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Use of Artificial Intelligence in Construction Planning: Delay Prediction and Resource Optimization with Machine Learning
Subject area: Science,Engineering and Technology · Area of research: Engineering
Abstract
This article explores the application of Artificial Intelligence (AI), particularly machine learning (ML), in construction planning with a focus on delay prediction and resource optimization. By leveraging historical project data, real-time sensor inputs, and multimodal information, ML models can forecast potential schedule deviations and optimize the allocation of labor, equipment, and materials. AI-driven decision support systems and automated alert mechanisms enhance managerial responsiveness and improve overall project efficiency. Additionally, the integration of AI supports sustainability objectives through predictive maintenance and resource waste reduction. Despite challenges related to data quality and model interpretability, the adoption of AI technologies in construction management demonstrates significant potential to improve productivity, reduce costs, and increase project success rates.
Keywords
Machine Learning, Predictive Planning, AI In Construction, Resource Optimization, Construction Delays, Decision Support Systems, Construction Productivity
How to cite this paper
@article{1710021,
author = {Danilo Ramos Stein},
title = {Use of Artificial Intelligence in Construction Planning: Delay Prediction and Resource Optimization with Machine Learning},
journal = {Iconic Research And Engineering Journals},
year = {2022},
volume = {5},
number = {7},
pages = {592-596},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1710021.pdf},
abstract = {This article explores the application of Artificial Intelligence (AI), particularly machine learning (ML), in construction planning with a focus on delay prediction and resource optimization. By leveraging historical project data, real-time sensor inputs, and multimodal information, ML models can forecast potential schedule deviations and optimize the allocation of labor, equipment, and materials. AI-driven decision support systems and automated alert mechanisms enhance managerial responsiveness and improve overall project efficiency. Additionally, the integration of AI supports sustainability objectives through predictive maintenance and resource waste reduction. Despite challenges related to data quality and model interpretability, the adoption of AI technologies in construction management demonstrates significant potential to improve productivity, reduce costs, and increase project success rates.},
keywords = {Machine Learning, Predictive Planning, AI In Construction, Resource Optimization, Construction Delays, Decision Support Systems, Construction Productivity},
month = {January},
}