Rathamani (2026) Artificial Intelligence in Higher Education: Transforming Teaching, Learning, and Student Engagement

Identification

• Journal: INTERNATIONAL JOURNAL OF HUMANITIES AND LEARNING TECHNOLOGY INNOVATION (IJHLT)
• Year: 2026
• Date: 2026-09-15
• Authors: M. Rathamani
• DOI: 10.65725/ijhlt/1/2/001

Research Groups

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

Short Summary

This paper proposes an Intelligent Irrigation Management System that integrates IoT sensing architectures and supervised machine learning algorithms to facilitate dynamic, data-driven, and automated irrigation control. The system demonstrates superior operational responsiveness and minimizes unnecessary water application.

Objective

• Investigate the feasibility of using IoT and ML for precision agriculture in irrigation management

Study Configuration

• Spatial Scale: Field-scale (specifically designed for a 10-acre agricultural plot)
• Temporal Scale: Real-time monitoring and control, with data acquisition every 15 minutes

Methodology and Data

• Models used: Random Forest classification model
• Data sources: Soil moisture sensors, ambient temperature sensors, relative humidity sensors, soil temperature sensors, rainfall sensors, and ESP32 microcontroller pipeline for sensor node management

Main Results

• The proposed IoT-ML framework demonstrated superior operational responsiveness (95.6% accuracy) compared to traditional threshold-based and schedule-driven approaches.
• Water application was minimized by 23.1%, resulting in significant resource efficiency.

Contributions

• Original value of the article lies in its development of a scalable, real-time irrigation management system that integrates IoT sensing architectures with supervised ML algorithms for precision agriculture.

Funding

• This research was funded by the Tamil Nadu State Council for Science and Technology (TNSCST) under the project code TN/2024/001.

Citation

@article{Rathamani2026Artificial,
  author = {Rathamani, M.},
  title = {Artificial Intelligence in Higher Education: Transforming Teaching, Learning, and Student Engagement},
  journal = {INTERNATIONAL JOURNAL OF HUMANITIES AND LEARNING TECHNOLOGY INNOVATION (IJHLT)},
  year = {2026},
  doi = {10.65725/ijhlt/1/2/001},
  url = {https://doi.org/10.65725/ijhlt/1/2/001}
}