Current Research Projects
Development of an Optimisation Algorithm for Weather-related Crop Insurance
Optimisation problems are part and parcel of day-to-day activities. In the case of Africa’s agricultural-based economies, optimisation problems can be extended to the various aspects of agricultural production, such as drought prediction, crop yield optimisation and crop insurance benefit maximisation using heuristics and metaheuristics solution. This research explores the possibility of applying ANNs to optimize the outcome of all the decision reached from the myriad aspects presented above.
Application of IK, ML and Satellite Imagery to optimise Cropping Decisions
Africa is one of the continents that are considered to have less of crop lands in comparison with other continents such as America and Asia. The application of remote sensing technology to assess & monitor the vegetation health in Africa with other conventional technology is not yet widely adopted. This research explores the application of indigenous knowledge, ML and satellite imagery to optimise cropping decisions by small-scale farmers, a case study of uMgungundlovu Municipality, South Africa
Development of Intelligent Prediction Model for Infectious Disease Outbreak
The rise of global temperatures makes the population tropical mega-cities vulnerable to heat stress, infectious diseases, and air pollution. In Free State Province, SA, the effects of climate change, with drought seasons, heatwaves are becoming more intensive. These extreme weather changes have resulted in the infectious disease outbreaks. This research focuses on the development of an intelligent prediction model for infectious disease outbreaks: an ensemble of ML, big climate data and IK.
Current Students
Doctoral
- PM Phoobane
- MJ Nyetanyane
Masters
- MM Meshake
- Y Madani
- Y Bizumuremyi
- V Nketu
- P Ramba
- M Ramahlosi
- V Njokweni
Allumni
Dr Alowo
ALOWO, Rebecca Lesley Orando a candidate for the degree DOCTOR OF ENGINEERING IN CIVIL ENGINEERING.” THE TITLE OF HER THESIS IS:
“Sustainable Groundwater Management Through Modelling of Selected Hydrological Parameters: A Case Study of The Modder River Catchment of South Africa.”
Her doctoral studies focused on developing a groundwater sustainability model that assess and predict the sustainability of groundwater in the Modder river catchment. Her studies indicated that the catchment groundwater is over abstracted and not sustainable in the current trajectory. To improve the sustainability of the catchment groundwater resources, Dr Alowo proposed the use of artificial intelligence and other ICT tools for effective monitoring and groundwater management. The results of her research were published in five DHET accredited journals and books chapters and were presented at two international conferences.
Dr M Mkhonto
MKHONTO, Mkhonto, a candidate for the degree DOCTOR OF PHILOSOPHY IN INFORMATION TECHNOLOGY. THE TITLE OF HIS THESIS IS:
“A framework for e-Government diffusion assessment tool for service delivery in South Africa’s municipalities: Task-Technology-Fit approach.”
In his doctoral research, he developed a framework for customised assessment tool for assessing the “fitness’ of e-Government solutions in South Africa’s municipalities. He addressed the marginalisation of e-Goverment diffusion in South African municipalities. The developed framework can assist municipalities’ in service delivery, thereby contributing to the technological - scientific knowledge.
The research results show that the rate of diffusion of e-Government in the municipalities across South Africa is seventy-five percent (75%). The results will assist decision makers in local government to consider the factors relevant to e-Government diffusion use and future success within existing e-Government initiatives.
Dr A Akanbi
AKANBI, Adeyinka Kabir, a candidate for the degree DOCTOR OF PHILOSOPHY IN INFORMATION TECHNOLOGY. THE TITLE OF HIS THESIS IS:
“Development of semantic-based distributed middleware for heterogeneous data integration and its application for drought.”
In his doctoral research, “Development of semantics-based distributed middleware for heterogeneous data integration and its application for drought”, the candidate addressed the challenges of generating accurate inference from heterogeneous data sources through the application of semantic technologies, real-time stream processing engines for, amongst others, integration and interoperability. The study’s main contribution to knowledge is the development of a semantic middleware that is capable of integrating drought-related data from diverse sources, including indigenous knowledge and sensors’ data in a distributed architecture. Six publications at international scientific conferences and in peer-reviewed journals emanated from the research.
Dr Mwagha
Dr Mwagha career spans academic teaching and research to industry and he has over a decade experience leading research and solution development involving computing technologies. Prior to joining academics, He was an ICT Officer for e-government, a Kenyan government directorate that develops and supports solutions for public services. He has he held faculty positions in computer science departments at Pwani University and Taita Taveta Universities in Kenya. He holds a Ph.D. Information Technology (CUT, Free State) and MSc in Computer Science (University of Nairobi) as well as a B.S. in Computer Mathematics and Science (Kenya Methodist University). He has research interests span the Internet of Things, Machine Learning, Computer Vision and Fuzzy Cognitive Mapping.
Thothela, Naledi Portia
“Evaluation of an intelligent agro-climate decision-support tool for small-scale farmers: An integration of mobile phones, smart sensors and indigenous knowledge”
Artificial Intelligence (AI) is fast becoming a technology of choice with enormous potential to transform small-scale agriculture. Machine Learning (ML) is a subfield of AI and computer science that focuses on using data and algorithms to emulate human learning, with the objective of continually improving accuracy. ML can be harnessed in the task of easing the burden on small-scale farmers by assisting them to make an informed decision on the choice of crop prior to planting. This paper presents a ML model for predicting the suitable crop to be planted based on the given edaphic and climatic conditions, as well as observed Indigenous Knowledge (IK) at planting stage. Several ML algorithms were interrogated to select the best fit for the classification of the selected crops according to the Swayimane area in the province of kwaZulu Natal.
Ntshako, Neo Romeo
“An intelligent internet of things monitoring system for potable quality water: A case study in Mangaung area
This research explores the use of multi-layer perceptron neural networks (MLP) for predicting and monitoring the quality of drinking water. Physical parameters such as turbidity, PH, colour and electrical conductivity are some of the most important parameters to monitor in terms of potable water quality. To develop these predictive models, three years of data records were collected from Bloemwater regional water company in Mangaung area South Africa. The data sets included the aforementioned physical parameters, divided into two subsets; training and testing based on cross validation approach. Five models were developed, one for each parameter. After training and testing of the models, their performance were evaluated using sparse top k categorical accuracy, top k categorical accuracy, log cosh, mean squared error (MSE) and huber loss. The colour model proved to be the best of all the models built, considering the performance of the model across all the evaluation metrics used on the model. Although the available data size is comparatively limited, for water quality prediction, fairly good results were obtained.
Ms Mbele
Ms Mbele is an Information Technology Lecturer at Central University of Technology with a history of teaching software development and networking. She holds a Master’s Degree in Information Technology from Central University of Technology (2018). Her research is based on “maintaining sustainable cities” she is currently developing an environmental pollution monitoring tool that integrates scientific and local knowledge for the District of Lejweleputswa, she received a Women in Science award from the Department of Science and Technology (DST) for her research in 2016.
Ms Tanki
Tanki Moloabi is a Deputy Director at the Free State Provincial Treasury (Bloemfontein) in South Africa and the head of the Information Technology Unit. She holds a BTech degree (2003-2005) from the Central University of Technology (CUT) in Bloemfontein, South Africa and has received a Master’s degree in the specialised field of Information and Technology from CUT in April 2019. Ms. Moloabi has an extensive managerial experience as an IT expert playing the role of, among others, server administrator, manager of the ICT Team (including programmers, ICT Security, server administrator) and ICT Governance framework implementation at Provincial Treasury. Currently, she is a member of: Provincial Treasury ICT Steering committee, the Provincial Government Information Technology Council, an Advisory committee to all Heads of Department of the FS Provincial Government (FSPG) on the implementation of technological innovations, IT infrastructure and system design within the public sector to ensure seamless service delivery and system interlinkages.
Ms Thotela
Ms Thotela completed her National Diploma in Information Technology, Cum Laude, with Central University of Technology, and she majored in Software development. She then went on to complete her Bachelor of Technology, Cum Laude at the same institution. She is currently studying towards her Master of Technology in Information Technology. Portia is a passionate and determined woman who has lived to defy the odds, and practices excellence in everything that she commits to. One of her passions is women empowerment and she believes that by changing one life, you could change a nation. She is the founder of Your Dream Dance and grooming Academy, which is a Non-profit organization with the aim to empower women and children in disadvantaged communities.
Mr Ts’itso Maphats’oe
Mr Maphats’oe obtained his Masters in Information technology in 2017, under the supervision of Professor Muthoni Masinde. It was through this period he learned about and became involved in the wonderful initiative that is URIDA, as well as the novel methods through which we may try and combat food shortages by predicting and preparing for dry drought seasons in Africa.
