{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T05:10:43Z","timestamp":1788844243465,"version":"build-2803163510"},"reference-count":30,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2026,9,6]],"date-time":"2026-09-06T00:00:00Z","timestamp":1788652800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001780","name":"RMIT University","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100001780","id-type":"DOI","asserted-by":"crossref"}]},{"id":[{"id":"https:\/\/ror.org\/04ttjf776","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This work presents a compact square complementary split-ring resonator (CSRR) microwave sensor, combined with a machine-learning-based calibration strategy, to achieve superior texture-aware soil moisture quantification. Implemented on a Rogers RO3010 substrate with a 20 \u00d7 30 mm2 footprint and operating near 1.3 GHz, the sensor exploits shifts in resonance\/notch frequency and insertion loss (S21) to probe both the real and imaginary components of the soil\u2019s complex permittivity. Full-wave 3D electromagnetic simulations guided optimisation of the CSRR topology and T-shaped microstrip feedline, yielding strong field confinement, high quality factor, and high Frequency Detection Resolution (FDR). Experiments on sand and loam across 0\u201330% and 0\u201340% moisture content ranges, respectively, demonstrate FDR values of 6.09 MHz (sand) and 6.86 MHz (loam), enabling discrimination of subtle permittivity changes. Several calibration strategies are developed and compared for complex permittivity extraction from measured S-parameters: linear and polynomial regression, a multivariable least-squares sensitivity-matrix model, and a delta-referenced multilayer perceptron (MLP) with z-score standardization. While polynomial and least-squares models significantly outperform linear regression (R2 &gt; 0.997), the MLP combined with the optimized CSRR architecture delivers the best performance, achieving near-ideal accuracy (R2 \u2248 1, MAE &lt; 0.001, RMSE &lt; 0.001) for both soil types. These results demonstrate that the synergy between the novel CSRR sensor design and data-driven MLP calibration enables high-resolution, robust, and field-deployable soil moisture sensing, offering a compelling solution for next-generation agricultural and geotechnical monitoring systems.<\/jats:p>","DOI":"10.3390\/s26175665","type":"journal-article","created":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T12:12:25Z","timestamp":1788783145000},"page":"5665","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["High-Resolution CSRR-Based Microwave Sensor for Soil Moisture Content Monitoring"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-0714-7622","authenticated-orcid":false,"given":"Salman","family":"Alduwish","sequence":"first","affiliation":[{"name":"School of Engineering, RMIT University, Melbourne, VIC 3000, Australia"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"investigation","vocabulary":"credit"},{"role":"visualization","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"resources","vocabulary":"credit"},{"role":"software","vocabulary":"credit"},{"role":"validation","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"formal-analysis","vocabulary":"credit"}]},{"given":"Yongxiang","family":"Li","sequence":"additional","affiliation":[{"name":"School of Engineering, RMIT University, Melbourne, VIC 3000, Australia"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"supervision","vocabulary":"credit"},{"role":"validation","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3200-6821","authenticated-orcid":false,"given":"James","family":"Scott","sequence":"additional","affiliation":[{"name":"School of Engineering, RMIT University, Melbourne, VIC 3000, Australia"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"supervision","vocabulary":"credit"},{"role":"validation","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"given":"Akram","family":"Hourani","sequence":"additional","affiliation":[{"name":"School of Engineering, RMIT University, Melbourne, VIC 3000, Australia"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"supervision","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8340-1058","authenticated-orcid":false,"given":"Nasir","family":"Mahmood","sequence":"additional","affiliation":[{"name":"School of Science, RMIT University, Melbourne, VIC 3000, Australia"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"supervision","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"S.U., S.L., and Singh, D.N. (2021). Keynote Speech: Significance of Soil Moisture Content and its Measurement Techniques. AIJR Proceedings, AIJR Publisher.","DOI":"10.21467\/proceedings.112.keynote4"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"570","DOI":"10.47115\/bsagriculture.1519668","article-title":"On Various Soil Moisture Measurement Techniques Available in the Literature","volume":"7","author":"Hasar","year":"2024","journal-title":"Black Sea J. Agric."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Yu, K. (2021). Soil Moisture Measurement, Springer.","DOI":"10.1007\/978-981-16-0411-9_9"},{"key":"ref_4","first-page":"32","article-title":"Review of research progress on soil moisture sensor technology","volume":"14","author":"Yu","year":"2021","journal-title":"Int. J. Agric. Biol. Eng."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"23713","DOI":"10.1109\/JSEN.2023.3307652","article-title":"Soil Moisture Monitoring System Based on Metamaterial-Inspired Microwave Sensor for Precision Agriculture Applications","volume":"23","year":"2023","journal-title":"IEEE Sens. J."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Gao, B., Chen, Z., Gong, X., Wang, P., and Tong, L. (2020). Design and Experiment of Microwave Soil Moisture Sensor. Proceedings of the IGARSS 2020\u20142020 IEEE International Geoscience and Remote Sensing Symposium, IEEE.","DOI":"10.1109\/IGARSS39084.2020.9323196"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"422","DOI":"10.1002\/mop.33119","article-title":"Analysis of metamaterial-inspired soil moisture microwave sensor","volume":"64","author":"Silva","year":"2021","journal-title":"Microw. Opt. Technol. Lett."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Oliveira, J.G.D., Pinto, E.N.M.G., Silva Neto, V.P., and D\u2019Assun\u00e7\u00e3o, A.G. (2020). CSRR-Based Microwave Sensor for Dielectric Materials Characterization Applied to Soil Water Content Determination. Sensors, 20.","DOI":"10.3390\/s20010255"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2335","DOI":"10.1080\/03772063.2023.2185297","article-title":"A Planar RF-Sensor Using Concentric Complementary Open-Ring Resonator for Dielectric Characterization & On-Field Testing of Soil","volume":"70","author":"Sagar","year":"2023","journal-title":"IETE J. Res."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"29945","DOI":"10.1109\/JSEN.2024.3428315","article-title":"Prototype of Circular Split Ring Resonator-Based Sensor for Estimating Soil Moisture as a Function of Soil Particle Distribution","volume":"24","author":"Kaur","year":"2024","journal-title":"IEEE Sens. J."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"De Sousa Silva, I., De A Lira, R.V., Barros, I.B.T., and Campos, A.L.P.S. (2025). A Proposed Microwave Resonator Sensor for Measuring Soil Water Content. Proceedings of the 2025 SBMO\/IEEE MTT-S International Microwave and Optoelectronics Conference (IMOC), IEEE.","DOI":"10.1109\/IMOC65414.2025.11365840"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Yan, Y., Lin, X., Chen, Z., Cai, Y., and Chen, Z. (2020). A Microwave Sensor for Leaf Moisture Detection Based on Split-Ring Resonator. Proceedings of the 2020 IEEE Asia-Pacific Microwave Conference (APMC), IEEE.","DOI":"10.1109\/APMC47863.2020.9331538"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"103968","DOI":"10.1016\/j.asej.2025.103968","article-title":"Coupling dielectric physics with calibration models for soil moisture sensing: Progress and perspectives","volume":"17","author":"Awais","year":"2026","journal-title":"Ain Shams Eng. J."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Pe\u010dan, U., Kastelec, D., and Pintar, M. (2020, January 4\u20138). Laboratory calibration of different soil moisture sensors in various soil types. Proceedings of the 22nd EGU General Assembl, Online.","DOI":"10.5194\/egusphere-egu2020-5956"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"118808","DOI":"10.1016\/j.measurement.2025.118808","article-title":"Correcting the moisture\u2013permittivity conversion functions for selected soil-specific properties in the 20 MHz\u20133 GHz frequency range for accurate soil moisture measurement","volume":"257","author":"Kafarski","year":"2026","journal-title":"Measurement"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Shan, Y.T., and Zheng, Z.K. (2023). Machine Learning Regression to Predict Soil Moisture in Domestic Garden Environments. Proceedings of the 2023 14th International Conference on Mechanical and Intelligent Manufacturing Technologies (ICMIMT), IEEE.","DOI":"10.1109\/ICMIMT59138.2023.10199334"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Zhang, X., Lin, Z., and Sun, X. (2023). Developing Machine Learning and Deep Learning Soil Moisture Models for Precision Agricultural Applications. Proceedings of the 2023 ASABE Annual International Meeting, American Society of Agricultural and Biological Engineers.","DOI":"10.13031\/aim.202300205"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Taheri, M., Bigdeli, M., Imanian, H., and Mohammadian, A. (2025). An Overview of Machine-Learning Methods for Soil Moisture Estimation. Water, 17.","DOI":"10.3390\/w17111638"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"115042","DOI":"10.1016\/j.sna.2024.115042","article-title":"A planar DGS sensor for moisture analysis in civil construction aggregates","volume":"367","author":"Pereira","year":"2024","journal-title":"Sens. Actuators A Phys."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"15023","DOI":"10.1109\/JSEN.2025.3545313","article-title":"A Low-Profile Self-Similar Geometry-Based Microwave Planar Sensor for Assessing the Impact of Organic Matter Content on Soil Field Capacity","volume":"25","author":"Kaur","year":"2025","journal-title":"IEEE Sens. J."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"7770","DOI":"10.1109\/JSEN.2024.3355762","article-title":"Affordable Microwave Soil Moisture Detector","volume":"24","author":"Iaccheri","year":"2024","journal-title":"IEEE Sens. J."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1000708","DOI":"10.1109\/TGRS.2025.3537338","article-title":"Design and Fabrication of a Low-Profile Planar Sensor for the Estimation of Plant-Available Water in Different Textured Soils","volume":"63","author":"Kaur","year":"2025","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_23","unstructured":"Cihlar, J. (1974). Dielectric Properties of Soils as a Function of Moisture Content, The University of Kansas Space Technology Center. CRES Technical Report."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Liu, W., Sun, H., and Xu, L. (2018). A Microwave Method for Dielectric Characterization Measurement of Small Liquids Using a Metamaterial-Based Sensor. Sensors, 18.","DOI":"10.3390\/s18051438"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Alahnomi, R.A., Zakaria, Z., Yussof, Z.M., Althuwayb, A.A., Alhegazi, A., Alsariera, H., and Rahman, N.A. (2021). Review of Recent Microwave Planar Resonator-Based Sensors: Techniques of Complex Permittivity Extraction, Applications, Open Challenges and Future Research Directions. Sensors, 21.","DOI":"10.3390\/s21072267"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"23076","DOI":"10.1038\/s41598-024-72061-3","article-title":"Multi-parameter simultaneous extraction with a novel microwave sensor based on coupled resonators","volume":"14","author":"Juan","year":"2024","journal-title":"Sci. Rep."},{"key":"ref_27","unstructured":"Goodfellow, I., Bengio, Y., and Courville, A. (2016). Deep Learning, MIT Press."},{"key":"ref_28","unstructured":"Huang, L., Qin, J., Zhou, Y., Zhu, F., Liu, L., and Shao, L. (2020). Normalization techniques in training DNNs: Methodology, analysis, and application. arXiv."},{"key":"ref_29","first-page":"145","article-title":"Dielectric behavior of soil as a function of frequency, temperature, moisture content and soil texture: A deep neural networks based regression model","volume":"56","author":"Palta","year":"2022","journal-title":"J. Microw. Power Electromagn. Energy"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"732","DOI":"10.1016\/j.neunet.2021.08.015","article-title":"On the approximation of functions by tanh neural networks","volume":"143","author":"Lanthaler","year":"2021","journal-title":"Neural Netw."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/26\/17\/5665\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T04:27:09Z","timestamp":1788841629000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/26\/17\/5665"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9,6]]},"references-count":30,"journal-issue":{"issue":"17","published-online":{"date-parts":[[2026,9]]}},"alternative-id":["s26175665"],"URL":"https:\/\/doi.org\/10.3390\/s26175665","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,9,6]]}}}