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January 1, 2026International Journal of Engineering Systems Modelling and Simulation

Intelligent paddy leaf disease detection and automated pesticide spraying using AI and IoT

Sheeba Santhosh G. Hari Krishnan G. Mohandass R. Sreelakshmi E. Sivanandam Ashok Kumar Srinivasan

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Key Points

To evaluate the effectiveness of artificial intelligence and IoT for disease detection and automated pesticide application on paddy leaves.
Designed an AI-based system for real-time disease detection in paddy leaves.
Implemented IoT devices for automated pesticide spraying based on detected diseases.
Achieved over 90% accuracy in disease detection with the AI system (p<0.01).
Reduced pesticide usage by 30% through targeted spraying compared to traditional methods (p<0.05).
Improved overall crop yield by 20% in the treated group during the trial period (p<0.01).

Implication

Investigates automated pesticide spraying effectiveness in paddy crops, suggesting improved disease management.

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Cite This Study

Santhosh et al. (2026) studied this question.

synapsesocial.com/papers/6a22688f763171746d5471ef https://doi.org/10.1504/ijesms.2026.10078931

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