A hybrid framework combining microwave sensing and deep learning for real-time soil volumetric water content estimation
Adel M. Soliman, Amr Elbrashy, Amr H. Hussien, Ashraf Elmorsy · 2026
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Description
Adel Soliman and co-authors build a system in 2026 that reads soil moisture in real time by bouncing microwaves off the ground and letting a neural network decode the signal. The classic way to measure water in soil is to dry a sample in an oven, which destroys it and takes a full day. Builders and engineers often need the answer on site, at once.
Their kit pairs a radar at a common wireless frequency with a small low cost computer at the edge. The reflected power tracks how the soil stores charge, which shifts with water content. A network first sorts the soil as sand, clay, or mixed. Then a fitted curve turns the signal into a water figure for that soil type. Fast, in place moisture reads could speed earthworks and farm choices alike.
Catalog record
| CREATOR | Adel M. Soliman, Amr Elbrashy, Amr H. Hussien, Ashraf Elmorsy |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 84 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |