Building a CNN Based Pest Detection System for Off Grid Hydroponic Farming in Rural South Africa
Summary. Researchers developed an AI-powered pest detection system for off-grid hydroponic farming in rural South Africa. Using a convolutional neural network trained on common pests like spider mites and aphids, the system runs locally on a Raspberry Pi without internet connectivity. The technology successfully automates pest detection in resource-constrained settings, reducing manual crop inspections and improving food security for subsistence farmers facing climate challenges and limited agricultural resources.
Cite this article
Adnan, Y., Wilson, T., & Till, S.. (2025). Building a CNN Based Pest Detection System for Off Grid Hydroponic Farming in Rural South Africa. https://doi.org/10.1109/etncc66224.2025.11299757
Adnan, Yusra, et al. “Building a CNN Based Pest Detection System for Off Grid Hydroponic Farming in Rural South Africa.” 2025. https://doi.org/10.1109/etncc66224.2025.11299757.
Adnan, Yusra, Taryn Wilson, and Sarina Till. 2025. “Building a CNN Based Pest Detection System for Off Grid Hydroponic Farming in Rural South Africa.” https://doi.org/10.1109/etncc66224.2025.11299757.
@article{adnan-2025-building-cnn-based-pest-detection,
title = {Building a CNN Based Pest Detection System for Off Grid Hydroponic Farming in Rural South Africa},
author = {Yusra Adnan and Taryn Wilson and Sarina Till},
year = {2025},
doi = {10.1109/etncc66224.2025.11299757},
url = {https://doi.org/10.1109/etncc66224.2025.11299757}
}
TY - JOUR TI - Building a CNN Based Pest Detection System for Off Grid Hydroponic Farming in Rural South Africa AU - Yusra Adnan AU - Taryn Wilson AU - Sarina Till PY - 2025 DO - 10.1109/etncc66224.2025.11299757 UR - https://doi.org/10.1109/etncc66224.2025.11299757 ER -
Details
- DOI
- 10.1109/etncc66224.2025.11299757
- Countries
- South Africa
- Regions
- Africa
- Categories
- agtech, broadband-and-digital, food-systems, general-innovation
- Added
- 2026-05-01