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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.

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 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.