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Outputs (54)

Can we revitalize interventional healthcare with AI-XR surgical metaverses? (2023)
Conference Proceeding
Qayyum, A., Bilal, M., Hadi, M., Capik, P., Caputo, M., Vohra, H., …Qadir, J. (2023). Can we revitalize interventional healthcare with AI-XR surgical metaverses?. In IEEE International Conference on Metaverse Computing, Networking and Applications (IEEE MetaCom 2023) (496-503). https://doi.org/10.1109/MetaCom57706.2023.00091

Recent advancements in technology, particularly in machine learning (ML), deep learning (DL), and the metaverse, offer great potential for revolutionizing surgical science. The combination of artificial intelligence and extended reality (AI-XR) techn... Read More about Can we revitalize interventional healthcare with AI-XR surgical metaverses?.

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.

SegCrop: Segmentation-based dynamic cropping of endoscopic videos to address label leakage in surgical tool detection (2023)
Presentation / Conference
Qayyum, A., Bilal, M., Qadir, J., Caputo, M., Vohra, H., Akinosho, T., …Abioye, S. (2023, April). SegCrop: Segmentation-based dynamic cropping of endoscopic videos to address label leakage in surgical tool detection. Paper presented at IEEE International Symposium on Biomedical Imaging (ISBI), 2023, Colombia

In recent times, surgical data science has emerged as an important research discipline in interventional healthcare. There are many potential applications for analysing endoscopic surgical videos using machine learning (ML) techniques such as surgica... Read More about SegCrop: Segmentation-based dynamic cropping of endoscopic videos to address label leakage in surgical tool detection.

Privacy-preserving artificial intelligence in healthcare: Techniques and applications (2023)
Journal Article
Khalid, N., Qayyum, A., Bilal, M., Al-Fuqaha, A., & Qadir, J. (2023). Privacy-preserving artificial intelligence in healthcare: Techniques and applications. Computers in Biology and Medicine, 158, Article 106848. https://doi.org/10.1016/j.compbiomed.2023.106848

There has been an increasing interest in translating artificial intelligence (AI) research into clinically-validated applications to improve the performance, capacity, and efficacy of healthcare services. Despite substantial research worldwide, very... Read More about Privacy-preserving artificial intelligence in healthcare: Techniques and applications.

A deep learning approach for context-aware citation recommendation using rhetorical zone classification and similarity to overcome cold-start problem (2022)
Journal Article
Abbas, M., Ajayi, S., Bilal, M., Oyegoke, A., Pasha, M., & Tauqeer Ali, H. (2024). A deep learning approach for context-aware citation recommendation using rhetorical zone classification and similarity to overcome cold-start problem. Journal of Ambient Intelligence and Humanized Computing, 15, 419–433. https://doi.org/10.1007/s12652-022-03899-6

In the recent decade, the citation recommendation has emerged as an important research topic due to its need for the huge size of published scientific work. Among other citation recommendation techniques, the widely used content-based filtering (CBF)... Read More about A deep learning approach for context-aware citation recommendation using rhetorical zone classification and similarity to overcome cold-start problem.

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.

Integrating single-shot fast gradient sign method (FGSM) with classical image processing techniques for generating adversarial attacks on deep learning classifiers (2022)
Conference Proceeding
Hassan, M., Younis, S., Rasheed, A., & Bilal, M. (2022). Integrating single-shot fast gradient sign method (FGSM) with classical image processing techniques for generating adversarial attacks on deep learning classifiers. In Proceedings Volume 12084, Fourteenth International Conference on Machine Vision (ICMV 2021). https://doi.org/10.1117/12.2623585

Deep learning architectures have emerged as powerful function approximators in a broad spectrum of complex representation learning tasks, such as, computer vision, natural language processing and collaborative filtering. These architectures bear a hi... Read More about Integrating single-shot fast gradient sign method (FGSM) with classical image processing techniques for generating adversarial attacks on deep learning classifiers.

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.

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.

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.

Life cycle assessment approach for renewable multi-energy system: A comprehensive analysis (2020)
Journal Article
Luo, X., Oyedele, L. O., Owolabi, H. A., Bilal, M., Ajayi, A. O., & Akinade, O. O. (2020). Life cycle assessment approach for renewable multi-energy system: A comprehensive analysis. Energy Conversion and Management, 224, Article 113354. https://doi.org/10.1016/j.enconman.2020.113354

In response to the gradual degradation of natural sources, there is a growing interest in adopting renewable resources for various building energy supply. In this study, a comprehensive life cycle assessment approach is proposed for a renewable multi... Read More about Life cycle assessment approach for renewable multi-energy system: A comprehensive analysis.

Secure and robust machine learning for healthcare: A survey (2020)
Journal Article
Qayyum, A., Qadir, J., Bilal, M., & Al Fuqaha, A. (2020). Secure and robust machine learning for healthcare: A survey. IEEE Reviews in Biomedical Engineering, 14, 156-180. https://doi.org/10.1109/rbme.2020.3013489

Recent years have witnessed widespread adoption of machine learning (ML)/deep learning (DL) techniques due to their superior performance for a variety of healthcare applications ranging from the prediction of cardiac arrest from one-dimensional heart... Read More about Secure and robust machine learning for healthcare: A survey.

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 with deep learning for benchmarking profitability performance in project tendering (2020)
Journal Article
Bilal, M., & Oyedele, L. O. (2020). Big Data with deep learning for benchmarking profitability performance in project tendering. Expert Systems with Applications, 147, Article 113194. https://doi.org/10.1016/j.eswa.2020.113194

© 2020 A reliable benchmarking system is crucial for the contractors to evaluate the profitability performance of project tenders. Existing benchmarks are ineffective in the tender evaluation task for three reasons. Firstly, these benchmarks are most... Read More about Big Data with deep learning for benchmarking profitability performance in project tendering.

Guidelines for applied machine learning in construction industry—A case of profit margins estimation (2019)
Journal Article
Bilal, M., & Oyedele, L. (2020). Guidelines for applied machine learning in construction industry—A case of profit margins estimation. Advanced Engineering Informatics, 43, 101013. https://doi.org/10.1016/j.aei.2019.101013

© 2019 Elsevier Ltd The progress in the field of Machine Learning (ML) has enabled the automation of tasks that were considered impossible to program until recently. These advancements today have incited firms to seek intelligent solutions as part of... Read More about Guidelines for applied machine learning in construction industry—A case of profit margins estimation.

Risk mitigation in PFI/PPP project finance: A framework model for financiers’ bankability criteria (2019)
Journal Article
Owolabi, H., Oyedele, L., Alaka, H., Ajayi, S., Bilal, M., & Akinade, O. (2020). Risk mitigation in PFI/PPP project finance: A framework model for financiers’ bankability criteria. Built Environment Project and Asset Management, 10(1), 28-49. https://doi.org/10.1108/BEPAM-09-2018-0120

Purpose: Earlier studies on risk evaluation in private finance initiative and public private partnerships (PFI/PPP) projects have focussed more on quantitative approaches despite increasing call for contextual understanding of the bankability of risk... Read More about Risk mitigation in PFI/PPP project finance: A framework model for financiers’ bankability criteria.

Design for deconstruction using a circular economy approach: Barriers and strategies for improvement (2019)
Journal Article
Akinade, O., Oyedele, L., Oyedele, A., Davila Delgado, J. M., Bilal, M., Akanbi, L., …Owolabi, H. (2020). Design for deconstruction using a circular economy approach: Barriers and strategies for improvement. Production Planning and Control, 31(10), 829-840. https://doi.org/10.1080/09537287.2019.1695006

This study explores the current practices of Design for Deconstruction (DfD) as a strategy for achieving circular economy. Keeping in view the opportunities accruable from DfD, a review of the literature was carried out and six focus group interviews... Read More about Design for deconstruction using a circular economy approach: Barriers and strategies for improvement.

Deep learning models for health and safety risk prediction in power infrastructure projects (2019)
Journal Article
Ajayi, A., Oyedele, L., Owolabi, H., Akinade, O., Bilal, M., Davila Delgado, J. M., & Akanbi, L. (2020). Deep learning models for health and safety risk prediction in power infrastructure projects. Risk Analysis, 40(10), 2019-2039. https://doi.org/10.1111/risa.13425

Inappropriate management of Health and safety (H&S) risk in power infrastructure projects can result in occupational accidents and equipment damage. Accidents at work have detrimental effects on workers, company, and the general public. Despite the a... Read More about Deep learning models for health and safety risk prediction in power infrastructure projects.

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.

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.

Investigating profitability performance of construction projects using big data: A project analytics approach (2019)
Journal Article
Bilal, M., Oyedele, L. O., Kusimo, H. O., Owolabi, H. A., Akanbi, L. A., Ajayi, A. O., …Davila Delgado, J. M. (2019). Investigating profitability performance of construction projects using big data: A project analytics approach. Journal of Building Engineering, 26, Article 100850. https://doi.org/10.1016/j.jobe.2019.100850

© 2019 The Authors The construction industry generates different types of data from the project inception stage to project delivery. This data comes in various forms and formats which surpass the data management, integration and analysis capabilities... Read More about Investigating profitability performance of construction projects using big data: A project analytics approach.

Stimulating the attractiveness of PFI/PPPs using public sector guarantees (2019)
Journal Article
Owolabi, H., Oyedele, L., Alaka, H., Bilal, M., Ajayi, S., Akinade, O., & Agboola, A. (2019). Stimulating the attractiveness of PFI/PPPs using public sector guarantees. World Journal of Entrepreneurship, Management and Sustainable Development, 15(3), 239-258. https://doi.org/10.1108/WJEMSD-05-2018-0055

Purpose: Although the UK Guarantee Scheme for Infrastructures (UKGSI) was introduced in 2012 to address the huge financing gap for critical infrastructures, PFI sponsors have so far guaranteed only few projects. Many stakeholders in the project finan... Read More about Stimulating the attractiveness of PFI/PPPs using public sector guarantees.

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.

Design optimisation using convex programming: Towards waste-efficient building designs (2019)
Journal Article
Bilal, M., Oyedele, L. O., Akinade, O. O., Delgado, J. M. D., Akanbi, L. A., Ajayi, A. O., & Younis, M. S. (2019). Design optimisation using convex programming: Towards waste-efficient building designs. Journal of Building Engineering, 23, 231-240. https://doi.org/10.1016/j.jobe.2019.01.022

© 2019 The Authors A non-modular building layout is amongst the leading sources of offcut waste, resulting from a substantial amount of onsite cutting and fitting of bricks, blocks, plasterboard, and tiles. The field of design for dimensional coordin... Read More about Design optimisation using convex programming: Towards waste-efficient building designs.

Predicting completion risk in PPP projects using big data analytics (2018)
Journal Article
Owolabi, H., Bilal, M., Oyedele, L., Alaka, H. A., Ajayi, S. O., & Akinade, O. (2020). Predicting completion risk in PPP projects using big data analytics. IEEE Transactions on Engineering Management, 67(2), 430-453. https://doi.org/10.1109/TEM.2018.2876321

Accurate prediction of potential delays in public private partnerships (PPP) projects could provide valuable information relevant for planning and mitigating completion risk in future PPP projects. However, existing techniques for evaluating completi... Read More about Predicting completion risk in PPP projects using big data analytics.

Big data platform for health and safety accident prediction (2018)
Journal Article
Ajayi, A., Oyedele, L., Davila Delgado, J. M., Akanbi, L., Bilal, M., Akinade, O., & Olawale, O. (2019). Big data platform for health and safety accident prediction. World Journal of Science, Technology and Sustainable Development, 16(1), 2-21. https://doi.org/10.1108/WJSTSD-05-2018-0042

Purpose – The purpose of this paper is to highlight the use of the big data technologies for health and safety risks analytics in the power infrastructure domain with large data sets of health and safety risks, which are usually sparse and noisy. Des... Read More about Big data platform for health and safety accident prediction.

Reusability analytics tool for end-of-life assessment of building materials in a circular economy (2018)
Journal Article
Akanbi, L., Oyedele, L., Davila Delgado, J. M., Bilal, M., Akinade, O., Ajayi, A., & Mohammed-Yakub, N. (2019). Reusability analytics tool for end-of-life assessment of building materials in a circular economy. World Journal of Science, Technology and Sustainable Development, 16(1), 40-55. https://doi.org/10.1108/WJSTSD-05-2018-0041

Purpose – In a circular economy, the goal is to keep materials values in the economy for as long as possible. For the construction industry to support the goal of the circular economy, there is the need for materials reuse. However, there is little o... Read More about Reusability analytics tool for end-of-life assessment of building materials in a circular economy.

Public private partnerships (PPP) in the developing world: Mitigating financiers’ risks (2018)
Journal Article
Owolabi, H. A., Oyedele, L., Alaka, H., Ebohon, O. J., Ajayi, S., Akinade, O., …Olawale, O. (2019). Public private partnerships (PPP) in the developing world: Mitigating financiers’ risks. World Journal of Science, Technology and Sustainable Development, 16(3), 121-141. https://doi.org/10.1108/WJSTSD-05-2018-0043

Purpose – A major challenge for foreign lenders in financing public private partnerships (PPP) infrastructure projects in an emerging market (EM) is the bankability of country-related risks. Despite existing studies on country risks in international... Read More about Public private partnerships (PPP) in the developing world: Mitigating financiers’ risks.

A Big Data analytics approach for construction firms failure prediction models (2018)
Journal Article
Alaka, H., Oyedele, L., Owolabi, H., Akinade, O., Bilal, M., & Ajayi, S. (2019). A Big Data analytics approach for construction firms failure prediction models. IEEE Transactions on Engineering Management, 66(4), 689-698. https://doi.org/10.1109/TEM.2018.2856376

Using 693,000 datacells from 33,000 sample construction firms that operated or failed between 2008 and 2017, failure prediction models were developed using artificial neural network (ANN), support vector machine (SVM), multiple discriminant analysis... Read More about A Big Data analytics approach for construction firms failure prediction models.

Designing out construction waste using BIM technology: Stakeholders’ expectations for industry deployment (2018)
Journal Article
Akinade, O., Oyedele, L., Ajayi, S., Bilal, M., Alaka, H. A., Owolabi, H., & Arawomo, O. (2018). Designing out construction waste using BIM technology: Stakeholders’ expectations for industry deployment. Journal of Cleaner Production, 180, 375-385. https://doi.org/10.1016/j.jclepro.2018.01.022

© 2018 The Authors The need to use Building Information Modelling (BIM) for Construction and Demolition Waste (CDW) minimisation is well documented but most of the existing CDW management tools still lack BIM functionality. This study therefore asses... Read More about Designing out construction waste using BIM technology: Stakeholders’ expectations for industry deployment.

A framework for big data analytics approach to failure prediction of construction firms (2018)
Journal Article
Alaka, H. A., Oyedele, L. O., Owolabi, H. A., Bilal, M., Ajayi, S. O., & Akinade, O. O. (2020). A framework for big data analytics approach to failure prediction of construction firms. Applied Computing and Informatics, 16(1/2), 207-222. https://doi.org/10.1016/j.aci.2018.04.003

This study explored use of big data analytics (BDA) to analyse data of a large number of construction firms to develop a construction business failure prediction model (CB-FPM). Careful analysis of literature revealed financial ratios as the best for... Read More about A framework for big data analytics approach to failure prediction of construction firms.

Salvaging building materials in a circular economy: A BIM-based whole-life performance estimator (2017)
Journal Article
Akanbi, L. A., Oyedele, L., Akinade, O., Ajayi, A. O., Davila Delgado, M., Bilal, M., & Bello, S. A. (2018). Salvaging building materials in a circular economy: A BIM-based whole-life performance estimator. Resources, Conservation and Recycling, 129, 175-186. https://doi.org/10.1016/j.resconrec.2017.10.026

© 2017 The Author(s) The aim of this study is to develop a BIM-based Whole-life Performance Estimator (BWPE) for appraising the salvage performance of structural components of buildings right from the design stage. A review of the extant literature w... Read More about Salvaging building materials in a circular economy: A BIM-based whole-life performance estimator.

Systematic review of bankruptcy prediction models: Towards a framework for tool selection (2017)
Journal Article
Alaka, H. A., Oyedele, L., Owolabi, H. A., Kumar, V., Ajayi, S. O., Akinade, O., & Bilal, M. (2018). Systematic review of bankruptcy prediction models: Towards a framework for tool selection. Expert Systems with Applications, 94, 164-184. https://doi.org/10.1016/j.eswa.2017.10.040

© 2017 Elsevier Ltd The bankruptcy prediction research domain continues to evolve with many new different predictive models developed using various tools. Yet many of the tools are used with the wrong data conditions or for the wrong situation. Using... Read More about Systematic review of bankruptcy prediction models: Towards a framework for tool selection.

The application of web of data technologies in building materials information modelling for construction waste analytics (2017)
Journal Article
Bilal, M., Oyedele, L. O., Munir, K., Ajayi, S. O., Akinade, O. O., Owolabi, H. A., & Alaka, H. A. (2017). The application of web of data technologies in building materials information modelling for construction waste analytics. Sustainable Materials and Technologies, 11, 28-37. https://doi.org/10.1016/j.susmat.2016.12.004

© 2017 Elsevier B.V. Predicting and designing out construction waste in real time is complex during building waste analysis (BWA) since it involves a large number of analyses for investigating multiple waste-efficient design strategies. These analyse... Read More about The application of web of data technologies in building materials information modelling for construction waste analytics.

Attributes of design for construction waste minimization: A case study of waste-to-energy project (2017)
Journal Article
Ajayi, S. O., Oyedele, L. O., Akinade, O. O., Bilal, M., Alaka, H. A., Owolabi, H. A., & Kadiri, K. O. (2017). Attributes of design for construction waste minimization: A case study of waste-to-energy project. Renewable and Sustainable Energy Reviews, 73, 1333-1341. https://doi.org/10.1016/j.rser.2017.01.084

© 2017 Elsevier Ltd Despite the consensus that waste efficient design is important for reducing waste generated by construction and demolition activities, design strategies for actual waste mitigation remain unclear. In addition, decisive roles requi... Read More about Attributes of design for construction waste minimization: A case study of waste-to-energy project.

BIM-based deconstruction tool: Towards essential functionalities (2017)
Journal Article
Akinade, O. O., Oyedele, L. O., Omoteso, K., Ajayi, S. O., Bilal, M., Owolabi, H. A., …Looney, J. H. (2017). BIM-based deconstruction tool: Towards essential functionalities. International Journal for Sustainable Built Environment, 6(1), 260-271. https://doi.org/10.1016/j.ijsbe.2017.01.002

© 2017 The Gulf Organisation for Research and Development This study discusses the future directions of effective Design for Deconstruction (DfD) using BIM-based approach to design coordination. After a review of extant literatures on existing DfD pr... Read More about BIM-based deconstruction tool: Towards essential functionalities.

Optimising material procurement for construction waste minimization: An exploration of success factors (2017)
Journal Article
Ajayi, S. O., Oyedele, L. O., Akinade, O. O., Bilal, M., Alaka, H. A., & Owolabi, H. A. (2017). Optimising material procurement for construction waste minimization: An exploration of success factors. Sustainable Materials and Technologies, 11, 38-46. https://doi.org/10.1016/j.susmat.2017.01.001

© 2017 Elsevier B.V. Although construction waste occurs during the actual construction activities, there is an understanding that it is caused by activities and actions at design, materials procurement and construction stages of project delivery proc... Read More about Optimising material procurement for construction waste minimization: An exploration of success factors.

Insolvency of small civil engineering firms: Critical strategic factors (2016)
Journal Article
Alaka, H. A., Oyedele, L. O., Owolabi, H. A., Bilal, M., Ajayi, S. O., & Akinade, O. O. (2017). Insolvency of small civil engineering firms: Critical strategic factors. Journal of Professional Issues in Engineering Education and Practice, 143(3), 04016026. https://doi.org/10.1061/%28ASCE%29EI.1943-5541.0000321

© 2016 American Society of Civil Engineers. Construction industry insolvency studies have failed to stem the industry's high insolvency tide because many focus on big civil engineering firms (CEF) when over 90% of firms in the industry are small or m... Read More about Insolvency of small civil engineering firms: Critical strategic factors.

Critical management practices influencing on-site waste minimization in construction projects (2016)
Journal Article
Ajayi, S. O., Oyedele, L. O., Bilal, M., Akinade, O. O., Alaka, H. A., & Owolabi, H. A. (2017). Critical management practices influencing on-site waste minimization in construction projects. Waste Management, 59, 330-339. https://doi.org/10.1016/j.wasman.2016.10.040

© 2016 Elsevier Ltd As a result of increasing recognition of effective site management as the strategic approach for achieving the required performance in construction projects, this study seeks to identify the key site management practices that are... Read More about Critical management practices influencing on-site waste minimization in construction projects.

Design for Deconstruction (DfD): Critical success factors for diverting end-of-life waste from landfills (2016)
Journal Article
Akinade, O. O., Oyedele, L. O., Ajayi, S. O., Bilal, M., Alaka, H. A., Owolabi, H. A., …Kadiri, K. O. (2017). Design for Deconstruction (DfD): Critical success factors for diverting end-of-life waste from landfills. Waste Management, 60, 3-13. https://doi.org/10.1016/j.wasman.2016.08.017

© 2016 Elsevier Ltd The aim of this paper is to identify Critical Success Factors (CSF) needed for effective material recovery through Design for Deconstruction (DfD). The research approach employed in this paper is based on a sequential exploratory... Read More about Design for Deconstruction (DfD): Critical success factors for diverting end-of-life waste from landfills.

Methodological approach of construction business failure prediction studies: a review (2016)
Journal Article
Alaka, H. A., Oyedele, L. O., Owolabi, H. A., Ajayi, S. O., Bilal, M., & Akinade, O. O. (2016). Methodological approach of construction business failure prediction studies: a review. Construction Management and Economics, 34(11), 808-842. https://doi.org/10.1080/01446193.2016.1219037

© 2016 Informa UK Limited, trading as Taylor & Francis Group. Performance of bankruptcy prediction models (BPM), which partly depends on the methodological approach used to develop it, has virtually stagnated over the years. The methodological posi... Read More about Methodological approach of construction business failure prediction studies: a review.

Competency-based measures for designing out construction waste: Task and contextual attributes (2016)
Journal Article
Ajayi, S. O., Oyedele, L. O., Kadiri, K. O., Akinade, O. O., Bilal, M., Owolabi, H. A., & Alaka, H. A. (2016). Competency-based measures for designing out construction waste: Task and contextual attributes. Engineering, Construction and Architectural Management, 23(4), 464-490. https://doi.org/10.1108/ECAM-06-2015-0095

© Emerald Group Publishing Limited. Purpose - Competency-based measure is increasingly evident as an effective approach to tailoring training and development for organisational change and development. With design stage widely reckoned as being decisi... Read More about Competency-based measures for designing out construction waste: Task and contextual attributes.

Critical factors for insolvency prediction: Towards a theoretical model for the construction industry (2016)
Journal Article
Alaka, H. A., Oyedele, L. O., Owolabi, H. A., Oyedele, A. A., Akinade, O. O., Bilal, M., & Ajayi, S. O. (2017). Critical factors for insolvency prediction: Towards a theoretical model for the construction industry. International Journal of Construction Management, 17(1), 25-49. https://doi.org/10.1080/15623599.2016.1166546

© 2016 Informa UK Limited, trading as Taylor & Francis Group. Many construction industry insolvency prediction model (CI-IPM) studies have arbitrarily employed or simply adopted from previous studies different insolvency factors, without justificat... Read More about Critical factors for insolvency prediction: Towards a theoretical model for the construction industry.

Big data architecture for construction waste analytics (CWA): A conceptual framework (2016)
Journal Article
Bilal, M., Oyedele, L. O., Akinade, O. O., Ajayi, S. O., Alaka, H. A., Owolabi, H. A., …Bello, S. A. (2016). Big data architecture for construction waste analytics (CWA): A conceptual framework. Journal of Building Engineering, 6, 144-156. https://doi.org/10.1016/j.jobe.2016.03.002

© 2016 Elsevier Ltd. All rights reserved. In recent times, construction industry is enduring pressure to take drastic steps to minimise waste. Waste intelligence advocates retrospective measures to manage waste after it is produced. Existing waste in... Read More about Big data architecture for construction waste analytics (CWA): A conceptual framework.

Reducing waste to landfill: A need for cultural change in the UK construction industry (2016)
Journal Article
Kadiri, K. O., Alaka, H. A., Ajayi, S. O., Oyedele, L., Akinade, O., Bilal, M., & Owolabi, H. (2016). Reducing waste to landfill: A need for cultural change in the UK construction industry. Journal of Building Engineering, 5, 185-193. https://doi.org/10.1016/j.jobe.2015.12.007

© 2015 Elsevier Ltd. All rights reserved. Owing to its contribution of largest portion of landfill wastes and consumption of about half of mineral resources excavated from nature, construction industry has been pressed to improve its sustainability.... Read More about Reducing waste to landfill: A need for cultural change in the UK construction industry.

Evaluation criteria for construction waste management tools: Towards a holistic BIM framework (2016)
Journal Article
Ajayi, S. O., Akinade, O., Oyedele, L., Munir, K., Bilal, M., Owolabi, H. A., …Bello, S. A. (2016). Evaluation criteria for construction waste management tools: Towards a holistic BIM framework. International Journal of Sustainable Building Technology and Urban Development, 7(1), 3-21. https://doi.org/10.1080/2093761X.2016.1152203

© 2016 Informa UK Limited, trading as Taylor & Francis Group. This study identifies evaluation criteria with the goal of appraising the performance of existing construction waste management tools and employing the results in the development of a ho... Read More about Evaluation criteria for construction waste management tools: Towards a holistic BIM framework.

Waste minimisation through deconstruction: A BIM based Deconstructability Assessment Score (BIM-DAS) (2015)
Journal Article
Akinade, O. O., Oyedele, L. O., Bilal, M., Ajayi, S. O., Owolabi, H. A., Alaka, H. A., & Bello, S. A. (2015). Waste minimisation through deconstruction: A BIM based Deconstructability Assessment Score (BIM-DAS). Resources, Conservation and Recycling, 105(Part A), 167-176. https://doi.org/10.1016/j.resconrec.2015.10.018

© 2015 Elsevier B.V. The overall aim of this study is to develop a Building Information Modelling based Deconstructability Assessment Score (BIM-DAS) for determining the extent to which a building could be deconstructed right from the design stage. T... Read More about Waste minimisation through deconstruction: A BIM based Deconstructability Assessment Score (BIM-DAS).

Analysis of critical features and evaluation of BIM software: towards a plug-in for construction waste minimization using big data (2015)
Journal Article
Bilal, M., Oyedele, L. O., Qadir, J., Munir, K., Akinade, O. O., Ajayi, S. O., …Owolabi, H. A. (2015). Analysis of critical features and evaluation of BIM software: towards a plug-in for construction waste minimization using big data. International Journal of Sustainable Building Technology and Urban Development, 6(4), 211-228. https://doi.org/10.1080/2093761X.2015.1116415

© 2016 Taylor & Francis. The overall aim of this study is to investigate the potential of Building Information Modelling (BIM) for construction waste minimization. We evaluated the leading BIM design software products and concluded that none of the... Read More about Analysis of critical features and evaluation of BIM software: towards a plug-in for construction waste minimization using big data.

Waste effectiveness of the construction industry: Understanding the impediments and requisites for improvements (2015)
Journal Article
Ajayi, S. O., Oyedele, L. O., Bilal, M., Akinade, O. O., Alaka, H. A., Owolabi, H., & Kadiri, K. O. (2015). Waste effectiveness of the construction industry: Understanding the impediments and requisites for improvements. Resources, Conservation and Recycling, 102, 101-112. https://doi.org/10.1016/j.resconrec.2015.06.001

© 2015 Elsevier B.V. All rights reserved. Construction industry contributes a large portion of waste to landfill, which in turns results in environmental pollution and CO2 emission. Despite the adoption of several waste management strategies, waste r... Read More about Waste effectiveness of the construction industry: Understanding the impediments and requisites for improvements.