Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI)
Matthew Olusegun Adigun
University of Zululand
Computer Science & IT Electrical & Electronics Engineering Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Performance investigation of two-stage detection techniques using traffic light detection dataset Sunday Adeola Ajagbe; Adekanmi Adeyinka Adegun; Ahmed Babajide Olanrewaju; John Babalola Oladosu; Matthew Olusegun Adigun
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 12, No 4: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v12.i4.pp1909-1919

Abstract

Using a camera to monitor an object or a group of objects over time is the process of object detection. It can be used for a variety of things, including security and surveillance, video communication, traffic light detection (TLD), object detection from compressed video in public places. In recent times, object tracking has become a popular topic in computer science particularly, the data science community, thanks to the usage of deep learning (DL) in artificial intelligence (AI). DL which convolutional neural network (CNN) as one of its techniques usually used two-stage detection methods in TLD. Despite all successes recorded in TLD through the use of two-stage detection methods, there is no study that has analyzed these methods in experimental research, studying the strength and witnesses by the researchers. Based on the needs this study analyses the applications of DL techniques in TLD. We implemented object detection for TLD using 5 two-stage detection methods with the traffic light dataset using a Jupyter notebook and the sklearn libraries. We present the achievements of two-stage detection methods in TLD, going by standard performance metrics used, FASTER-CNN was the best in detection accuracy, F1-score, precision and recall with 0.89, 0.93, 0.83 and 0.90 respectively.
Integration of micro-grids into Nigeria’s power system: Challenges, policy perspectives and opportunities for sustainable energy access Ismaheel O. Oladejo; Sunday Adeola Ajagbe; Razaaq A. Adetutu; Mathew Timothy Oluwafemi; Matthew Olusegun Adigun
International Journal of Electrical and Computer Engineering (IJECE) Vol 16, No 5: October 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v16i5.pp2321-2334

Abstract

Nigeria’s electricity sector faces persistent challenges, including insufficient generation capacity, weak transmission and distribution networks, frequent outages, and continued reliance on fossil-fuel-based power. These limitations constrain economic growth and highlight the need for more resilient, decentralized, and sustainable electricity solutions. This paper presents a systematic review of the integration of micro-grids (MGs) into Nigeria’s power system, focusing on reliability improvement, control strategies, renewable energy integration, and implementation barriers. The review synthesizes literature from major academic databases to examine the current state of Nigeria’s power sector, the drivers for MG deployment, global development trends, and the policy framework supporting adoption. It evaluates the role of MGs in enhancing reliability, voltage support, resilience, rural electrification, and energy access, particularly through the use of renewable energy sources, battery energy storage systems, and intelligent energy management. Key technical issues considered include islanding capability, protection coordination, reliability indices, hierarchical control structures, and both grid-connected and standalone operation within the Nigerian context. The paper’s main contribution is a comprehensive engineering-based assessment of the reliability, control, and integration requirements of MGs in Nigeria, while also identifying major policy, financial, and infrastructural constraints. Overall, the review concludes that MGs offer a practical pathway toward a more reliable, sustainable, and inclusive electricity supply system in Nigeria.
Co-Authors Adekanmi Adeyinka Adegun Ahmed Babajide Olanrewaju Ismaheel O. Oladejo John Babalola Oladosu Mathew Timothy Oluwafemi Razaaq A. Adetutu Sunday Adeola Ajagbe Sunday Adeola Ajagbe