A et al. (2026) Sensor Enabled - Soil and Plant Health Portable Device

Identification

• Journal: INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
• Year: 2026
• Date: 2026-04-02
• Authors: Dr. Shashikala A, Arpitha Arpitha
• DOI: 10.55041/ijsrem58519

Research Groups

• Department of Mechanical Engineering, Acharya Institute of Technology, Bengaluru, Karnataka, India

Short Summary

This project develops a portable, sensor-enabled device leveraging IoT and Machine Learning for real-time soil and plant health monitoring, demonstrating reliable performance in detecting plant diseases and monitoring soil conditions to enhance precision agriculture.

Objective

• To develop a low-cost, portable, and user-friendly sensor-enabled device for real-time monitoring of soil and plant health, integrating IoT and Machine Learning to improve crop productivity and sustainability in smart agriculture.

Study Configuration

• Spatial Scale: Field or farm-level (suitable for small and medium-scale farmers).
• Temporal Scale: Continuous and real-time data collection.

Methodology and Data

• Models used: Internet of Things (IoT) for data collection and display, Machine Learning (specifically Convolutional Neural Network - CNN) for plant disease detection.
• Data sources: Soil moisture sensors, soil temperature sensors, and leaf images.

Main Results

• A sensor-enabled portable device was successfully developed for continuous monitoring of soil moisture, soil temperature, and plant health.
• The system integrates IoT for real-time data collection and display on a user-friendly web dashboard.
• A Convolutional Neural Network (CNN) model was implemented for plant disease detection using leaf images, achieving high accuracy.
• Experimental results demonstrated reliable performance in monitoring soil conditions and detecting plant diseases.
• The device is designed to be low-cost, portable, and easy to use, making it suitable for small and medium-scale farmers.

Contributions

• Development of an integrated, low-cost, and portable system for real-time soil and plant health monitoring, specifically targeting small and medium-scale farmers.
• Effective integration of IoT for continuous environmental data collection and Machine Learning (CNN) for accurate plant disease detection from leaf images.
• Provides a practical solution for precision agriculture, enabling farmers to make informed decisions on irrigation and crop management, thereby reducing resource wastage and improving crop health and overall agricultural efficiency.

Funding

• Not specified in the provided text.

Citation

@article{A2026Sensor,
  author = {A, Dr. Shashikala and Arpitha, Arpitha},
  title = {Sensor Enabled - Soil and Plant Health Portable Device},
  journal = {INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT},
  year = {2026},
  doi = {10.55041/ijsrem58519},
  url = {https://doi.org/10.55041/ijsrem58519}
}