Papers
3
Total Citations
13
H-Index
2
About
Merouane Mazar is a pioneering researcher at the intersection of agricultural robotics and precision horticulture. His work focuses on the simulation, optimization, and dynamic scheduling of robotic systems for UV-C treatment of plant diseases, addressing critical challenges in sustainable crop protection. Mazar’s major contributions include developing computational frameworks that enable robots to autonomously navigate greenhouses and deliver targeted ultraviolet radiation to combat fungal pathogens like mildew, reducing reliance on chemical pesticides. His most cited paper, "Simulation and optimization of robotic tasks for UV treatment of diseases in horticulture" (2020, 7 citations), establishes a foundational methodology for task planning in UV-C robotics. An earlier work, presented to an international audience in 2018, further refined these optimization techniques. His 2021 study on dynamic scheduling introduces real-time adaptability to fluctuating disease pressures. Though his citation counts are modest, Mazar’s research is highly specialized and directly applicable to the emerging field of precision agriculture. His achievements include bridging robotics, control theory, and plant pathology, offering scalable solutions for disease management in controlled environments. For students and researchers, Mazar’s work exemplifies how simulation-driven optimization can transform agricultural practices, making them more efficient and environmentally friendly.
Research Focus
Key Achievements
Top Papers
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- 3Dynamic Scheduling of Robotic Mildew Treatment by UV-c in Horticulture2 citations · 2021