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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.

Conversational artificial intelligence in the AEC industry: A review of present status, challenges and opportunities (2023)
Journal Article
Saka, A. B., Oyedele, L. O., Akanbi, L. A., Ganiyu, S. A., Chan, D. W., & Bello, S. A. (2023). Conversational artificial intelligence in the AEC industry: A review of present status, challenges and opportunities. Advanced Engineering Informatics, 55, 101869. https://doi.org/10.1016/j.aei.2022.101869

The idea of developing a system that can converse and understand human languages has been around since the 1200 s. With the advancement in artificial intelligence (AI), Conversational AI came of age in 2010 with the launch of Apple's Siri. Conversati... Read More about Conversational artificial intelligence in the AEC industry: A review of present status, challenges and opportunities.

Performance evaluation of deep learning and boosted trees for cryptocurrency closing price prediction (2022)
Journal Article
Oyedele, A. A., Ajayi, A., Oyedele, A., Bello, S., & Oyedele, L. (2023). Performance evaluation of deep learning and boosted trees for cryptocurrency closing price prediction. Expert Systems with Applications, 213(Part C), Article 119233. https://doi.org/10.1016/j.eswa.2022.119233

The emergence of cryptocurrencies has drawn significant investment capital in recent years with an exponential increase in market capitalization and trade volume. However, the cryptocurrency market is highly volatile and burdened with substantial het... Read More about Performance evaluation of deep learning and boosted trees for cryptocurrency closing price prediction.

Robotics in construction: A critical review of the reinforcement learning and imitation learning paradigms (2022)
Journal Article
Davila Delgado, M., & Oyedele, L. (2022). Robotics in construction: A critical review of the reinforcement learning and imitation learning paradigms. Advanced Engineering Informatics, 54, Article 101787. https://doi.org/10.1016/j.aei.2022.101787

The reinforcement and imitation learning paradigms have the potential to revolutionise robotics. Many successful developments have been reported in literature; however, these approaches have not been explored widely in robotics for construction. The... Read More about Robotics in construction: A critical review of the reinforcement learning and imitation learning paradigms.

Internet of things and machine learning techniques in poultry health and welfare management: A systematic literature review (2022)
Journal Article
Ojo, R. O., Ajayi, A. O., Owolabi, H. A., Oyedele, L. O., & Akanbi, L. A. (2022). Internet of things and machine learning techniques in poultry health and welfare management: A systematic literature review. Computers and Electronics in Agriculture, 200, Article 107266. https://doi.org/10.1016/j.compag.2022.107266

The advent of digital technologies has brought substantial improvements in various domains. This article provides a comprehensive review of research emphasizing AI-enabled IoT applications in poultry health and welfare management. This study focused... Read More about Internet of things and machine learning techniques in poultry health and welfare management: A systematic literature review.

A deep learning approach to concrete water-cement ratio prediction (2022)
Journal Article
Oyedele, L., Bello, S., Olaitan, O. K., Olonade, K. A., Olajumoke, A. M., Ajayi, A., …Bello, A. L. (2022). A deep learning approach to concrete water-cement ratio prediction. Results in Materials, 15(September 2022), Article 100300. https://doi.org/10.1016/j.rinma.2022.100300

Concrete is a versatile construction material, but the water content can greatly influence its quality. However, using the trials and error method to determine the optimum water for the concrete mix results in poor quality concrete structures, which... Read More about A deep learning approach to concrete water-cement ratio prediction.

A scalable deep learning system for monitoring and forecasting pollutant concentration levels on UK highways (2022)
Journal Article
Akinosho, T. D., Oyedele, L. O., Bilal, M., Barrera-Animas, A. Y., Gbadamosi, A. Q., & Olawale, O. A. (2022). A scalable deep learning system for monitoring and forecasting pollutant concentration levels on UK highways. Ecological Informatics, 69, Article 101609. https://doi.org/10.1016/j.ecoinf.2022.101609

The construction of intercity highways by the government has resulted in a progressive increase in vehicle emissions and pollution from noise, dust, and vibrations despite its recognition of the air pollution menace. Efforts that have targeted roadsi... Read More about A scalable deep learning system for monitoring and forecasting pollutant concentration levels on UK highways.

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.

Integrated life-cycle optimisation and supply-side management for building retrofitting (2021)
Journal Article
Luo, X., & Oyedele, L. O. (2022). Integrated life-cycle optimisation and supply-side management for building retrofitting. Renewable and Sustainable Energy Reviews, 154, Article 111827. https://doi.org/10.1016/j.rser.2021.111827

Building retrofitting is a powerful approach to enhance building energy performance. The net-zero ambition urges the need to renovate building energy system in view of the life-cycle optimal, to address climate and environmental challenges. Existing... Read More about Integrated life-cycle optimisation and supply-side management for building retrofitting.

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.

Assessment and optimisation of life cycle environment, economy and energy for building retrofitting (2021)
Journal Article
Luo, X. J., & Oyedele, L. O. (2021). Assessment and optimisation of life cycle environment, economy and energy for building retrofitting. Energy for Sustainable Development, 65, 77-100. https://doi.org/10.1016/j.esd.2021.10.002

Building retrofitting plays a vital role in realising net-zero carbon ambition. Conventional retrofitting solutions are generally based upon decreasing operating energy usage or corresponding costs. However, many of these would increase the embodied... Read More about Assessment and optimisation of life cycle environment, economy and energy for building retrofitting.

Artificial intelligence in the construction industry: A review of present status, opportunities and future challenges (2021)
Journal Article
Abioye, S. O., Oyedele, L. O., Akanbi, L., Ajayi, A., Davila Delgado, J. M., Bilal, M., …Ahmed, A. (2021). Artificial intelligence in the construction industry: A review of present status, opportunities and future challenges. Journal of Building Engineering, 44, Article 103299. https://doi.org/10.1016/j.jobe.2021.103299

The growth of the construction industry is severely limited by the myriad complex challenges it faces such as cost and time overruns, health and safety, productivity and labour shortages. Also, construction industry is one the least digitized industr... Read More about Artificial intelligence in the construction industry: A review of present status, opportunities and future challenges.

Deep learning with small datasets: Using autoencoders to address limited datasets in construction management (2021)
Journal Article
Davila Delgado, M., & Oyedele, L. (2021). Deep learning with small datasets: Using autoencoders to address limited datasets in construction management. Applied Soft Computing, 112, Article 107836. https://doi.org/10.1016/j.asoc.2021.107836

Large datasets are necessary for deep learning as the performance of the algorithms used increases as the size of the dataset increases. Poor data management practices and the low level of digitisation of the construction industry represent a big hur... Read More about Deep learning with small datasets: Using autoencoders to address limited datasets in construction management.

Forecasting building energy consumption: Adaptive long-short term memory neural networks driven by genetic algorithm (2021)
Journal Article
Luo, X., & Oyedele, L. O. (2021). Forecasting building energy consumption: Adaptive long-short term memory neural networks driven by genetic algorithm. Advanced Engineering Informatics, 50, Article 101357. https://doi.org/10.1016/j.aei.2021.101357

The real-world building can be regarded as a comprehensive energy engineering system; its actual energy consumption depends on complex affecting factors, including various weather data and time signature. Accurate energy consumption forecasting and e... Read More about Forecasting building energy consumption: Adaptive long-short term memory neural networks driven by genetic algorithm.

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.

Digital Twins for the built environment: Learning from conceptual and process models in manufacturing (2021)
Journal Article
Davila Delgado, J. M., & Oyedele, L. (2021). Digital Twins for the built environment: Learning from conceptual and process models in manufacturing. Advanced Engineering Informatics, 49, Article 101332. https://doi.org/10.1016/j.aei.2021.101332

The overall aim of this paper is to contribute to a better understanding of the Digital Twin (DT) paradigm in the built environment by drawing inspiration from existing DT research in manufacturing. The DT is a Product Life Management information con... Read More about Digital Twins for the built environment: Learning from conceptual and process models in manufacturing.

Deep learning and boosted trees for injuries prediction in power infrastructure projects (2021)
Journal Article
Oyedele, A., Ajayi, A., Oyedele, L. O., Delgado, J. M. D., Akanbi, L., Akinade, O., …Bilal, M. (2021). Deep learning and boosted trees for injuries prediction in power infrastructure projects. Applied Soft Computing, 110(107587), 1 - 14. https://doi.org/10.1016/j.asoc.2021.107587

Electrical injury impacts are substantial and massive. Investments in electricity will continue to increase, leading to construction project complexities, which undoubtedly contribute to injuries and associated effects. Machine learning (ML) algorith... Read More about Deep learning and boosted trees for injuries prediction in power infrastructure projects.

IoT technologies for livestock management: A review of present status, opportunities, and future trends (2021)
Journal Article
Akhigbe, B. I., Munir, K., Akinade, O., Akanbi, L., & Oyedele, L. O. (2021). IoT technologies for livestock management: A review of present status, opportunities, and future trends. Big Data and Cognitive Computing, 5(1), Article 10. https://doi.org/10.3390/bdcc5010010

The world population currently stands at about 7 billion amidst an expected increase in 2030 from 9.4 billion to around 10 billion in 2050. This burgeoning population has continued to influence the upward demand for animal food. Moreover, the managem... Read More about IoT technologies for livestock management: A review of present status, opportunities, and future trends.

Cloud computing in construction industry: Use cases, benefits and challenges (2020)
Journal Article
Bello, S. A., Oyedele, L. O., Akinade, O. O., Bilal, M., Davila Delgado, J. M., Akanbi, L. A., …Owolabi, H. A. (2021). Cloud computing in construction industry: Use cases, benefits and challenges. Automation in Construction, 122, Article 103441. https://doi.org/10.1016/j.autcon.2020.103441

Cloud computing technologies have revolutionised several industries (such as aerospace, manufacturing, automobile, retail, etc.) for several years. Although the construction industry is well placed to also leverage these technologies for competitive... Read More about Cloud computing in construction industry: Use cases, benefits and challenges.