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Big data innovation and implementation in projects teams: Towards a SEM approach to conflict prevention (2024)
Journal Article
Owolabi, H., Oyedele, A. A., Oyedele, L., Alaka, H., Olawale, O., Aju, O., …Ganiyu, S. (in press). Big data innovation and implementation in projects teams: Towards a SEM approach to conflict prevention. Information Technology and People, https://doi.org/10.1108/ITP-06-2019-0286

Purpose: Despite an enormous body of literature on conflict management, intra-group conflicts vis-à-vis team performance, there is currently no study investigating the conflict prevention approach to handling innovation-induced conflicts that may hin... Read More about Big data innovation and implementation in projects teams: Towards a SEM approach to conflict prevention.

A multi-dimensional evaluative framework for examining project reputation within the construction industry: Contractors' perspective (2024)
Thesis
Olawale, O. A multi-dimensional evaluative framework for examining project reputation within the construction industry: Contractors' perspective. (Thesis). University of the West of England. Retrieved from https://uwe-repository.worktribe.com/output/11074652

The construction industry, intrinsically project-focused, faces significant challenges in managing project reputation. High-profile incidents like the collapse of the Charles de Gaulle Airport terminal and the Grenfell Tower fire have starkly highlig... Read More about A multi-dimensional evaluative framework for examining project reputation within the construction industry: Contractors' perspective.

An internet of things enabled system for real-time monitoring and predictive maintenance of railway infrastructure (2023)
Thesis
Gbadamosi, A. An internet of things enabled system for real-time monitoring and predictive maintenance of railway infrastructure. (Thesis). University of the West of England. Retrieved from https://uwe-repository.worktribe.com/output/10928540

The railway industry plays a pivotal role in the socioeconomic landscape of many countries. However, its operation poses considerable challenges in terms of safety, environmental impact, and the intricacies of intertwined technical and social structu... Read More about An internet of things enabled system for real-time monitoring and predictive maintenance of railway infrastructure.

A review of the performance of CHIRPS and future research directions in hydro-climatic studies (2023)
Journal Article
Du, H., Tan, M. L., Zhang, F., Chun, K., Li, L., & Humayun Kabir, M. (in press). A review of the performance of CHIRPS and future research directions in hydro-climatic studies. Theoretical and Applied Climatology,

Long-term gridded precipitation products (GPPs) are crucial for climatology and hydrological research to overcome the limitations of gauge observations. Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) provides long-term daily... Read More about A review of the performance of CHIRPS and future research directions in hydro-climatic studies.

Computer vision and IoT research landscape for health and safety management on construction sites (2023)
Journal Article
Arshad, S., Akinade, O., Bello, S., & Bilal, M. (2023). Computer vision and IoT research landscape for health and safety management on construction sites. Journal of Building Engineering, 76, Article 107049. https://doi.org/10.1016/j.jobe.2023.107049

Aims: Perform a systematic review of current literature to evaluate and summarise the health and safety hazards on construction sites. Methods: Science Direct, SCOPUS and web of science databases were searched for research articles published from 201... Read More about Computer vision and IoT research landscape for health and safety management on construction sites.

Deep learning-based multi-target regression for traffic-related air pollution forecasting (2023)
Journal Article
Akinosho, T. D., Bilal, M., Hayes, E. T., Ajayi, A., Ahmed, A., & Khan, Z. (2023). Deep learning-based multi-target regression for traffic-related air pollution forecasting. Machine Learning with Applications, 12, Article 100474. https://doi.org/10.1016/j.mlwa.2023.100474

Traffic-related air pollution (TRAP) remains one of the main contributors to urban pollution and its impact on climate change cannot be overemphasised. Experts in developed countries strive to make optimal use of traffic and air qua... Read More about Deep learning-based multi-target regression for traffic-related air pollution forecasting.

Life cycle optimisation of building retrofitting considering climate change effects (2022)
Journal Article
Luo, X. J., & Oyedele, L. O. (2022). Life cycle optimisation of building retrofitting considering climate change effects. Energy and Buildings, 258, 111830. https://doi.org/10.1016/j.enbuild.2022.111830

Novelty: Climate change has significant impacts on building energy performance. A novel life cycle optimisation strategy is developed for determining optimal retrofitting solutions for office buildings with climate change effects taken into considera... Read More about Life cycle optimisation of building retrofitting considering climate change effects.

A self-adaptive deep learning model for building electricity load prediction with moving horizon (2022)
Journal Article
Luo, X., & Oyedele, L. (2022). A self-adaptive deep learning model for building electricity load prediction with moving horizon. Machine Learning with Applications, 7, Article 100257. https://doi.org/10.1016/j.mlwa.2022.100257

A self-adaptive deep learning model powered by ranking selection-based particle swarm optimisation (RSPSO) is developed to predict electricity load in buildings with moving horizons. The main features of the load prediction model include its self-ada... Read More about A self-adaptive deep learning model for building electricity load prediction with moving horizon.

Construction site layout planning methods: An analytical review (2021)
Conference Proceeding
Otukogbe, G., Oyedele, L., Akanbi, L., Manuel Davila-Delgado, M., Owolabi, H., Ganiyu, S., …Kadiri, K. (2021). Construction site layout planning methods: An analytical review. In Proc. of the IDoBE International Conference on Uncertainty in the Built Environment: How can we build a resilient future in the new normal?

Designing an effective construction site layout planning is essential to the successful implementation of construction projects. Construction site layout planning involves the optimal layout of facilities (i.e., fixed, and temporary facilities). Seve... Read More about Construction site layout planning methods: An analytical review.

Rainfall Prediction: A Comparative Analysis of Modern Machine Learning Algorithms for Time-Series Forecasting (2021)
Journal Article
Barrera Animas, A., Oladayo Oyedele, L., Bilal, M., Dolapo Akinosho, T., Davila Delgado, J. M., & Adewale Akanbi, L. (2022). Rainfall Prediction: A Comparative Analysis of Modern Machine Learning Algorithms for Time-Series Forecasting. Machine Learning with Applications, 7, Article 100204. https://doi.org/10.1016/j.mlwa.2021.100204

Rainfall forecasting has gained utmost research relevance in recent times due to its complexities and persistent applications such as flood forecasting and monitoring of pollutant concentration levels, among others. Existing models use complex statis... Read More about Rainfall Prediction: A Comparative Analysis of Modern Machine Learning Algorithms for Time-Series Forecasting.

A data-driven life-cycle optimisation approach for building retrofitting: A comprehensive assessment on economy, energy and environment (2021)
Journal Article
Luo, X. J., & Oyedele, L. O. (2021). A data-driven life-cycle optimisation approach for building retrofitting: A comprehensive assessment on economy, energy and environment. Journal of Building Engineering, 43, Article 102934. https://doi.org/10.1016/j.jobe.2021.102934

A novel data-driven life-cycle optimisation approach is proposed for building retrofitting. The innovation points include big-data information, integrated retrofitting design, and life-cycle optimisation through a comprehensive assessment of the econ... Read More about A data-driven life-cycle optimisation approach for building retrofitting: A comprehensive assessment on economy, energy and environment.

Big data for design options repository: Towards a DFMA approach for offsite construction (2020)
Journal Article
Gbadamosi, A., Oyedele, L., Mahamadu, A., Kusimo, H., Bilal, M., Davila Delgado, J. M., & Muhammed-Yakubu, N. (2020). Big data for design options repository: Towards a DFMA approach for offsite construction. Automation in Construction, 120, Article 103388. https://doi.org/10.1016/j.autcon.2020.103388

A persistent barrier to the adoption of offsite construction is the lack of information for assessing prefabrication alternatives and the choices of suppliers. This study integrates three aspects of offsite construction, including BIM, DFMA and big d... Read More about Big data for design options repository: Towards a DFMA approach for offsite construction.

Deep learning in the construction industry: A review of present status and future innovations (2020)
Journal Article
Akinosho, T. D., Oyedele, L. O., Bilal, M., Ajayi, A. O., Delgado, M. D., Akinade, O. O., & Ahmed, A. A. (2020). Deep learning in the construction industry: A review of present status and future innovations. Journal of Building Engineering, 32, Article 101827. https://doi.org/10.1016/j.jobe.2020.101827

The construction industry is known to be overwhelmed with resource planning, risk management and logistic challenges which often result in design defects, project delivery delays, cost overruns and contractual disputes. These challenges have instigat... Read More about Deep learning in the construction industry: A review of present status and future innovations.

Project reputation in construction: A process-based perspective of construction practitioners in the UK (2020)
Journal Article
Olawale, O., Oyedele, L., Owolabi, H., Gbadamosi, A., & Kusimo, H. (2022). Project reputation in construction: A process-based perspective of construction practitioners in the UK. International Journal of Construction Management, 22(12), https://doi.org/10.1080/15623599.2020.1783598

The overall aim of this study is to elicit the perspective of practitioners (e.g., architects, civil engineers, building engineers, structural engineers and quantity surveyors) on the process-related factors influencing the project reputation of cons... Read More about Project reputation in construction: A process-based perspective of construction practitioners in the UK.

Big data innovation and diffusion in projects teams: Towards a conflict prevention culture (2020)
Journal Article
Oyedele, A., Owolabi, H. A., Oyedele, L. O., & Olawale, O. A. (2020). Big data innovation and diffusion in projects teams: Towards a conflict prevention culture. Developments in the Built Environment, 3, Article 100016. https://doi.org/10.1016/j.dibe.2020.100016

Despite the enormous literature on how team conflicts can be managed and resolved, this study diverges, by examining factors that facilitate conflict prevention culture in project teams, especially when introducing Big Data Technology. Relying on fin... Read More about Big data innovation and diffusion in projects teams: Towards a conflict prevention culture.

Construction practitioners’ perception of key drivers of reputation in mega-construction projects (2020)
Journal Article
Olawale, O. A., Oyedele, L. O., & Owolabi, H. A. (2020). Construction practitioners’ perception of key drivers of reputation in mega-construction projects. Journal of Engineering, Design and Technology, 18(6), 1571-1592. https://doi.org/10.1108/JEDT-10-2019-0255

Purpose: The purpose of this study is to commence the discourse on the non-inclusiveness of the dynamics of reputation within the construction industry by identifying and examining the key product and process drivers of reputation in mega-constructio... Read More about Construction practitioners’ perception of key drivers of reputation in mega-construction projects.

Optimised Big Data analytics for health and safety hazards prediction in power infrastructure operations (2020)
Journal Article
Ajayi, A., Oyedele, L., Akinade, O., Bilal, M., Owolabi, H., Akanbi, L., & Delgado, J. M. D. (2020). Optimised Big Data analytics for health and safety hazards prediction in power infrastructure operations. Safety Science, 125, Article 104656. https://doi.org/10.1016/j.ssci.2020.104656

© 2020 Elsevier Ltd Forecasting imminent accidents in power infrastructure projects require a robust and accurate prediction model to trigger a proactive strategy for risk mitigation. Unfortunately, getting ready-made machine learning algorithms to e... Read More about Optimised Big Data analytics for health and safety hazards prediction in power infrastructure operations.

Big data analytics system for costing power transmission projects (2019)
Journal Article
Delgado, J. M. D., Oyedele, L., Bilal, M., Ajayi, A., Akanbi, L., & Akinade, O. (2020). Big data analytics system for costing power transmission projects. Journal of Construction Engineering and Management, 146(1), https://doi.org/10.1061/%28ASCE%29CO.1943-7862.0001745

© 2019 American Society of Civil Engineers. Inaccurate cost estimates have significant impacts on the final cost of power transmission projects and erode profits. Methods for cost estimation have been investigated thoroughly, but they are not used wi... Read More about Big data analytics system for costing power transmission projects.

Critical success factors for ensuring bankable completion risk in PFI/PPP megaprojects (2019)
Journal Article
Owolabi, H. A., Oyedele, L. O., Alaka, H. A., Ajayi, S. O., Akinade, O. O., & Bilal, M. (2020). Critical success factors for ensuring bankable completion risk in PFI/PPP megaprojects. Journal of Management in Engineering, 36(1), https://doi.org/10.1061/%28ASCE%29ME.1943-5479.0000717

© 2019 American Society of Civil Engineers. This study investigates project financiers' perspectives on the bankability of completion risk in private finance initiative and public-private partnership (PFI/PPP) megaprojects. Using a mixed methodology... Read More about Critical success factors for ensuring bankable completion risk in PFI/PPP megaprojects.

Complexities of smart city project success: A study of real-life case studies (2019)
Presentation / Conference
Olawale, O., Oyedele, L., Owolabi, H., Kusimo, H., Gbadamosi, A., Akinosho, T., …Olojede, I. (2019, July). Complexities of smart city project success: A study of real-life case studies. Presented at CIB World Building Congress 2019, Hong Kong SAR, China

Over the years, the world has moved towards an unprecedented level of urbanisation as half of the world’s total population live in cities. This trajectory of rapid urbanisation has greatly improved the modern economy as well as the standard of living... Read More about Complexities of smart city project success: A study of real-life case studies.