Alireza Zourmand
Papers
2
Total Citations
8
H-Index
2
About
Alireza Zourmand is a researcher advancing the intersection of robotics, computer vision, and the Internet of Things (IoT) for agricultural automation. His work focuses on developing intelligent, low-cost solutions for precision farming, particularly in the postharvest handling of crops. His most cited paper, "Robotics Solution for Agriculture: Automated and IoT-enabled Tomato Picking and Packing" (2023, 5 citations), introduces a novel system that integrates IoT and Machine-to-Machine (M2M) communication to automate the sorting and packing of tomatoes, demonstrating a practical, scalable approach to reducing labor costs and improving efficiency. In a complementary study, "Harvesting tomatoes with a Robot: an evaluation of Computer-Vision capabilities" (2023, 3 citations), Zourmand rigorously compares the performance of Intel RealSense D435 and Zivid Two 3D cameras for tomato detection and localization, using the YOLO model under both laboratory and greenhouse conditions. This work provides critical insights into the trade-offs between image quality and real-world deployment, guiding the selection of sensors for agricultural robots. Zourmand’s contributions are notable for their applied focus, bridging the gap between cutting-edge computer vision and tangible, cost-effective automation in food production.
Research Focus
Key Achievements
Top Papers
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