Where Agriculture Meets Mechatronics

Prof. Eshkabilov's group focuses on the development and testing of autonomous all-terrain vehicles for agricultural applications, with an emphasis on weed control, soil analysis, and plant monitoring. The team innovates and experiments with tractor powertrains and develops wireless sensor technologies to address agricultural, industrial, and ecological challenges. Leveraging imagery data, they apply AI algorithms to identify and predict water and nutrient stresses in plant

The mission of Prof. Eshkabilov's lab is to find innovative solutions in agricultural engineering by integrating cutting-edge technologies such as machine learning, artificial intelligence, Internet of Things (IoT), and advanced sensor systems. The lab focuses on addressing critical challenges in sustainable agriculture, including optimizing crop production, ensuring food safety, and mitigating environmental impacts. By leveraging interdisciplinary collaboration, the lab designs and implements advanced systems for autonomous vehicles, clean energy tractors, and automated controlled environment agriculture. Through projects supported by prestigious grants, the lab develops robust models for plant health assessment, irrigation management, and weed control using Edge-AI and UGV systems, alongside real-time decision-making enabled by electromagnetic sensors and ML algorithms. The lab is committed to fostering innovation, educating the next generation of agricultural engineers, and contributing to the global shift toward sustainable and technology-driven farming practices.