet farm-level adoption of soil-moisture monitoring remains limited by the cost, low portability and installation complexity of commercial sensing systems. This study presents the development and field validation of WaziSense, a low-cost, solar-powered Internet-of-Things (IoT) smart tensiometer, developed within the OSIRRIS platform for soil-water monitoring and irrigation scheduling. The device couples a Watermark granular-matrix sensor and a DS18B20 temperature probe to an ATmega328P microcontroller (Arduino Pro-Mini, 3.3 V, 8 MHz) with long-range LoRa communication and a maximum-power-point-tracking (MPPT) solar-charging stage, logging soil matric potential and soil temperature every 15 min. An open-source edge/cloud stack (WaziGate, WaziApp) retrieves weather forecasts from an open API and runs an automated machine learning (AutoML) regression pipeline that forecasts soil-water dynamics and the time to a user-defined threshold, from which irrigation is scheduled and its applied volume verified by a flow meter. The system was deployed at three bioclimatic sites in Tunisia (durum wheat at Cherfech, citrus at Nabeul, apple at Sbeitla), with tensiometers installed at 20 and 40 cm depths, and validated against commercial 10HS capacitive probes coupled to a ZL6 data logger, with which the co-located readings were significantly correlated (r = 0.81). Calibrated readings showed a strong relationship between soil-water content and soil-water potential (R

Indexed as

Agriculture 4.0automated machine learning (AutoML)deficit irrigationInternet of Thingsirrigation forecastingirrigation schedulingLoRasemi-aridsmart tensiometersoil matric potentialsoil-water monitoringWaziSense

Identifiers

PMID42739968

DOI10.3390/s26175348

PMCPMC13567938

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.