Article Per Year (5 Year)
p-Index From 2021 - 2026
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This Author published in this journals
All Journal International Journal of Science Education and Cultural Studies Vokasi UNESA Bulletin of Engineering, Technology and Applied Science
Najeem Olawale Adelakun
Federal College of Education Iwo, Osun State
Computer Science & IT Education Engineering Languange, Linguistic, Communication & Media Mechanical Engineering Transportation Other

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Empirical Study on Electronic Learning System: Benefits, Challenges and Prospects Najeem Olawale Adelakun; Samuel Adeniyi Omolola; Azeez Olamilekan Mosaku; Matthew Saint Adebola
International Journal of Science Education and Cultural Studies Vol. 1 No. 2 (2022): ijsecs
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1088.028 KB) | DOI: 10.58291/ijsecs.v1i2.58

Abstract

The swift growth of digital technology has led to the adoption of emerging technologies in all human endeavours. Over the years, the rate of smartphone users has increased rapidly which makes so many developed nations adopt online learning as a means of taking education to everyone irrespective of their geographical location. Similarly, the COVID-19 outbreak makes so many developing countries adopt the electronic learning system as a viable approach to teaching and learning. Consequently, the e-learning system is useful for the creation of informative online sessions, supplementary lessons for students, webinars, e-mentoring and online conferences. This paper uses an empirical approach to evaluate the benefits and challenges associated with the e-learning system, and a survey was conducted among students in a higher institution in Nigeria to know the likely challenges faced by students with the e-learning system and also at different online researchers forum across the globe. A total of four hundred and ninety-five (495) responses were gathered and the data was analysed using descriptive statistics. The result shows that 33.94% of students complained about weak internet connectivity from the questionnaire administered which is also a major problem in most developing nations, while only 7.27% of respondents complained about limited feedback, it is recommended that there should be a provision of standard IT infrastructure, strong internet connectivity, and user-friendly e-learning platform, its implementation will improve performance and lead to greater productivity.
A Systematic Review of Artificial Intelligence in Autonomous and Sustainable Transportation Systems: Evolution, Current Applications and Future Directions Najeem Olawale Adelakun; Matthew Babatunde Olajide; Samuel Adeniyi Omolola
Vokasi UNESA Bulletin of Engineering, Technology and Applied Science Vol. 3 No. 3 (2026): (In Progress)
Publisher : Universitas Negeri Surabaya or The State University of Surabaya

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Abstract

The concept of Artificial Intelligence (AI) rapidly redefines the principles of the modern transportation system, allowing transitioning to autonomous, efficient, and sustainable mobility. This paper provides a systematic review of the history, present, and future of AI in autonomous and sustainable transport systems. Both the foundational studies and recent developments in the field were synthesised in a structured and rigorous methodology. The review follows the development of AI in transportation since primitive rule-based and heuristic methods to more modern data-driven paradigms founded on machine learning and deep learning. It reviews the state-of-the-art applications in major areas, such as traffic control and prediction, self-driving and connected cars, smart infrastructure, safety optimisation and energy-conscious mobility systems. The special focus is made on AI integration with electrical power systems, where smart algorithms can improve energy efficiency, optimise the process of charging electric vehicles, and allow smart grid coordination. Moreover, the paper pinpoints ongoing issues such as data quality constraints, model interpretability, cybersecurity risks, infrastructure constraints and regulatory fragmentation especially in developing areas. In turn, the new research directions are presented, including the potential in energy-conscious AI models, federated learning, federated with digital twin technologies, and multi-modal intelligent mobility ecosystems. Its findings position artificial intelligence as a primary enabler of the next-generation transportation systems, which is a way to make transportation safer, more efficient, and environmentally sustainable.
Co-Authors Azeez Olamilekan Mosaku Matthew Babatunde Olajide Matthew Saint Adebola Samuel Adeniyi Omolola Samuel Adeniyi Omolola