Rathamani (2026) Iot and Weather Data-Driven Smart Irrigation for Water-Efficient Crop Production

Identification

• Journal: RCHUB JOURNAL OF COMPUTATIONAL INTELLIGENCE SCIENCE AND ENGINEERING (JCISE)
• Year: 2026
• Date: 2026-09-15
• Authors: M. Rathamani
• DOI: 10.65725/jcise/2/3/012

Research Groups

• Department of Agricultural Engineering, Anna University, Chennai, India
• RCHUB Research Academy, Chennai, India

Short Summary

This study proposes an IoT and Weather Data-Driven Smart Irrigation System for Water-Efficient Crop Production that enables intelligent and automated irrigation based on real-time field conditions. The system achieved a water savings of up to 35% compared to conventional schedule-based irrigation.

Objective

• Investigate the feasibility of using IoT and weather data in smart irrigation systems for precision agriculture and sustainable water management.

Study Configuration

• Spatial Scale: Field-scale agricultural production, controlled experimental conditions.
• Temporal Scale: Real-time monitoring and automated decision-making based on current and predicted weather conditions.

Methodology and Data

• Models used: None specified; data-driven approach using IoT sensors and external weather information.
• Data sources: Soil-moisture, temperature, humidity, and water-level sensors; external weather forecasts including rainfall probability and temperature predictions.

Main Results

• Water savings of up to 35% compared to conventional schedule-based irrigation.
• Improved soil moisture stability by 18.2%.
• Enhanced crop growth and system reliability.

Contributions

• Original contribution lies in the integration of IoT and weather data for precision agriculture, demonstrating a more efficient use of water resources in agricultural production.

Funding

• This research was supported by the RCHUB Research Academy, Chennai, India (Grant No.: RCHUB/2026/RG001).

Citation

@article{Rathamani2026Iot,
  author = {Rathamani, M.},
  title = {Iot and Weather Data-Driven Smart Irrigation for Water-Efficient Crop Production},
  journal = {RCHUB JOURNAL OF COMPUTATIONAL INTELLIGENCE SCIENCE AND ENGINEERING (JCISE)},
  year = {2026},
  doi = {10.65725/jcise/2/3/012},
  url = {https://doi.org/10.65725/jcise/2/3/012}
}