Raihani Mohamed
Papers
1
Total Citations
2
H-Index
1
About
Raihani Mohamed is a researcher whose work lies at the intersection of artificial intelligence, multi-agent systems, and agricultural technology. His primary research focuses on developing optimization algorithms for complex task allocation problems, particularly in precision agriculture applications. Mohamed’s most notable contribution is his innovative modification of the Ant Colony Optimization (ACO) algorithm to solve multi-agent task allocation challenges, specifically for coordinating UAVs in agricultural settings. His 2023 paper on this subject demonstrates a practical approach to forming optimal coalitions of drones to complete on-farm tasks efficiently. While his citation count is still growing, Mohamed’s work addresses a critical gap in agricultural automation—how to intelligently deploy multiple autonomous agents to maximize productivity. His research has significant implications for smart farming, where efficient task allocation among drones can reduce labor costs, optimize resource use, and improve crop management. As the field of agricultural robotics expands, Mohamed’s contributions to algorithm development for multi-agent coordination position him as an emerging voice in the intersection of computational intelligence and sustainable agriculture.
Research Focus
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Top Papers
- 1