Hybrid Approach for Multi-Crop Disease Detection for Enhanced Crop Health and Yield
Abstract & Details
Research Area
Electronics and Communication Engineering
Keywords
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Abstract
This project introduces an AI-powered agricultural robot designed for automated plant disease detection and treatment. The system integrates STM32 microcontroller based robotic movement, computer vision, and deep learning algorithms to identify diseases in crops with high accuracy. A Python-based application processes real-time images captured by the robot, while wireless communication (Wi-Fi/BLE) enables seamless coordination between the laptop and the robotic system. Upon disease detection, the AgriBot precisely applies pesticides, reducing chemical usage by 40-50%. This solution enhances farming efficiency, minimizes crop losses, and promotes sustainable agriculture.
License
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Attribution-ShareAlike 4.0 International License.
Author Information
| # | Name | Institute / Affiliation |
|---|---|---|
| 1 | Prof. LAVAKUMAR T B | SJM Institute of Technology |
| 2 | AYESHA BANU | SJM Institute of Technology |
| 3 | NAJMA BANU | SJM Institute of Technology |
| 4 | REHANA BANU | SJM Institute of Technology |
| 5 | SHREYA H E | SJM Institute of Technology |
How to Cite
Use the following formats to cite this article in your research.
APA Style
B, Prof. LAVAKUMAR T, BANU, AYESHA, BANU, NAJMA, BANU, REHANA, & E, SHREYA H (2025). Hybrid Approach for Multi-Crop Disease Detection for Enhanced Crop Health and Yield. International Journal of Advance Research and Innovative Ideas In Education, 11(6), 835-842.
MLA Style
B, Prof. LAVAKUMAR T, et al. "Hybrid Approach for Multi-Crop Disease Detection for Enhanced Crop Health and Yield." International Journal of Advance Research and Innovative Ideas In Education, vol. 11, no. 6, 2025, pp. 835-842.
IEEE Style
Prof. LAVAKUMAR T B, AYESHA BANU, NAJMA BANU, REHANA BANU, and SHREYA H E, "Hybrid Approach for Multi-Crop Disease Detection for Enhanced Crop Health and Yield," International Journal of Advance Research and Innovative Ideas In Education, vol. 11, no. 6, pp. 835-842, 2025.
Vancouver Style
B Prof. LAVAKUMAR T, BANU AYESHA, BANU NAJMA, BANU REHANA, E SHREYA H. Hybrid Approach for Multi-Crop Disease Detection for Enhanced Crop Health and Yield. International Journal of Advance Research and Innovative Ideas In Education. 2025;11(6):835-842.
Harvard Style
B, Prof. LAVAKUMAR T, BANU, AYESHA, BANU, NAJMA, BANU, REHANA, & E, SHREYA H (2025) 'Hybrid Approach for Multi-Crop Disease Detection for Enhanced Crop Health and Yield', International Journal of Advance Research and Innovative Ideas In Education, 11(6), pp. 835-842.
Chicago Style
B, Prof. LAVAKUMAR T, et al. "Hybrid Approach for Multi-Crop Disease Detection for Enhanced Crop Health and Yield." International Journal of Advance Research and Innovative Ideas In Education 11, no. 6 (2025): 835-842.
Turabian Style
B, Prof. LAVAKUMAR T, et al. "Hybrid Approach for Multi-Crop Disease Detection for Enhanced Crop Health and Yield." International Journal of Advance Research and Innovative Ideas In Education 11, no. 6 (2025): 835-842.
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