Mohamed Zarboubi
Papers
2
Total Citations
16
H-Index
2
About
Mohamed Zarboubi is at the forefront of integrating artificial intelligence with precision agriculture, pioneering smart solutions for crop protection and pest management. His research centers on developing autonomous robotic systems powered by state-of-the-art deep learning models, specifically targeting real-time disease and pest detection in high-value crops. Zarboubi’s major contributions include the design and implementation of YOLOv8 and YOLOv10-enabled IoT robot cars, which bring computer vision directly into the field and storage facilities. His 2024 paper on smart pest control in grain warehouses, which has already garnered 11 citations, addresses a critical global challenge: protecting cereal grains—which supply over 50% of the world’s energy and protein—from infestation. This work demonstrates a practical, scalable approach to reducing post-harvest losses. Complementing this, his study on YOLOv10 for strawberry disease detection (5 citations) showcases the adaptability of his framework to high-value horticulture. By merging edge computing with mobile robotics, Zarboubi is helping to usher in a new era of data-driven, autonomous crop management, making precision agriculture more accessible and effective for farmers worldwide.
Research Focus
Key Achievements
Top Papers
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