Ramli, Muhammad Shahrul Azwan and Zainal Abidin, Mohamad Shukri and Pui, Boon Hean and Abd. Rahman, Mohd. Amiruddin and Perumal, Thinagaran and Md. Reba, Mohd. Nadzri (2022) Empirical based irrigation model using predicted soil moisture for durian plantation. In: 3rd International Conference on Control, Instrumentation and Mechatronics Engineering, CIM 2022, 2 March 2022 - 3 March 2022, Virtual, Online.
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Official URL: http://dx.doi.org/10.1007/978-981-19-3923-5_23
Abstract
It is vital to the agricultural activities to have sufficient water supply for its operation and maintenance mainly for cultivation to keep it in good condition Therefore, it is important to determine the soil moisture levels existing while designing a precise irrigation system. Installing soil moisture sensors in each tree is complicated or excessively expensive. Forecasting the value using climate data is a viable solution in this scenario. Climate data are used to forecast soil moisture and then utilized in this irrigation model. This study uses an Artificial Neural Network (ANN) to forecast soil moisture values. The statistical method is used to determine the predicted values’ correctness. After the process, the irrigation volume and schedule are calculated based on the most accurate prediction findings.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Uncontrolled Keywords: | artificial neural network, durian farming, irrigation system, machine learning, soil moisture prediction |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Faculty of Engineering - School of Electrical |
| ID Code: | 100729 |
| Deposited By: | Yanti Mohd Shah |
| Deposited On: | 30 Apr 2023 10:20 |
| Last Modified: | 30 Apr 2023 10:20 |
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