ConLogAI – Concept for an AI-enabled platform for construction logistics scheduling

Maximilian Gehring, Jascha Brötzmann, Uwe Rüppel

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

Abstract

Construction logistics management plays a crucial role in the successful execution of construction projects. Building Information Modeling (BIM) supports scheduling processes by providing structured project data. The integration of Artificial Intelligence (AI) further enhances the impact of BIM by enabling automation, pattern recognition, and intelligent decision-making. Additionally, digital technologies such as the Internet of Things (IoT) can support data-driven adaptations during execution. This paper introduces a concept for a BIM-based, AI-enabled construction scheduling platform designed to address critical challenges in construction logistics planning. By leveraging BIM data as a foundation, the platform incorporates AI-driven semantic enrichment to derive task relationships and dependencies, while employing advanced scheduling algorithms to generate optimized execution plans. The proposed system aims to enable dynamic, resource-constrained scheduling and facilitate real-time adaptation to disruptions. A preliminary implementation validates the feasibility of the concept and highlights its potential to improve transparency, efficiency, and responsiveness in construction logistics management.
Original languageEnglish
Title of host publicationEG-ICE 2025
Subtitle of host publicationAI-Driven Collaboration for Sustainable and Resilient Built Environments Conference Proceedings
EditorsAlejandro Moreno-Rangel, Bimal Kumar
Place of PublicationGlasgow
Number of pages10
DOIs
Publication statusPublished - 1 Jul 2025
EventEG-ICE 2025: International Workshop on Intelligent Computing in Engineering - The Technology and Innovation Centre, Glasgow, United Kingdom
Duration: 1 Jul 20253 Jul 2025
https://egice2025.co.uk/

Conference

ConferenceEG-ICE 2025: International Workshop on Intelligent Computing in Engineering
Country/TerritoryUnited Kingdom
CityGlasgow
Period1/07/253/07/25
Internet address

Keywords

  • automated scheduling
  • BIM
  • construction logistics
  • artificial intelligence

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