Dr. Moustafa M. Kurdi
Smart Farming and Precision Agriculture by Using UAV and UGV Robots
Moustafa M. Kurdi received the B. E. degree in Computer Engineering from Beirut Arab University, Lebanon, in 2002, the MBA degree in Management from Lebanese International University, Lebanon, in 2010, and Ph.D. in System Analysis and Data Processing from Belarusian National Technical University, Belarus, in 2018.
Since 2007, he is a member of the Order of Engineers (Beirut – Lebanon) registered under number 30269. From 2010, he is a sworn expert of Information Technology in the Ministry of Justice (Saida – Lebanon). Since 2011, he has been coordinator of the Computer Science Department, American University of Culture and Education, Lebanon. From 2014, he has been coordinator of faculty of applied sciences, American University of Technology (Lebanon). Currently, he is the campus director (Tyre – Lebanon). He has more than 10 years of academic teaching experience in the fields of computer, software and networking engineering. Mr. Kurdi is member of IEEE. He is the author of 30 research works. His current research interests include Robotics, Positioning, Navigation, Multi-functional Robot, Thermography, Smart Systems, Neural Networks, Educational Data, Data Mining, Car-Like Robot, Computer Vision, System Analysis, Information processing, Intelligent Mobile Robot, Image watermarking, and Design Automation.
Hybrid autonomous robots used mostly in precision agriculture, farming and landmine operations. Initially, this paper manages organizing quadcopter and ground mobile robot to gather information for agriculture applications. The ground and aerial measurements gathered by the framework are utilized for improving agriculture and farming. The quadcopter Phantom-4 Pro utilized for agricultural image-coverage and exact studying of the harvests and leaves diminishing the human exertion. The agricultural farm is overviewed by an infrared camera which will demonstrate the shading picture showing the contrast between tainted or sick yield and developed harvest. Second, it describes the method of landmine operations based-on the ground penetrating radar (GPR) attached to quadcopter, which is useful for farming and maximizing agriculture. Third, we present a new coverage path-planning problem in which the ground mobile robot must traverse depending on each point visited by the quadcopter.
Precision Agriculture; Smart Farming; UAV-UGV; Thermal Image