CORTEXA
← Browse
openalexZenodo (CERN European Organization for Nuclear Research)2026-07-23Cited by 0

EFFECT OF BUILDING INFORMATION MODELLING ON EFFECTIVE TIME MANAGEMENT OF BUILDING CONSTRUCTION DELIVERY IN ENUGU METROPOLIS

C.E Enebe, A.T Chukwuenye, Okeke FN

This study focused on the effect of building information modelling on effective time management of building construction delivery in Enugu metropolis. The specific objectives of the study is to examine the relationship between the adoption of BIM and the efficient project delivery of the Nigerian construction industry. Identify factors affecting the adoption of BIM for project delivery in the Nigeria construction industry. The survey research design was used for the study. The targeted population are 40 builders, 90 quantity surveyors, 70 Architect and 60 Engineers (Sourced from the physical planning units of the study area). Summing the total population of the respondent to be 260. The findings of the study reveals that Robotics, building information modelling and drones, have a positive relationship with effective project delivery, which conforms to the expected sign whereas artificial intelligence has negative relationship with effective project delivery which does not conforms to the expected signs. The study also reveals that Lack of awareness and understanding, High initial cost of implementations, Inadequate technical expertise, resistance to change, poor ICT infrastructure, lack of government policy and regulations, fragmentations in the construction industry, low demand from client, limited educational integration, security and data management concerns are the identified factors affecting the adoption of BIM for project delivery in the Nigerian construction industry. The study recommends that there is need for building professionals to always organize seminars, workshops and awareness campaigns in Enugu State to sensitize construction professionals (Architects, Engineers, project managers) on the time saving benefits of BIM

View free PDFSource page

Related papers

openalexZenodo (CERN European Organization for Nuclear Research)2026-07-24

Controllable Generative AI: A Technical Review of Model Parameters for Hallucination Mitigation, Fine-Tuning, and Replicable Model Construction

Prateek Dutta

Generative artificial intelligence (GenAI) systems, particularly large language models (LLMs), expose a dense and interacting set of architectural, optimization, and inference-time parameters that jointly determine factual reliability, adaptation quality, and reproducibility. Thi…

View free PDFSource page
openalexZenodo (CERN European Organization for Nuclear Research)2026-07-24

From BIM Level 2 to AI-Ready Infrastructure: The UK Digital Built Environment Challenge and the Role of Enterprise Architecture

Sergey Sinyagov

The United Kingdom has been a global leader in Building Information Modelling (BIM) adoption, establishing BIM Level 2 as the foundation for collaborative information management across the built environment. Mandated for publicly funded projects in 2016, this framework introduced…

View free PDFSource page
openalexZenodo (CERN European Organization for Nuclear Research)

Financial data source preparation and analysis as the initial stage of stochastic time series modeling by machine learning techniques

Yurchenko Yuriy, Oleksandr Zakovorotnyi

Proceedings of the Scientific Conference "The 13th International Scientific and Practical Online Conference of Young Scientists and Students ‘Contemporary Problems of Automation and Control’".The conference talk presents a structured approach to preparing and analyzing financial…

Also available via: European Organization for Nuclear Research

View free PDFSource page
openalexZenodo (CERN European Organization for Nuclear Research)2026-07-24

developing a nature-inspired design framework for self-regulating urban parks: a digital twin-based model for intelligent landscape management

Parisa Azimi, Sepideh Habibpour Mehraban

developing a nature-inspired design framework for self-regulating urban parks: a digital twin-based model for intelligent landscape management parisa azimi1, sepideh habibpour mehraban2 1- M.Sc in Enviromental Design2- M.Sc in Enviromental Design Abstract Urban parks have faced i…

View free PDFSource page
openalexZenodo (CERN European Organization for Nuclear Research)2026-07-26

Electrical resistivity tomography surveys, trained physics-informed neural network models and code for amortized ERT inversion along Route Regionale 707, Moroccan Middle Atlas

Rajae Ajana

This deposit contains the field data, synthetic training datasets, trained network weights and analysis code supporting the article "Physics-informed neural network inversion of electrical resistivity tomography data: amortized optimization with field validation in the Moroccan M…

View free PDFSource page
openalexZenodo (CERN European Organization for Nuclear Research)2026-07-24

Bayesian-Optimized Physics-Informed Neural Networks for the FitzHugh-Nagumo Model

Bogdan Miličević, N Filipovic

Physics-Informed Neural Networks (PINNs) offer a promising bridge between deep learning and biophysical modeling by embedding differential equations directly into the learning process. This paper explores an automated framework using Bayesian Optimization (BO) and PINNs in order…

View free PDFSource page