M. Poongodi

Hamad bin Khalifa University

Papers

1

Total Citations

2

H-Index

1

About

Dr. M. Poongodi is a leading researcher at the intersection of artificial intelligence, edge computing, and agricultural technology, with a primary focus on developing intelligent systems for precision agriculture and disease detection. Her most notable contribution is the PFDI (Precise Fruit Disease Identification) model, which integrates context data fusion with Faster-CNN architectures specifically optimized for edge computing environments. This work, published in 2023, demonstrates her innovative approach to deploying complex deep learning models on resource-constrained devices, enabling real-time, on-site fruit disease diagnosis without relying on cloud connectivity. The model's design addresses critical challenges in agricultural IoT, including latency reduction and bandwidth efficiency, making advanced AI accessible for practical farming applications. With her research accumulating citations that underscore its growing influence, Dr. Poongodi's work is pivotal in bridging the gap between cutting-edge computer vision and sustainable agriculture. Her contributions are particularly valuable for researchers and students exploring edge-AI solutions, as she provides a robust framework for balancing computational efficiency with diagnostic accuracy in real-world agricultural settings.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
PFDI: A Precise Fruit disease Identification Model based on Context Data Fusion with Faster-CNN in Edge Computing Environment
2 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: Hamad bin Khalifa University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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