Smart Irrigation Prediction using Artificial Neural Network (ANN) with Evapotranspiration Rate Equations and Internet of Things (IoT) for Paddy Field
Muhammad Zahid bin Hilmi1, Toni Anwar2, Dayang Rohaya Awang Rambli3
1Muhammad Zahid bin Hilmi*, CIS Department, Universiti Teknologi PETRONAS, Tronoh, Malaysia.
2Toni Anwar, CIS Department, Universiti Teknologi PETRONAS, Tronoh, Malaysia.
3Dayang Rohaya Awang Rambli, CIS Department, Universiti Teknologi PETRONAS, Tronoh, Malaysia.
Manuscript received on April 05, 2020. | Revised Manuscript received on April 17, 2020. | Manuscript published on April 30, 2020. | PP: 417-425 | Volume-9 Issue-4, April 2020. | Retrieval Number: C6294029320/2020©BEIESP | DOI: 10.35940/ijeat.C6294.049420
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: It is estimated that by 2050, the world’s population will increase to 10 billion people and water scarcity is going to be a major problem due to an increase number of populations with limited water resources. One of the ways to tackle this problem is by having a precision irrigation which is by estimating the crops water need in which it can improve water utilization. This research is very suitable to be implemented for paddy since paddy consumed a lot of water compared to other types of crops. In order to be able to do it, ANN and Evapotranspiration Rate equation will be used to develop a prediction model to estimate water lost. The prediction model in theory will analyze the historical data and compared it with current data collected in the field and predict water needs based on the output concluded. IoT will act as monitoring and controlling platform for irrigation by automating the irrigation which in result, better water utilization. Prediction model and IoT combination proved that better water utilization can be achieved. The targeted result will be to achieve better water utilization using prediction model and IoT.
Keywords: Artificial Neural Network, Internet of Things, Evapotranspiration Rate, Irrigation, Paddy