I am a Postdoctoral Researcher at the Precision Agriculture Laboratory, Department of Agricultural Machinery Engineering, Chungnam National University, Daejeon, Republic of Korea. My research specializes in smart agriculture technologies, with expertise spanning image processing, remote sensing, UAV-based crop monitoring, yield prediction and mapping, AI-driven plant factory management, and intelligent livestock farming systems.

My current work focuses on integrating machine learning with UAV-based data acquisition for real-time cabbage counting, detection, and growth stage monitoring using YOLO models, NDVI, and CWSI analysis. I am also developing AI-based models that utilize RGB, thermal, and acoustic data for disease detection and crushing prevention in pigs, supporting next-generation smart livestock management. Additionally, I am investigating stress detection in vegetable seedlings under controlled environments using ANN, CNN, and KNN classifiers. My research further includes sensor-integrated systems for upland crop yield monitoring, seed flow tracking in multi-type seeders, and precision spray control technologies.

My doctoral research, "Rice Growth and Yield Monitoring Based on Unmanned Aerial Vehicle (UAV) Imagery", focused on integrating remote sensing data for accurate crop assessment. Beyond my dissertation, I have contributed to multiple nationally funded projects under the Brain Korea 21 Plus, Rural Development Administration (RDA), and Korea Institute of Planning and Evaluation for Technology in Food, Agriculture, and Forestry (IPET). These projects have encompassed sensor interface development, remote sensing applications, AI-driven decision-making systems, and yield monitoring technologies for both crop and livestock sectors.

In addition to research, I have academic teaching experience as a teaching assistant, delivering lectures to undergraduate and graduate students on Precision Agriculture and Artificial Intelligence in Precision Agriculture. These courses covered GPS, GIS, UAV-based remote sensing, yield mapping, and the application of image processing, artificial neural networks, and deep learning for smart farming solutions.

For more information about my research activities and ongoing projects, please visit my website or feel free to contact me directly.

Contact details

Department of Agricultural Machinery Engineering

Chungnam National University, Daejeon 34134

Republic of Korea

E-mail: reza5575@cnu.ac.kr

ResearchGate: Md Nasim Reza

Google scholar: Md Nasim Reza