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.

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.

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.

Robotics and automated systems in construction: Understanding industry-specific challenges for adoption (2019)
Journal Article
Davila Delgado, J. M., Oyedele, L., Ajayi, A., Akanbi, L., Akinade, L., Bilal, M., & Owolabi, H. (2019). Robotics and automated systems in construction: Understanding industry-specific challenges for adoption. Journal of Building Engineering, 26, Article 100868. https://doi.org/10.1016/j.jobe.2019.100868

© 2019 The Authors The construction industry is a major economic sector, but it is plagued with inefficiencies and low productivity. Robotics and automated systems have the potential to address these shortcomings; however, the level of adoption in th... Read More about Robotics and automated systems in construction: Understanding industry-specific challenges for adoption.

Smart Cities Implementation: Challenges in Nigeria (2019)
Presentation / Conference
kadiri, K., Oyedele, L., Owolabi, H., Akinade,, O., Akanbi,, L., & Gbadamosi, A. (2019, June). Smart Cities Implementation: Challenges in Nigeria. Presented at CIB World Building Congress 2019, Hong Kong SAR, China

A city is a large human settlement that have extensive systems for housing, transportation, sanitation, utilities, land use, and communication. Their density facilitates interaction between people, government organizations and businesses, sometimes b... Read More about Smart Cities Implementation: Challenges in Nigeria.

Development of an IoT-based big data platform for day-ahead prediction of building heating and cooling demands (2019)
Journal Article
Luo, X. J., Oyedele, L. O., Ajayi, A. O., Monyei, C. G., Akinade, O. O., & Akanbi, L. A. (2019). Development of an IoT-based big data platform for day-ahead prediction of building heating and cooling demands. Advanced Engineering Informatics, 41, Article 100926. https://doi.org/10.1016/j.aei.2019.100926

© 2019 Elsevier Ltd The emerging technologies of the Internet of Things (IoT) and big data can be utilised to derive knowledge and support applications for energy-efficient buildings. Effective prediction of heating and cooling demands is fundamental... Read More about Development of an IoT-based big data platform for day-ahead prediction of building heating and cooling demands.

Disassembly and deconstruction analytics system (D-DAS) for construction in a circular economy (2019)
Journal Article
Akanbi, L. A., Oyedele, L. O., Omoteso, K., Bilal, M., Akinade, O. O., Ajayi, A. O., …Owolabi, H. A. (2019). Disassembly and deconstruction analytics system (D-DAS) for construction in a circular economy. Journal of Cleaner Production, 223, 386-396. https://doi.org/10.1016/j.jclepro.2019.03.172

© 2019 Despite the relevance of building information modelling for simulating building performance at various life cycle stages, Its use for assessing the end-of-life impacts is not a common practice. Even though the global sustainability and circula... Read More about Disassembly and deconstruction analytics system (D-DAS) for construction in a circular economy.