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Original Article
Transforming agriculture with edge AI – enabling the Smart Farming
Katha Amulya1
Naga Rohitha2
U. Venkata Krishna3
Naman Pratap Singh4
K Gopala Krishna5
1 2 3 4 5 Department of CSE, KL University, Vijayawada, Andhra Pradesh, India.
Published Online: March-April 2026
Pages: 244-253
Cite this article
↗ https://www.doi.org/10.59256/ijire.20260702030
References
1. Katumba, M., et al. (2024). Leveraging Edge Computing and Deep Learning for the Real-Time Identification of Bean Plant Pathologies.
2. Tariq, A., et al. (2025). Edge-Enabled Smart Agriculture Framework: Integrating IoT and Low-Power Deep Learning for Precision
Farming.
3. Cordier, S., et al. (2024). Affordable Phenotyping at the Edge for High-Throughput Seedling Assessment.
4. He, Y., et al. (2024). Edge Computing-Oriented Smart Agricultural Supply Chain Management Framework.
5. Bresolin, N., et al. (2023). Computer Vision on the Edge: A Computing Framework for High-Throughput Phenotyping in Livestock
Operations.
6. Anonymous Authors. (2024). An Edge Computing-Based Solution for Real-Time Leaf Disease Classification Using Thermal Imaging.
7. Rathore, M., & Rajavat, R. (2024). Smart Farming Based on IoT-Edge Computing for Potato Crop Disease and Irrigation Prediction.
8. Saxena, P., et al. (2025). Deep Learning-Driven IoT Solution for Smart Tomato Farming.
9. Anonymous Authors. (2024). Enabling Smart Farming Through Edge Artificial Intelligence (AI).
10. Gong, X., et al. (2025). Edge Computing-Enabled Smart Agriculture: Technical Frameworks and Future Directions.
11. Multiple Authors. (2025). Deep Learning and Edge Computing in Agriculture: A Comprehensive Review.
12. Anonymous Authors. (2025). IoT-Based Smart Farming Architecture Using Federated Learning.
13. Prashanth, K., et al. (2025). Smart Farming Revolution: A Cutting-Edge Review of Deep Learning in Smart Farming.
14. Khan, M., et al. (2020). Deep Learning and IoT for Agricultural Applications.
15. Zhang, Y., et al. (2025). Farm-LightSeek: An Edge-Centric Multimodal Agricultural Perception System.
2. Tariq, A., et al. (2025). Edge-Enabled Smart Agriculture Framework: Integrating IoT and Low-Power Deep Learning for Precision
Farming.
3. Cordier, S., et al. (2024). Affordable Phenotyping at the Edge for High-Throughput Seedling Assessment.
4. He, Y., et al. (2024). Edge Computing-Oriented Smart Agricultural Supply Chain Management Framework.
5. Bresolin, N., et al. (2023). Computer Vision on the Edge: A Computing Framework for High-Throughput Phenotyping in Livestock
Operations.
6. Anonymous Authors. (2024). An Edge Computing-Based Solution for Real-Time Leaf Disease Classification Using Thermal Imaging.
7. Rathore, M., & Rajavat, R. (2024). Smart Farming Based on IoT-Edge Computing for Potato Crop Disease and Irrigation Prediction.
8. Saxena, P., et al. (2025). Deep Learning-Driven IoT Solution for Smart Tomato Farming.
9. Anonymous Authors. (2024). Enabling Smart Farming Through Edge Artificial Intelligence (AI).
10. Gong, X., et al. (2025). Edge Computing-Enabled Smart Agriculture: Technical Frameworks and Future Directions.
11. Multiple Authors. (2025). Deep Learning and Edge Computing in Agriculture: A Comprehensive Review.
12. Anonymous Authors. (2025). IoT-Based Smart Farming Architecture Using Federated Learning.
13. Prashanth, K., et al. (2025). Smart Farming Revolution: A Cutting-Edge Review of Deep Learning in Smart Farming.
14. Khan, M., et al. (2020). Deep Learning and IoT for Agricultural Applications.
15. Zhang, Y., et al. (2025). Farm-LightSeek: An Edge-Centric Multimodal Agricultural Perception System.
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