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Bashir, RN, Bajwa, IS, Abbas, MZ, Rehman, A, Saba, T, Bahaj, SA and Kolivand, H (2022) Internet of things (IoT) assisted soil salinity mapping at irrigation schema level. Applied Water Science, 12 (5). ISSN 2190-5487
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Abstract
Soil salinity accumulates a high concentration of salts in soils that interfere with normal plant growth. Early detection and quantification of soil salinity are essential to effectively deal with soil salinity in agriculture. Soil salinity quantification and mapping at the irrigation scheme level are vital to evaluating saline soil's reclamation activity. Existing solutions of salinity mapping are costly, time-consuming, and inadequate for applications at the irrigation scheme level. Internet of Things (IoT) assisted salinity mapping at the irrigation scheme level is proposed to quantify and map the soil salinity in agriculture. The proposed IoT-assisted salinity mapping characterizes the soil salinity in terms of Electric Conductivity, pH, and Total Dissolved Salts. The proposed IoT-assisted salinity mapping effectively observes impacts of reclamation activities in saline soil by frequent observation of soil salinity cost-effectively. The accuracy of proposed IoT-assisted salinity mapping is evaluated against the standard method of salinity measurements. The proposed IoT-assisted salinity mapping is cost-effective, and portable, which is very useful for site-specific treatments and soil zones management in saline soils.
| Item Type: | Article |
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| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software S Agriculture > S Agriculture (General) T Technology > T Technology (General) |
| Divisions: | Computer Science & Mathematics |
| Publisher: | Springer Science and Business Media LLC |
| SWORD Depositor: | A Symplectic |
| Date Deposited: | 01 Dec 2022 10:57 |
| Last Modified: | 01 Dec 2022 10:57 |
| DOI or ID number: | 10.1007/s13201-022-01619-1 |
| URI: | https://researchonline.ljmu.ac.uk/id/eprint/18243 |
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