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.

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.

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.

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.

Benchmarks for energy access: Policy vagueness and incoherence as barriers to sustainable electrification of the global south (2019)
Journal Article
Monyei, C. G., Oyedele, L. O., Akinade, O. O., Ajayi, A. O., & Luo, X. J. (2019). Benchmarks for energy access: Policy vagueness and incoherence as barriers to sustainable electrification of the global south. Energy Research and Social Science, 54, 113-116. https://doi.org/10.1016/j.erss.2019.04.005

© 2019 The unavailability of tangible policy benchmarks continues to mitigate against sustainable electrification in the global south. Furthermore, incoherent policy benchmarks as to what should constitute clean energy allow for varying interpretatio... Read More about Benchmarks for energy access: Policy vagueness and incoherence as barriers to sustainable electrification of the global south.

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.