Dr Abayomi Otebolaku

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Dr Abayomi Otebolaku BSc, MSc, PhD, FHEA

Senior Lecturer


Dr Otebolaku is currently a Senior Lecturer in Computing, and a research active member of the Department of Computing where he teaches and leads modules in computer science and software engineering at both undergraduate and postgraduate levels.

His research interest is within the broad span of mobile and distributed computing. Specifically, his core expertise is within context sensing, mobile data management, and IoT-driven service personalization using machine learning and AI. His research work has been applied in several research projects including European H2020 projects.

He is particularly interested in internet of Intelligent things (IoIT), Edge Computing and Ambient Intelligence (AmI) with applications in digital health, environment, and energy.


Dr Otebolaku received his PhD in Electrical and Computer Engineering (Telecommunication Engineering) from the Electrical and Computer Engineering department, Faculty of Engineering, University of Porto, Portugal. Prior to his PhD, he received BSc and MSc (by research) degrees in Computer Engineering and Computer Science respectively.

Prior to studying for Postgraduate degrees, he worked in the ICT industry as an IT Engineer specialising in networking. He was a Postdoctoral Research Associate in the Department of Computer Science, Faculty of Engineering and Technology, Liverpool John Moores University, Liverpool, U.K.  He was also a Postdoctoral Research Associate in the Department of Electronics, Telecommunications and Informatics, University of Aveiro, and the Institute of Telecommunications, Aveiro, Portugal.

He was a Research and Development Engineer at the Centre for Telecommunications and Multimedia, INESC TEC (formerly INESC Porto) also in Portugal. He received the INESC TEC grants for doctoral research and the Portuguese’s government prestigious Fundacao para Ciencia e a Tecnologia (Foundation for Science and Technology, FCT) full doctoral research grants (Bolsa de Deutoramento).

Dr Otebolaku is an active researcher with participation in several research projects, including European H2020 Projects where his research outputs have been applied. His research focuses broadly on mobile and pervasive computing, and specifically on context-aware systems, context sensing, mobile data management, and IoT-driven personalized services.  He has published widely in leading thematic peer-reviewed international journals and conferences. In addition, he serves as a technical committee member for several reputable international conferences and workshops, and as guest editor for reputable thematic journals.  He is also a peer reviewer for several journals and conference proceedings.

He is passionate about the application of Artificial Intelligence (AI) and Machine Learning (ML) within mobile and distributed computing to address emerging challenges, focusing on ambient intelligence, specifically on context sensing, intelligent service personalisation, and Internet of Intelligent Things(IoIT).  In the past, his research addressed various problems in the domain of context-aware mobile multimedia systems, providing personalized mobile multimedia delivery and consumptions using intelligence obtained from mobile sensory data. Besides, he has addressed problems in ambient context sensing and recognition, and its applications in the design and implementation of context-aware personalised user preferences. These involve the design, development, and deployment of intelligent applications on smart devices. His current work focuses on the application of AI/ML, Edge Computing and Software Engineering to address real-world problems in energy, healthcare, and environments.

His main teaching interests are in Computer Science and Software Engineering including Distributed Programming, AI/ML, and Data Science.

He is a Fellow of the Higher Education Academy (FHEA) and a member of the Institute of Electrical and Electronics Engineers (IEEE).


Department of Computing , Department of Culture and Media

College of Business, Technology and Engineering

In the last 12 years, I have been involved in several research projects such as:

The H2020 Wise-IoT project. The outcome of the project was the development of a federated and interoperable IoT platform that ensures end-to-end security and trust for reliable business environments.

The H2020 SWARMs project. The project delivered an integrated platform for a new generation of autonomous maritime and underwater robotic operations as a set of software/hardware components for improving autonomy, robustness, cost-effectiveness, and reliability through autonomous vehicle cooperation. My involvement was in the design and implementation of the context sensing and context awareness framework for the project.

The MAT (Media Arts and Technology) an EU project at INESC TEC with technical contributions in context-aware mobile multimedia content delivery using smartphone sensors.

Computer Science and Software Engineering

BSc Computer Science, B.Eng Software Engineering and MSc Big Data Analytics

  • Networked Software Development
  • Programming Concepts and Practice
  • Distributed Programming and Technologies
  • Mobile App development on the Android platform
  • Software Projects


My research interest is within the broad span of mobile/pervasive and distributed computing. Specifically, it lies within context-aware computing (context-awareness, smart context sensing and recognition), mobile data management, and IoT-driven personalisation using machine learning and AI.

I am passionate about the following areas:

  • Context sensing and high-level context influence using Semantic Web and deep learning algorithms
  • Context-aware human activity recognition on Edge/IoT devices
  • Explainable and personalised sensor based human activity recognition
  • Advanced trust evaluation and predictions for IoE
  • Context-aware personalised recommendation systems
  • Personalised recommendation services in healthcare systems   

Research projects


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.

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.

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, which is scheduled to kick off this summer (2023), is explore/develop innovative solutions that could assist in preventing OHL strikes.


Key Publications

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

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

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

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

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. 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. 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. 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. 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. 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). 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 Encyclopedia of Information Science and Technology, Third Edition. (pp. 5658-5666). IGI Global: http://doi.org/10.4018/978-1-4666-5888-2.ch559

Other activities

Journal /Book Review and invited Talks
IEEE Access, MDPI Sensors, Electronics, Symmetry, Sustainability, Computers, Technologies, Applied Sciences, Sensors and Actuator, Computers,  Information, and Electronics Others are Springer Ambient Intelligence and Humanized Computing, IEEE Transactions on network and service management, ACM Transactions on Internet Technologies, ACM transactions on Internet of Things, IEEE Transactions on Industrial Informatics, Taylor & Francis Connection Science, Elsevier Journal of networks and computer applications, Springer Multimedia Tools and Applications, Mobile Information Systems, etc.

Conference Technical Committee Member /Reviewer
Technical Reviewer for IEEE Sensors Conference (2019), Montreal, Canada.
2021 IEEE 94th Vehicular Technology Conference
Technical Programme committee, 9th International Conference on Information and Communication Technologies for Ageing Well and e-Health (ICT4AWE 2023)
Technical Programme committee, 9th International Conference on Information and Communication Technologies for Ageing Well and e-Health (ICT4AWE 2024)
Technical Programme committee, 10th International Conference on Information and Communication Technologies for Ageing Well and e-Health (ICT4AWE 2024)
Technical committee 2021 IEEE 94th   Vehicular Technology Conference.
Technical Programme Committee, 5th IEEE International Workshop on Pervasive and Context-Aware Middleware (PerCAM 17), Rome, Italy.
IEEE International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob 2018)
Technical Committee member, 6th International Conference on Frontiers of Signal Processing (ICFSP 2021), Paris, France.
Technical Committee member, 3rd   Asia Symposium on Signal Processing, 2023
Technical Committee member, 4th   Asia Symposium on Signal Processing,2024, etc.

Book Reviewer
Manning Publications

Postgraduate supervision

I currently 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, Internet of Intelligence Things(IoIT) and its applications.

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