Dr. Abayomi Otebolaku MSc, PhD
Senior Lecturer
Summary
I'm a Senior Lecturer whose research primarily focuses on mobile and distributed systems, with particular interest in IoT-based personalisation, mobile data management, ambient intelligence, computational trust, and intelligent edge computing. I leverage AI and machine learning to enhance digital service delivery, and I have contributed to both national and international research initiatives, including European Horizon 2020 projects.
About
Currently, I'm a Senior Lecturer in Computing with a PhD in Electrical and Computer Engineering (Telecommunication Engineering) from the University of Porto, Portugal. I also hold BSc and MSc (by research) degrees in Computer Engineering and Computer Science, respectively, along with a Postgraduate Certificate in Teaching and Learning in Higher Education. I'm a Fellow of the Higher Education Academy (FHEA) and a member of the IEEE.
I bring a strong blend of academic and industry experience, having previously worked as an IT Engineer in the ICT sector with a focus on networking. My postdoctoral research includes appointments at Liverpool John Moores University (UK), the University of Aveiro, and the Institute of Telecommunications (Portugal). I also served as an R&D Engineer at INESC TEC, where I was awarded both institutional and national research grants, including the prestigious FCT doctoral scholarship.
My research spans mobile and pervasive computing, with emphasis on context-aware systems, mobile data management, ambient intelligence, computational trust, and IoT-driven personalised services. I'm particularly interested in applying AI and machine learning to address emerging challenges in healthcare, energy, and environmental domains through intelligent edge computing and software engineering.
I have contributed to several national and international research initiatives, including European Horizon 2020 projects. My work has been published in leading peer-reviewed journals and conferences, and I regularly serve as a technical committee member, guest editor, and peer reviewer for reputable academic journals and conferences.
My teaching interests include Applied Machine Learning/AI, and Data Science, Distributed Programming, Programming Concepts and Practice. I'm keen to collaborate on interdisciplinary projects that explore innovative, data-driven solutions to real-world problems.
Teaching
School of Computing and Digital Technologies
College of Business, Technology and Engineering
Computer Science and Software Engineering
MSc Big Data Analytics, BEng Software Engineering, MEng Software Engineering, BSc Computer Science
Programming Concepts and Practice, Networked Software Development,Machine Learning Algorithms and Heuristics,Distributed Programming and Technologies, Software Projects, Deep Neural Networks and Learning Systems, Introduction to programming for Big Data.
Research
- Industry and Innovation Research Institute
OHL
The Overhead Line (OHL) network consists of conductors, infrastructure, and electrical assets operating across voltage levels from 132 kV to 230 V. Most OHL conductors are uninsulated, posing significant safety risks—contact or close proximity can result in severe injury or fatality. These incidents not only affect individuals and their families physically and emotionally but also disrupt power supply, impacting customers and creating operational challenges for Distribution Network Operators (DNOs).
Despite the existence of Health and Safety Executive (HSE) guidance note GS6, which outlines precautions for working near overhead lines, cable strikes continue to occur.
This project seeks to develop innovative, technology-driven solutions to proactively prevent OHL strikes, enhance public and workforce safety, and reduce service disruptions.
WiseIoT
The EU H2020 WiseIoT project. WiseIoT is a collaborative project between Europe and South Korea. It aimed at deepening the interoperability and interworking of IoT existing systems. WiseIoT also aimed to develop federated and interoperable platforms ensuring end-to-end security and trust management for reliable business environments. Building synergies with national and international initiatives in both Europe and South Korea, the project also focuses on standardisation to foster IoT application development and interoperability.
SWARMs
The SWARMs project. The goal of the EU H2020 SWARMs project was to expand the use of autonomous underwater and surface vehicles (AUVs, ROVs, USVs) to facilitate conception, planning and execution of maritime and offshore operations and missions.
Research projects
OHL
The Overhead Line (OHL) network is comprised of conductors, infrastructure and electrical assets associated with the overhead network (132 kV to 230 V). In most cases, the OHL conductors are not insulated, therefore if either an object/person comes into contact, or in close proximity to it, it can cause serious injury or death. These injuries can have both physical and mental impacts on the affected person’s quality of life and their families.
Disruption to power, caused by these incidents, and the impact it can have on customers is also an issue for the DNOs.
Health and Safety (HSE) guidance note GS6, is a guidance note for people who may be planning to work near overhead lines where there is a risk of contact with the wires, and describes steps that should be taken to prevent contact with them. Despite this guidance document, cable strikes still occur.
This project aims to develop innovative solutions to assist in preventing OHL strikes.
WiseIoT
The EU H2020 WiseIoT project. WiseIoT is a collaborative project between Europe and South Korea. It aimed at deepening the interoperability and interworking of IoT existing systems. WiseIoT also aimed to develop federated and interoperable platforms ensuring end-to-end security and trust management for reliable business environments. Building synergies with national and international initiatives in both Europe and South Korea, the project also focuses on standardisation to foster IoT application development and interoperability.
SWARMs
The SWARMs project. The goal of the EU H2020 SWARMs project was to expand the use of autonomous underwater and surface vehicles (AUVs, ROVs, USVs) to facilitate conception, planning and execution of maritime and offshore operations and missions.
Publications
Key Publications
Ameh, J., Otebolaku, A., Shenfield, A., & Ikpehai, A. (2025). C3-VULMAP: A Dataset for Privacy-Aware Vulnerability Detection in Healthcare Systems. Electronics, 14 (13). http://doi.org/10.3390/electronics14132703
Ibude, F., Otebolaku, A., Ameh, J., & Ikpehai, A. (2024). Multi-Timescale Energy Consumption Management in Smart Buildings Using Hybrid Deep Artificial Neural Networks. Journal of Low Power Electronics and Applications, 14 (4). http://doi.org/10.3390/jlpea14040054
Omolaja, A., Otebolaku, A., & Alfoudi, A. (2022). Context-Aware complex human activity recognition using hybrid deep learning models. Applied Sciences, 12 (18). http://doi.org/10.3390/app12189305
Alfoudi, A., Newaz, S., Otebolaku, A., Lee, G.M., & Pereira, R. (2019). An efficient resource management mechanism for network slicing in LTE network. IEEE Access, 7, 89441-89457. http://doi.org/10.1109/ACCESS.2019.2926446
Jayasinghe, U., Otebolaku, A., Um, T.-.W., & Lee, G.M. (2018). Data centric trust evaluation and prediction framework for IOT. Proceedings of the 2017 ITU Kaleidoscope Academic Conference: Challenges for a Data-Driven Society, ITU K 2017, 2018-J (2018-J), 1-7. http://doi.org/10.23919/ITU-WT.2017.8246999
Otebolaku, A., & Lee, G.M. (2017). Towards context classification and reasoning in IoT. Proceedings of the 14th International Conference on Telecommunications, ConTEL 2017, 147-154. http://doi.org/10.23919/ConTEL.2017.8000051
Otebolaku, A., & Andrade, M.T. (2016). Context-aware personalization using neighborhood-based context similarity. Wireless Personal Communications, 94 (3), 1595-1618. http://doi.org/10.1007/s11277-016-3701-2
Otebolaku, A., & Andrade, M.T. (2016). User context recognition using smartphone sensors and classification models. Journal of Network and Computer Applications, 66, 33-51. http://doi.org/10.1016/j.jnca.2016.03.013
Otebolaku, A.M., & Andrade, M.T. (2014). A Context-Aware Framework for Media Recommendation on Smartphones. In Lecture Notes in Electrical Engineering, (pp. 87-108). Springer International Publishing: http://doi.org/10.1007/978-3-319-05440-7_8
Otebolaku, A., & Andrade, M.T. (2014). Context-aware media recommendations for smart devices. Journal of Ambient Intelligence and Humanized Computing, 6 (1), 13-36. http://doi.org/10.1007/s12652-014-0234-y
Otebolaku, A., Ameh, J., Ikpehai, A., & Shenfield, A. (2025). Performance Analysis of Lightweight Transformer Models for Healthcare Application Privacy Threat Detection. In 30th European Symposium on Research in Computer Security, Toulouse, France, 22 September 2025 - 26 September 2025. Springer Nature
Journal articles
Mosa, Q.O., Alfoudi, A.S., Brisam, A.A., Otebolaku, A., & Lee, G.M. (2022). Driving Active Contours to Concave Regions. Webology, 19 (1), 5131-5140. http://doi.org/10.14704/web/v19i1/web19345
Alfoudi, A., Alsaeedi, A., Abed, M., Otebolaku, A., & Razooqi, Y. (2021). Palm Vein Identification Based on Hybrid Feature Selection Model. International Journal of Intelligent Engineering and Systems, 14 (5), 469-478. http://doi.org/10.22266/ijies2021.1031.41
Otebolaku, A., Enamamu, T., Alfoudi, A., Ikpehai, A., Marchang, J., & Lee, G.M. (2020). Deep Sensing: Inertial and Ambient Sensing for Activity Context Recognition Using Deep Convolutional Neural Networks. Sensors, 20 (13), 3803. http://doi.org/10.3390/s20133803
Dighriri, M., Otebolaku, A., Alfoudi, A., & Lee, G.M. (2020). Slice Allocation Management Model in 5G Networks for IoT Services with Reliable Low Latency. . http://doi.org/10.20944/preprints202007.0536.v1
Enamamu, T., Otebolaku, A.M., Marchang, J., & Joy, D. (2020). Continuous m-Health Data Authentication Using Wavelet Decomposition for Feature Extraction. Sensors, 20, 5690. http://doi.org/10.3390/s20195690
Otebolaku, A., Enamamu, T., Alfouldi, A., Ikpehai, A., & Marchang, J. (2020). Deep Sensing: Inertia and Ambient Sensing for Activity Context Recognition Using Deep Convolutional Neural Networks. . http://doi.org/10.20944/preprints202005.0430.v1
Enamamu, T., Otebolaku, A., Marchang, J., & Dany, J. (2020). Continuous m-Health Data Authentication Using Wavelet Decomposition for Feature Extraction. Sensors, 20 (19). http://doi.org/10.3390/s20195690
Marchang, J., Wang, J., Otebolaku, A., Enamamu, T., Porter, D., & Sanders, B. (2019). Multidimensional: User with File Content and Server’s status based Authentication for Secure File Operations in Cloud. Current Trends in Computer Sciences & Applications (CTCSA), 1 (5), 108-118. http://doi.org/10.32474/CTCSA.2019.01.000121
Otebolaku, A., & Lee, G.M. (2018). A Framework for Exploiting Internet of Things for Context-Aware Trust-Based Personalized Services. Mobile Information Systems, 2018, 1-24. http://doi.org/10.1155/2018/6138418
Alsaeedi, A.H., Al-Sharqi, M.A., Alkafagi, S.S., Nuiaa, R.R., D. Alfoudi, A.S., Manickam, S., ... Otebolaku, A.M. (n.d.). Hybrid Extend Particle Swarm Optimization (EPSO) model for Enhancing the performance of MANET Routing Protocols. Journal of Al-Qadisiyah for Computer Science and Mathematics, 15 (1). http://doi.org/10.29304/jqcm.2023.15.1.1160
Conference papers
Alfoudi, A.S.D., Dighriri, M., Otebolaku, A., Pereira, R., & Lee, G.M. (2018). Mobility management architecture in different RATs based network slicing. Proceedings - 32nd IEEE International Conference on Advanced Information Networking and Applications Workshops, WAINA 2018, 2018-J (2018-J), 270-274. http://doi.org/10.1109/WAINA.2018.00097
Otebolaku, A.M., & Andrade, M.T. (2014). Context-Aware Media Recommendations. 2014 28th International Conference on Advanced Information Networking and Applications Workshops, 191-196. http://doi.org/10.1109/waina.2014.40
Otebolaku, A.M., & Andrade, M.T. (2014). Context-Aware User Profiling and Multimedia Content Classification for Smart Devices. 2014 28th International Conference on Advanced Information Networking and Applications Workshops, 560-565. http://doi.org/10.1109/waina.2014.92
Otebolaku, A.M., & Andrade, M.T. (2014). Supporting Context-Aware Cloud-Based Media Recommendations for Smartphones. 2014 2nd IEEE International Conference on Mobile Cloud Computing, Services, and Engineering, 109-116. http://doi.org/10.1109/mobilecloud.2014.26
Otebolaku, A.M., & Andrade, M.T. (2013). Recognizing High-Level Contexts from Smartphone Built-In Sensors for Mobile Media Content Recommendation. 2013 IEEE 14th International Conference on Mobile Data Management, 142-147. http://doi.org/10.1109/mdm.2013.84
Otebolaku, A., & Andrade, M.T. (2011). Context representation for context-aware mobile multimedia content recommendation. Proceedings of the 15th IASTED International Conference on Internet and Multimedia Systems and Applications, IMSA 2011, 68-75. http://doi.org/10.2316/P.2011.746-004
Otebolaku, A.M., Iyilade, J.S., & Adigun, M.O. (2008). CAAM: A Context Aware Adaptation Model for Mobile Grid Service Infrastructure. 2008 11th IEEE International Conference on Computational Science and Engineering - Workshops, 419-425. http://doi.org/10.1109/csew.2008.37
A.M., O., M.O., A., Iyilade, J.S., & O.O., E. (2007). On Modeling Adaptation in Context-Aware Mobile Grid Systems. Third International Conference on Autonomic and Autonomous Systems (ICAS'07), 52. http://doi.org/10.1109/conielecomp.2007.90
Book chapters
Otebolaku, A.M., & Andrade, M.T. (2019). Context-Aware Personalization for Mobile Services. In Advances in Computer and Electrical Engineering. (pp. 818-830). IGI Global: http://doi.org/10.4018/978-1-5225-7598-6.ch059
Otebolaku, A., & Andrade, M. (2017). Context-Aware Personalization for Mobile Services. In Khosrow-Pour, M. (Ed.) Encyclopedia of Information Science and Technology, 4th edition. (pp. 6031-6042). IGI-Global: https://www.igi-global.com/book/encyclopedia-information-science-technology-fourth/173015
Otebolaku, A.M., & Andrade, M.T. (2014). Context-Aware Multimedia Content Recommendations for Smartphone Users. In Advances in Information Quality and Management. (pp. 5658-5666). IGI Global: http://doi.org/10.4018/978-1-4666-5888-2.ch559
Presentations
Otebolaku, A. (2015). CAMR APPLICATION A smartphone-based context-awareness framework for mobile multimedia personalization- A demo. Presented at: INESCT TEC, Porto, portugal, 2015
Other activities
I serve as technical committee member for several thematic IEEE conferences and others.
I regularly serve as reviewer and guest editor for several key thematic journals.
I'm also a book reviewer for Manning Publications.
Postgraduate supervision
Currently, I supervise MSc and PhD candidates. Prospective PhD candidates are encouraged to contact me for PhD projects in the area of Ambient Intelligence, Mobile Data Management, Computational Trust, Internet of Intelligence Things (IoIT) and Applications.
Current PhD Candidates:
Jude Enenche Ameh (as Director of Studies), 2023