Smart Agriculture Water System Using Crop Water Stress Index and Weather Prediction

Authors

  • Jason Timotius Purwoko Bina Nusantara University
  • Taurean Orlin Wingardi Bina Nusantara University
  • Benfano Soewito Bina Nusantara University

DOI:

https://doi.org/10.21512/commit.v17i1.8435

Keywords:

Smart Agriculture Water System, Crop Water Stress Index (CWSI), Weather Prediction

Abstract

Water is essential for crops to grow well. However, overwatered or underwatered plants hinder growth and produce less fruit than plants with sufficient watering. Using the Internet of Things (IoT), agriculture can be controlled to achieve the best condition for plants to grow. The research aims to develop a watering system based on Crop Water Stress Index (CWSI), soil moisture content, and weather prediction. By evaluating CWSI and soil moisture content, the research makes a smart watering system that efficiently monitors water concentration in a plant. However, there is a flaw in the watering system that water from the rain makes the plant overwatered. So, using weather prediction can delay irrigation to save water and produce a better stress index result. Next, the research compares the watering system using four pots: (1) weather prediction, CWSI, and soil moisture watering system; (2) CWSI and soil moisture watering syste;, (3) soil moisture watering system; (4) manual irrigation watering system to get the best watering system by water consumption and CWSI. The results show a significant difference by using CWSI. It gets a 42.7754% smaller CWSI value by using CWSI value in making watering decisions. By adding weather prediction, the research saves water consumption by 21.9% compared to CWSI and soil moisture watering systems. These results show that weather prediction and CWSI are vital for IoT plant watering systems.

Dimensions

Plum Analytics

Author Biographies

Jason Timotius Purwoko, Bina Nusantara University

Computer Science Department, BINUS Graduate Program – Master of Computer Science

Taurean Orlin Wingardi, Bina Nusantara University

Computer Science Department, BINUS Graduate Program – Master of Computer Science

Benfano Soewito, Bina Nusantara University

Computer Science Department, BINUS Graduate Program – Master of Computer Science

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Published

2023-03-17
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PDF downloaded 683  .