NCBL
NCBL

University of alberta

Uchechi Ukaegbu

About me:

I obtained my bachelor’s degree in mechanical engineering from the University of Nigeria, Nsukka in 2017. I also obtained my master’s degree in mechanical engineering from the University of Johannesburg, South Africa in 2021. I have joined the Neuromuscular control and biomechanics lab as a PhD student in 2023.

SUPERVISORS:

  • Dr. Hossein Rouhani

RESEARCH INTERESTS:

  • Machine learning

  • Robotics

  • Biomechanics

Projects

Development of a smart plant weed detector and agricultural drone employing deep learning (master’s thesis)

  • My master’s thesis involved the development of a drone that was able to differentiate between two types of plant weeds and spray herbicides accordingly. A deep learning model was trained and deployed on a raspberry pi which was incorporated on the drone.

Design and fabrication of a solar-powered unmanned aerial vehicle (BSc. Project)

  •   My BSc. Project involved the design and development of a fixed-wing UAV powered using solar energy.

Honors and awards

  • Best master’s student researcher, department of mechanical engineering, University of Johannesburg, South Africa. (2021)

  • University of Johannesburg commonwealth scholarship award (2022)

  • Global stature excellence scholarship award (2019-2020)

  • MTN foundation scholarship (2012-2016)

  • Agbami scholarship award (2012-2016)

publicationS

Journal articles:

  1. Ukaegbu, U.F., Tartibu, L.K., Okwu, M.O. and Olayode, I.O., 2021. Development of a light-weight unmanned aerial vehicle for precision agriculture. Sensors, 21(13), p.4417. https://doi.org/10.3390/s21134417

  2. Ukaegbu, U., Tartibu, L., & Lim, C. W. (2023). Multi-Objective Optimization of a Solar-Assisted Combined Cooling, Heating and Power Generation System Using the Greywolf Optimizer. Algorithms, 16(10), 463. https://doi.org/10.3390/a16100463   

  3. Olayode, I.O., Tartibu, L.K., Okwu, M.O. and Ukaegbu, U.F., 2021. Development of a hybrid artificial neural network-particle swarm optimization model for the modelling of traffic flow of vehicles at signalized road intersections. Applied Sciences, 11(18), p.8387. https://doi.org/10.3390/app11188387

Conference Proceeding:

  1. Ukaegbu, U.F., Tartibu, L.K. and Lim, C.W., 2022, October. Supervised and Unsupervised Deep Learning Applications for Visual SLAM: A Review. In ASME International Mechanical Engineering Congress and Exposition (Vol. 86656, p. V003T04A010). American Society of Mechanical Engineers. 10.1115/IMECE2022-95685.

  2. Ukaegbu, U.F., Tartibu, L.K., Okwu, M.O. and Olayode, I.O., 2021, December. Deep learning application in diverse fields with plant weed detection as a case study. In Proceedings of the International Conference on Artificial Intelligence and its Applications (pp. 1-9). 10.1145/3487923.3487926 

  3. Ukaegbu, U.F., Tartibu, L.K., Okwu, M.O. and Olayode, I.O., 2021, December. Integrating Unmanned Aerial Vehicle and Deep Learning Algorithm for Pipeline Monitoring and Inspection in the Oil and Gas Sector. In Proceedings of the International Conference on Artificial Intelligence and its Applications (pp. 1-6). 10.1145/3487923.3487924.

  4. Ukaegbu, U., Tartibu, L. and Okwu, M., 2021, August. Unmanned aerial vehicles for the future: classification, challenges, and opportunities. In 2021 International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems (icABCD) (pp. 1-7). IEEE. 10.1109/icABCD51485.2021.9519367.

  5. Ukaegbu, U. and Tartibu, L.K., 2021, July. Analysis of Anfis-Based Approaches for the Prediction of Net Energy Consumption. In AIUE Proceedings of the 2nd Energy and Human Habitat Conference. 10.2139/ssrn.3900762.

  6. Ukaegbu, U., Tartibu, L. and Okwu, M., 2020. Deep learning hardware accelerators for high performance in smart agricultural systems: an overview. In SAllE Conference 2020.

  7. Ukaegbu, U., Tartibu, L., Laseinde, T., Okwu, M. and Olayode, I., 2020, August. A deep learning algorithm for detection of potassium deficiency in a red grapevine and spraying actuation using a raspberry pi3. In 2020 international conference on artificial intelligence, big data, computing and data communication systems (icabcd) (pp. 1-6). IEEE. 10.1109/icABCD49160.2020.9183810.

  8. Okwu, M., Oyejide, O.J., Tartibu, L. and Ukaegbu, U., 2021, August. Performance Analysis of an Autonomous Cart Trolley for the Disabled: An ANFIS Based Evaluating Methodology. In 2021 International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems (icABCD) (pp. 1-6). IEEE. 10.1109/icABCD51485.2021.9519376.

  9. Olayode, I.O., Tartibu, L.K., Ukaegbu, U.F. and Severino, A., 2022, August. Modelling of Traffic Flow of Long and Short Trucks on a Signalized Road Intersection Using Artificial Neural Network Model. In 2022 International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems (icABCD) (pp. 1-7). IEEE.

  10. Olayode, I.O., Tartibu, L.K., Okwu, M.O. and Uchechi, D.U., 2020. Intelligent transportation systems, un-signalized road intersections and traffic congestion in Johannesburg: A systematic review. Procedia CIRP, 91, pp.844-850. 10.1016/j.procir.2020.04.137.