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About

Mohammed El-Abd is a robotics and artificial intelligence researcher whose work spans autonomous systems, agricultural robotics, swarm intelligence, and infrastructure inspection. He is perhaps best recognized for his contributions to practical robotic applications, including a cherry-tomato harvesting robot (2017, 39 citations) designed to automate agricultural tasks in both household and greenhouse settings while preserving homeowner privacy, and an autonomous firefighting robot (2015, 37 citations) aimed at reducing human risk in life-threatening emergency scenarios. His tour-guide robot (2016, 23 citations), leveraging Kinect technology, demonstrates his commitment to human-robot interaction in public spaces, while iPlant (2015, 21 citations) reflects his dedication to smart greenhouse automation. Beyond physical robotics, El-Abd has made notable theoretical contributions through his analytical framework for high-speed hardware particle swarm optimization (2019, 19 citations), advancing computational intelligence in hardware implementation. His more recent work on IoT-enabled robot swarms for pipeline crack detection (2024) signals a continued evolution toward intelligent multi-robot systems for critical infrastructure monitoring. Collectively, his research reflects a consistent vision of deploying intelligent robotics to solve real-world human challenges across safety, agriculture, and urban infrastructure.