Full Name: Dr. Kadeghe Goodluck Fue
Title: Senior Lecturer
Area of specialization: Digital and Data-Driven Agricultural Engineering, Agricultural Automation
School: School of Engineering and Technology.
Department: Department of Agricultural Engineering
Office Location: Edward Moringe Campus (SUA Main Campus), Building No.48, Electronics and Precision Agriculture Laboratory(EPAL) at SoET, Office No.1
Email address: kadefue[at]sua.ac.tz.
Dr. Kadeghe “Kade” Goodluck Fue is a distinguished professional in the field of Digital and Data-Driven Agriculture and Natural Resource Management. He holds membership in several esteemed organizations, including SUASA, IET, IEEE, ASABE, AAAS, and AUVSI, reflecting his active engagement with the global scientific community.
Dr. Fue’s expertise spans vital areas such as Precision Agriculture, Artificial Intelligence, Machine Vision, Agricultural Robotics, Agricultural Data Science, and Earth Data Science. He obtained his Bachelor’s degree in Computer Engineering from the University of Dar es Salaam in Tanzania, then advanced his studies with a Master’s degree in Precision Agriculture from the University of Florida and a PhD in Agricultural Robotics from the University of Georgia, both located in the United States.
With more than 14 years of professional experience, Dr. Fue specializes in full-stack development, which integrates hardware and software systems. He is known for creating innovative algorithms that enhance autonomy and apply AI in the agricultural and natural resource domains. In addition, he serves as a senior lecturer, consulting engineer, and researcher at the Department of Agricultural Engineering at the School of Engineering and Technology at Sokoine University of Agriculture (SUA).
In his role as the Principal Investigator at the Electronics and Precision Agriculture Lab (EPAL), Dr. Fue has successfully directed collaborations and secured funding from multiple countries, underscoring his leadership in the field. He has also managed numerous consultancy projects that focus on developing sophisticated systems for monitoring agriculture and natural resources. He is the coordinator for the AIMS unit in the office of the deputy vice-chancellor for academic, research, and consultancy. Dr. Fue’s significant contributions and achievements have profoundly impacted Digital and Data-Driven Agriculture and Natural Resource Management.
For more information on Dr. Fue’s research contributions, you can find his ORCID ID, Scopus ID, and Scholar ID through the respective URLs.
Academic/Educational Background:
PhD (Eng), University of Georgia, Athens, Georgia, USA 2020
MSc (Eng), University of Florida, Gainesville, Florida, USA 2014
BSc (Eng), University of Dar es Salaam, Dar es Salaam, Tanzania 2011
Research Interests / Areas:
Precision Agriculture, Artificial Intelligence, Machine Vision, Agricultural Robotics, and Agricultural Data Science
Funded Research Projects:
Towards a Nationwide Automatic Irrigation Scheduling System using Geospatial Artificial Intelligence (NAISS-GAI), a SUARIS Grant 2022-2024
Morogoro youth empowerment through establishment of social innovation (YEESI) lab for problem-centered training in machine vision 2021-2023
TWAS-BMBF Seed Grant for New African Principal Investigators (SG-NAPI) 2022-2023
FSNet-Africa Fellowship 2021-2023
Climate Smart Rice Project (Climate – smart flood salinity tolerant Africa Rice) 2021-2025
List of courses:
AGE 328 Communications and Computer Networking
AGE 219 Basics of Computer Programming
AGE 316 Microcomputer Systems
AGE 418 Sensors and Controls for Precision Agriculture.
Students Supervision
Shija, Heribert, M.Sc. Student Engineering
Mmanga, Omar M., PhD Student Soil Science
Massawe, Dickson., Undergraduate Student
Edward, Nosim, Undergraduate Student
Seif, Mlagazya Musa, undergraduate Student
Sabinus, Sebastian, Undergraduate Student
Philimon, Philimon Stafford, Undergraduate student
Sylindon, Johnson, Undergraduate student
Osward, Eligidius Onesmo, Undergraduate student
Joshua, Rabo, Undergraduate student
Maswe, Christopher Sospeter, Undergraduate student, Mzumbe University
Kimera, Shoko Sharadhuli, Undergraduate student, University of Dodoma
Nyamatama, Karim Said, Undergraduate student, Mzumbe University
Kashaigili, Jovan Japhet, Undergraduate student, University of Dar es salaam
Journal Articles:
Fue, K., Barnes, E., Porter, W., Li, C., and Rains, G., (2020). Center-Articulated Hydrostatic Cotton Harvesting Rover Using Visual-Servoing Control and a Finite State Machine. Electronics, 9(8), 1226. [Editor’s Choice Article]
Fue, K., Barnes, E., Porter, W., Li, C., and Rains, G., (2020). An Autonomous Navigation of a Center-articulated and Hydrostatic Transmission Rover using a Modified Pure Pursuit Algorithm in a Cotton Field. Sensors, 20(16), 4412.
Fue, K., Barnes, E., Porter, W., Li, C., and Rains, G., (2020). Evaluation of a Stereo Vision System for Cotton Row Detection and Boll Location Estimation in Direct Sunlight. Agronomy, 9(8), 1127.
Fue, K., Barnes, E., Porter, W., and Rains, G., (2020). An Extensive Review of Mobile Agricultural Robotics for Field Operations: Focus on Cotton Harvesting. AgriEngineering., 2(1):150-174
Fue, K., Barnes, E., Porter, W., and Rains, G., (2021). Ensemble Method of Deep Learning, Color Segmentation, and Image Transformation to Track and Count Bolls using a Moving Camera in Real-time. Transactions of ASABE, 65(1), 13112
Barnes, E., Morgan, G., Hake, K., Devine, J., Kurtz, R., Ibendahl, G., … Fue, K.G. & Holt, G. (2021). Opportunities for Robotic Systems and Automation in Cotton Production. AgriEngineering, 3(2), 339-363.
Parab, C. U., Mwitta, C., Hayes, M., Schmidt, J. M., Riley, D., Fue, K., … & Rains, G. C. (2022). Comparison of Single-Shot and Two-Shot Deep Neural Network Models for Whitefly detection in IoT Web Application. AgriEngineering, 4(2), 507-522.
Book Chapters
Fastelini, G., Schillaci, C., Crestey, T., Tisseyre, B., Fountas, S., Anastasiou, E., Acutis, E., Kayad, A., Marinello, F., Sartori, L., Liakos, V., Vellidis, G., Mendes, A., Velez, J., Fue, K., Sanga, C., Tumbo, S., & E. Morimoto. (2020). Precision farming and IoT case studies across the world. In A. Castrignano, G. Buttafuoco, R. Khosla, A. Mouazen, D. Moshou & O. Naud (Eds.), Agricultural Internet of Things and Decision Support for Precision Smart Farming (pp. 65-74). Amsterdam, Netherlands: Elsevier.
Conference/Workshops/Seminar Papers
Barnes, E., Hake, K., Griffin, T., Rains, G., Maja, J., Thomasson, J., Griffin, J., Pelletier, M., Bruce, M., Fue, K., Kimura, E., Morgan, G., Devine, J., Ibendahl, G., & Ayre, B.(2019). Initial Possibilities for Robotic Cotton Harvest. In 2019 Beltwide Cotton Conferences, New Orleans, Louisiana. Paper No. 19370. Cordova, TN: NCC
Fue, K., Porter, W., Barnes, E., & Rains, G. (2019). Visual Inverse Kinematics for Cotton Picking Robot. In 2019 Beltwide Cotton Conferences, New Orleans, Louisiana. Paper No. 19379. Cordova, TN: NCC
Fue, K., Porter, W., Barnes, E., & Rains, G. (2019). Visual Row Detection Using Pixel-Based Algorithm and Stereo Camera for Cotton Picking Robot. In 2019 Beltwide Cotton Conferences, New Orleans, Louisiana. Paper No. 19376. Cordova, TN: NCC
Fue, K., Barnes, E., Porter, W., and Rains, G., (2019). Visual Control of Cotton-picking Rover and Manipulator using a ROS-independent Finite State Machine. In 2019 ASABE Annual International Meeting, Boston, Massachusetts (pp. 1-16). Paper No. 1900779. St Joseph, MI: ASABE.
Fue, K., Porter, W., Barnes, E., & Rains, G. (2020). Field Testing of the Autonomous Cotton Harvesting Robot in an Undefoliated Cotton Field. In 2020 Beltwide Cotton Conferences, Austin, Texas. Paper No. 19875. Cordova, TN: NCC
Barnes, E., Morgan, G., Hake, K., Devine, J., Kurtz, R., Griffin, T., Ibendahl, G., Sharda, A., Fue, K., Rains, G., Mari Maja, J., Edgar Bruce, M., Thomasson, A., Griffin, J., Kimura, E., Gharakhani, H., Ayre, B., Young, S., & Pelletier, M. (2020). Current and Potential Robotic Applications to Improve Cotton Production. In 2020 Beltwide Cotton Conferences, Austin, Texas. Paper No. 19872. Cordova, TN: NCC
Mourice, S. K., Mlebus, F. J., & Fue, K. G. (2021). A simple Convolutional Neural Network Architecture for monitoring Tuta absoluta (Gelechiidae) infestation in tomato plants. In 2021 2nd SUA Scientific Conference, SUA Edward Moringe Campus Morogoro, Tanzania (pp. 6). Morogoro, Tanzania: SUA.
Google Scholar:
https://scholar.google.com/citations?user=rqeqefwAAAAJ&hl=en
Research Gate :
Educational Technology and Digital Infrastructure Specialist [HEET Project Component Leader], 2021 to Current.
Acting Coordinator, Academic Information Management and Support Unit, Aug 2021 to Current.
Electronics and Precision Agriculture Lab
Department of Agricultural Engineering,
School of Engineering and Technology,
Sokoine University of Agriculture.
P O Box 3003, Chuo Kikuu, Morogoro, Tanzania.
Email: kadefue at sua.ac.tz
Personal Email: kadefue at gmail.com
Personal Website: www.kadefue.com