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Lawal Sulaimon Abiodun

Publications (6)

Artificial Intelligence-driven Supply Chain Optimization for Sustainable Last-mile Delivery in Smart Cities: An Electric Vehicle Routing Approach

Raphael Popoola, Oghogho Favour Aisosa, Lawal Sulaimon Abiodun, Olayinka Adeolu, David, Paul Oluchukwu Mbamalu, Adeleke, Anuoluwapo Rachael & Confidence Adimchi, Chinonyerem · Asian Journal of Advanced Research and Reports · 2025

There has been a rise in demand for affordable, sustainable last-mile delivery services in smart cities due to the upsurge in e-commerce and urbanization. Aside from many challenges to the traditional logistic infrastructure are environmental pollution, excessive operating costs,...

Open access Research Article 10.9734/ajarr/2025/v19i101165

AI-Enabled Digital Twin Framework for Predictive Maintenance and Performance Optimisation of Mechatronic Mechanical Systems

Oluwafunmilayo Ifeoluwa Somoye, Akinsuyi Samson, Rufus Fidelis Ojuoluwa, Lawal Sulaimon Abiodun & Confidence Adimchi Chinonyerem · Asian Journal of Advanced Research and Reports · 2026

The growing integration of artificial intelligence and digital twin technologies into predictive maintenance has greatly contributed to the optimisation of the performance of mechatronics and industrial systems; yet several challenges, related to model validation, scalability, an...

Open access Research Article 10.9734/ajarr/2026/v20i41338

AI-Driven Automation and Digital Twin Framework for Smart Transportation Systems and Predictive Infrastructure Maintenance

Henry Inkum, Chidiebere Anastacia Ezeh, Georgina Fiyinfoluwa Leramo, Adedokun Abdulrahman Adegoke, Lawal Sulaimon Abiodun, Gbadamosi, Damilola Mukahil & Confidence Adimchi Chinonyerem · Asian Journal of Advanced Research and Reports · 2026

With the accelerated pace of urbanisation and growing transport demand, traffic congestion has worsened, while transportation infrastructure has increasingly deteriorated, particularly in rapidly growing metropolises such as Lagos, Nigeria. Traditional transportation management s...

Open access Research Article 10.9734/ajarr/2026/v20i81438

Hybrid Machine Learning-driven Digital Twin Framework for Real-Time Traffic Optimization in Mega Cities

Chidiebere Anastacia Ezeh, Chijioke George Edeh, Yusuf Mohammed-Ali, Onyegbule Tochukwu Victor, Lawal Sulaimon Abiodun & Confidence Adimchi Chinonyerem · Asian Journal of Advanced Research and Reports · 2026

Traffic congestion remains a major challenge in Lagos, causing substantial delays, higher fuel consumption, pollution and reduced productivity. As the city continues to grow and vehicle ownership increases, the existing road infrastructure is insufficient to accommodate rapidly r...

Open access Research Article 10.9734/ajarr/2026/v20i71416

The Role of Digital Twins in Construction Project Lifecycle Management: Enhancing Efficiency and Innovation in the United States

Chijioke George Edeh, Stephenie Oge Nwachukwu, Jideofor Chinedu Anyankah, Mboe Fabiola Lizzy, Israel Ejenawo F. Utho, Lawal Sulaimon Abiodun, Rufus Fidelis Ojuoluwa & Confidence Adimchi Chinonyerem · Asian Journal of Advanced Research and Reports · 2025

Digital Twin (DT) technology use throughout the lifecycle of infrastructure projects is revolutionizing infrastructure planning, construction, and operation in the United States. The paper discusses systematically 138 publications (2016–2024) to analyse DT applications, advantage...

Open access Research Article 10.9734/ajarr/2025/v19i111215

AI-driven Digital Twin Framework for Predictive Maintenance, Asset Integrity Management, and Energy Optimization in Smart Oil and Gas Industrial Systems

Henry Inkum, Chidiebere Anastacia Ezeh, Vanessa Grant, Urhiofe God'sfavour Oghenerabome, Lawal Adeshina Muhammed, Adedokun Abdulrahman Adegoke, Lawal Sulaimon Abiodun & Confidence Adimchi Chinonyerem · Asian Journal of Advanced Research and Reports · 2026

Advances in AI, physics-informed modelling, and Digital Twin technologies offer the potential to enhance predictive maintenance, asset-integrity assessment, and energy management within oil and gas processing systems. However, these frameworks are most useful when they are based...

Open access Research Article 10.9734/ajarr/2026/v20i91456