Unknown (2025) Ai-Based Smart Irrigation System

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: International Research Journal of Modernization in Engineering Technology and Science
• Year: 2025
• Date: 2025-12-09
• Authors: Unknown
• DOI: 10.56726/irjmets86171

Research Groups

Not specified in the provided text.

Short Summary

This research proposes an intelligent irrigation model combining deep learning-based soil moisture classification from mobile phone images with dynamic weather forecasting to improve irrigation decisions, achieving up to 92% classification accuracy and 30-40% water savings.

Objective

• To develop and evaluate an intelligent irrigation model that integrates deep learning for soil moisture analysis and dynamic weather forecasting to optimize water usage in agriculture.

Study Configuration

• Spatial Scale: Not explicitly specified, implied at the farm/field level for agricultural application.
• Temporal Scale: Real-time, dynamic decision-making based on current conditions and forecasts.

Methodology and Data

• Models used: Convolutional Neural Network (CNN) for soil moisture classification.
• Data sources: Mobile phone images for soil moisture, weather data (temperature, humidity, rainfall probability).

Main Results

• Achieved up to 92% accuracy for soil moisture classification.
• Demonstrated a response time below 0.5 seconds for irrigation decisions.
• Showed a potential water savings of 30-40%.

Contributions

• Introduces an affordable, scalable, and efficient AI-driven irrigation solution for modern agriculture.
• Combines deep learning for visual soil analysis with dynamic weather forecasting for improved irrigation decisions.

Funding

Not specified in the provided text.

Citation

@article{Unknown2025AiBased,
  author = {},
  title = {Ai-Based Smart Irrigation System},
  journal = {International Research Journal of Modernization in Engineering Technology and Science},
  year = {2025},
  doi = {10.56726/irjmets86171},
  url = {https://doi.org/10.56726/irjmets86171}
}