Rami Al‐Hmouz
Papers
2
Total Citations
49
H-Index
2
About
Rami Al-Hmouz is a researcher whose work spans computer vision, robotics, and intelligent monitoring systems. His key contributions lie in two primary areas: automated fish monitoring using AI and computer vision, and motion planning for mobile robots in dynamic environments. In his highly cited 2025 comprehensive study on computer vision-based approaches for fish monitoring systems, Al-Hmouz provides a thorough review of benchmark datasets and emerging intelligent technologies—including AI and robotics—that are transforming real-world aquatic monitoring applications. This work, with 26 citations, serves as a foundational resource for researchers developing automated solutions for marine biology and environmental monitoring. Earlier, in his 2005 paper on probabilistic road maps (PRM) for obstacle avoidance, Al-Hmouz demonstrated a novel approach to motion planning for non-holonomic mobile robots operating in cluttered dynamic environments. This work, which has garnered 23 citations, introduced a fast and simple local planner that builds efficient network representations of configuration spaces. Together, these contributions highlight Al-Hmouz’s versatility in applying computational methods to both biological and robotic systems, making his research valuable for students and professionals working at the intersection of AI, robotics, and environmental science.
Research Focus
Key Achievements
Top Papers
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