Pandurangan et al. (2026) An IoT-Enabled Smart Farming System Using LoRa: Integrating Meteorological and Sensor Data for Optimized Irrigation and Crop Health Monitoring

Identification

• Journal: Lecture notes in networks and systems
• Year: 2026
• Date: 2026-01-01
• Authors: Raji Pandurangan, J. Swetha, M. K. Vishnuu Priya
• DOI: 10.1007/978-3-032-14194-1_7

Research Groups

• Department of Electronics and Communication Engineering, Saveetha Engineering College, Chennai, Tamil Nadu, India

Short Summary

This study presents an IoT-enabled smart farming system that integrates meteorological and local sensor data via LoRa technology to optimize irrigation decisions and monitor crop health using image processing, aiming to enhance agricultural output and water efficiency.

Objective

• To develop an IoT-enabled smart farming system that combines sensor networks and meteorological data to optimize irrigation and track crop health, providing farmers with useful information for effective crop management, efficient water use, and improved agricultural results.

Study Configuration

• Spatial Scale: Meteorological data collected from an area a few kilometers from the farmer's field; LoRa communication range up to 15 kilometers; local field data collected from the farmer's field.
• Temporal Scale: Meteorological data gathered at hourly and daily intervals; field conditions tracked in real-time.

Methodology and Data

• Models used: Image processing tools for crop health and growth monitoring.
• Data sources:
  • Meteorological department: Temperature, humidity (hourly and daily intervals).
  • Local field sensors: Temperature, humidity, soil moisture (real-time).
  • Farmer-provided data: Crop kind, soil properties.
  • Hardware: ESP32, LoRa modules, Raspberry Pi.

Main Results

• Developed a functional IoT system integrating diverse data sources (meteorological, sensor, farmer-provided) for smart farming.
• Demonstrated data transmission over distances up to 15 kilometers using LoRa technology.
• Enabled real-time monitoring of field conditions (temperature, humidity, soil moisture).
• Facilitated data-driven irrigation decision-making for farmers.
• Implemented crop health and growth monitoring through image processing for early problem identification.

Contributions

• Introduction of a comprehensive IoT-enabled smart farming system leveraging LoRa for long-range data transmission in agricultural settings.
• Integration of both broad meteorological data and specific local field sensor data, combined with farmer input, into a unified decision-making platform.
• Application of image processing for proactive crop health monitoring alongside optimized irrigation strategies.
• Focus on practical benefits for farmers, including improved crop management, water use efficiency, and agricultural outcomes.

Funding

• Not explicitly mentioned in the provided paper text.

Citation

@article{Pandurangan2026IoTEnabled,
  author = {Pandurangan, Raji and Swetha, J. and Priya, M. K. Vishnuu},
  title = {An IoT-Enabled Smart Farming System Using LoRa: Integrating Meteorological and Sensor Data for Optimized Irrigation and Crop Health Monitoring},
  journal = {Lecture notes in networks and systems},
  year = {2026},
  doi = {10.1007/978-3-032-14194-1_7},
  url = {https://doi.org/10.1007/978-3-032-14194-1_7}
}