Chijioke George Edeh

A Machine Learning-Based Framework for Real-Time Environmental Health Risk Prediction and Spatial Air Quality Intelligence in Urban-Industrial Ecosystems

Chijioke George Edeh, Gloria Opoku Darkoh, Shobayo Ifeoluwanimi Praise, Julius Odemi Brown, Rufus Fidelis Ojuoluwa, Omotayo Christopher Afolabi, Waliu Temidayo Asamu, Ifeoluwa Odunayo Olofinsao, Nana Firdausi Hassan & Akinsuyi Samson · Asian Journal of Advanced Research and Reports · 2026

The high rate of industrialization and urbanization has enhanced the pollution of the environment and the occurrence of occupational health hazards especially in urban-industrial ecosystems where people are subjected to cumulative environmental and occupational hazards. Tradition...

Open access Research Article 10.9734/ajarr/2026/v20i41324

Integration of Digital Twin Platforms with Machine Learning Models for Early Detection of Project Delays and Cost Overruns

Chijioke George Edeh, Prosper Tanyaradzwa Masakara, Jideofor Chinedu Anyankah, Ridwan Bale, Rufus Fidelis Ojuoluwa, Israel Ejenawo F. Utho, Adebayo Victor Adebayo & Confidence Adimchi, Chinonyerem · Asian Journal of Advanced Research and Reports · 2026

The problem of recurring schedule delays and cost overruns has long been one of the biggest challenges in the management of construction projects. Recent technological developments in Digital Twin and Machine Learning technologies provide project managers with promising opportuni...

Open access Research Article 10.9734/ajarr/2026/v20i11271

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

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

Digital Transformation and Business Growth in Emerging Markets: A PRISMA-Based Systematic Literature Review of Strategic Leadership and Data Analytics

Kehinde Akinwale, Chijioke George Edeh, Blessing Itodo, Patricia Ugochi Uzoma, Osakpolor Emmanuel Orobor, Philip Williams Appiah-Agyei, Alabi Modinat & Confidence Adimchi Chinonyerem · Asian Journal of Advanced Research and Reports · 2026

As a strategic imperative in the context of emerging markets, digital transformation is associated with institutional, infrastructural, and technological challenges, but also with great potential for supporting the sustainable performance of firms facing rapid change in such an e...

Open access Research Article 10.9734/ajarr/2026/v20i61389

Development of an AI-Driven Digital Twin Framework for Predictive Maintenance of Urban Infrastructure Systems

Aderibigbe Michael Oluwaseyi, Ogunmusemi Tunde Ebini Dele, Chijioke George Edeh, Francis Chibueze Onyekwelu, Osakpolor Emmanuel Orobor, Afolabi, Omotayo Christopher, Rufus Fidelis Ojuoluwa & Confidence Adimchi Chinonyerem · Asian Journal of Advanced Research and Reports · 2026

Modern urban infrastructure systems are becoming increasingly vulnerable to deterioration caused by ageing equipment, growing service demands, and environmental stressors, making traditional reactive and preventive maintenance approaches insufficient to ensure long-term system re...

Open access Research Article 10.9734/ajarr/2026/v20i71421