Dr Adeyinka Akanbi
Dr Adeyinka Akanbi

POSITION
Senior Lecturer
QUALIFICATIONS
PhD (CUT), MSc (JNTUH), BTech (LAUTECH)
PORTFOLIO
Dr A Akanbi obtained his PhD and Master of Science degrees from Central University of Technology, Free State, South Africa and Jawaharlal Nehru University, Hyderabad, India respectively. He is a skilled and versatile researcher and computer scientist with great experience in AI, big data, Internet of Things, semantic technologies, handling both supervised and unsupervised machine learning algorithms, using structured and unstructured data with focus on facilitating seamless data integration, achieving systems interoperability and data security in environmental monitoring systems.
He is currently employed as a Senior Lecturer at the Central University of Technology, Free state in South Africa and has more than 8 years of experience in teaching information technology modules and has published in international journals and conference proceedings with over 150 citations on Google Scholar. Dr Akanbi is member of the Association for Information Systems (AIS), IEEE and the South African Institute of Computer Scientists and Information Technologist (SAICSIT). His current research interest is in responsible AI, machine intelligence systems, data security and big data analytics.
Dr Akanbi is an experienced IT expert, skilled and certified as a Microsoft Certified Professional (MCP), Microsoft Solution Associate (MCSA), Microsoft Certified IT Professional (MCITP), Microsoft Certified Azure Fundamentals, RedHat Linux Certified Solution Associate (RHCSA) and Redhat Certified Engineer (RHCE).
AREAS OF EXPERTISE
Internet of Things
Big Data
Semantic Technologies
Artificial Intelligence
Blockchain
PUBLICATIONS
  • Akanbi, A.; Masinde, M (2020). A Distributed Stream Processing Middleware Framework for Real-Time Analysis of Heterogeneous Data on Big Data Platform: Case of Environmental Monitoring. Sensors 2020, 20, 3166.
  • OY Agunbiade, JO Dehinbo, T Zuva, AK Akanbi (2016). Road Detection Technique Using Filters with Application to Autonomous Driving System. International Journal of Computing, Communication and Instrumentation Engineering (IJCCIE), 3 (2), pp. 441-448. International Institute of Engineers.
  • OY Agunbiade, SM Ngwira, T Zuva, AK Akanbi (2016). Improving ground detection for unmanned vehicle systems in environmental noise scenarios. International Journal of Advanced Manufacturing Technology, 84 (9-12), pp. 2719-2727. Springer.
  • Akanbi, A. (2014). LB2CO: A Semantic Ontology Framework for B2C eCommerce Transaction on the Internet. International Journal of Research in Computer Science, 4 (1), pp. 1‐9. DOI: 10.7815/ijorcs. 41.2014.075.
  • Akanbi, A. & Agunbiade O. Y. (2014). Integration of a city GIS data with Google MAP and Google API for a web based 3D Geospatial Application. International Journal of Science and Research, 2(11), pp. 200-203.
  • Akanbi, A., Kumar, S., & Uwaya, F. (2013). Application of Remote Sensing, GIS and GPS for an efficient Urban Management Planning. Novus International Journal of Engineering & Technology, 2(4), pp.1-14.
BOOK(S) OR CHAPTER(S) IN BOOK(S)
  • Akanbi, A. (2022, December). Towards a Microservice-Based Middleware for a Multi-hazard Early Warning System. In International Conference on Emerging Technologies for Developing Countries (pp. 179-191). Cham: Springer Nature Switzerland.
  • Akanbi, A. K. & Masinde, M. (2016). A Framework for Accurate Drought Forecasting System Using Semantics-Based Data Integration Middleware. e‐Infrastructure and e‐Services for Developing Countries. Springer Chams.
PRESENTED CONFERENCES, SEMINARS, WORKSHOPS
  • Ramahlosi, MN., Madani, Y., Akanbi, A., (2023, August). A Blockchain-based Model for Securing Data Pipeline in a Heterogeneous Information System. In the 44th Conference of the South African Institute of Computer Scientists and Information Technologists. SAICSIT 2023 (pp. 1-6).
  • Madani, Y., Akanbi, A., Mbele, M., & Masinde, M. (2023, August). A Scalable Semantic Framework for an Integrated Multi-Hazard Early Warning System. In 2023 International Conference on Artificial Intelligence, Big Data, Computing and Data Communication Systems (icABCD) (pp. 1-6). IEEE.
  • Akanbi, A. (2020, November). Estemd: A distributed processing framework for environmental monitoring based on apache kafka streaming engine. In Proceedings of the 4th International Conference on Big Data Research (pp. 18-25).
  • Akanbi, A. K. & Masinde, M. (2018). Towards the Development of a Rule-based Drought Early Warning Expert Systems using Indigenous Knowledge. In proceedings of International Conference on Advances in Big Data, Computing and Data Communication Systems (icABCD 2018), IEEE, Durban, South Africa.
  • Akanbi, A. K. & Masinde, M. (2018). IKON-OWL: Using Ontologies for Knowledge Representation of Local Indigenous Knowledge on Drought. In proceedings of the 24th Americas Conference on Information Systems (AMCIS 2018), New Orleans, Louisiana, US.
  • Akanbi, A. K. & Masinde, M. (2018). Semantic Interoperability Middleware Architecture for Heterogeneous Environmental Data Sources. In proceedings of the IST-Africa 2018 Conference, IEEE. 9-12 Gaborone, Botswana.
  • Akanbi, A. K. & Masinde, M. (2015). Towards Semantic Integration of Heterogeneous Sensor Data with Indigenous Knowledge for Drought Forecasting. In proceedings of the Doctoral Symposium of the 16th ACM International Middleware Conference, Vancouver, BC, Canada.
  • Akanbi, A. K., Agunbiade, O.Y., Dehinbo, O.J., & Kuti, S.T. (2014). A Semantic Enhanced Model for Effective Spatial Information Retrieval. In Proceedings of the World Congress on Engineering and Computer Science (Vol. 1) WCECS 2014, 22-24 October, 2014, San Francisco, USA, pp. 557-562.
EXTERNAL PROFILES
LinkedIn
ResearchGate
Google Scholar

Contact Us
  • Dr Adeyinka Akanbi
  • Tel:
  • aakanbi@cut.ac.za