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June 14, 2026Iraqi Journal for Computers and InformaticsOpen Access

AI-Powered Smart Irrigation: A Case Study on Applying Genetic Algorithms and Particle Swarm Optimization for Water Conservation in Agricultural Projects

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Authors

AEAli Mohammed ElaibiUniversity Of Information Technology

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Implication

Randomized trial shows reduced water use and energy consumption in agricultural irrigation, suggesting a sustainable solution.

Key Points

  • The aim is to develop an AI-based irrigation system that optimizes water use in agriculture.
  • Developed the Smart Drop system utilizing machine learning models.
  • Implemented genetic algorithms and particle swarm optimization for irrigation prediction.
  • Tested in a 4.25-kilometer pipe network covering 147 hectares.
  • Reduced water use by 23.42%, saving 797,731 cubic meters over 1,000 days.
  • Estimated savings of US$121,036.62, a 23.4% reduction in costs.
  • Maintained optimal crop conditions with acceptable pressure distribution and minimal losses.

Cite This Study

Ali Mohammed Elaibi (2026) studied this question.

synapsesocial.com/papers/6a2e4429b1cc60ccdea8a0b6https://doi.org/10.25195/ijci.v52i1.815
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