Team NoDig - Decision Support for Sustainable Worksites

Authors

  • Lars Martin Hodne Norconsult Digital
  • Ole-Magnus Høiback Norconsult Digital
  • Mats Stensrud Skui Norconsult Digital
  • Øystein Stavnes Sletta Norconsult Digital
  • Andreas Thyholt Henriksen Norconsult Digital

DOI:

https://doi.org/10.5617/nmi.10536

Keywords:

RoadAI, machine learning, LightGBM, agglomerative clustering, automated decision support

Abstract

RoadAI: Reducing emissions in road construction is a competition hosted by the Norwegian Artificial Intelligence Research Consortium (NORA) in collaboration with Skanska, Sintef, and other partners. Data from a Skanska construction site has been given to all participants. This article describes an accurate automatic load and dump cycle detector and a daily report generator that can provide real-time insight into mass movement, idle machines, and machine-specific statistics. The transparency, deployment, and further development of the presented solutions are discussed.

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Published

2023-12-21

Issue

Vol. 3 No. 3 (2023): RoadAI: Reducing Emissions in Road Construction

Section

NMI Challenge

License

Copyright (c) 2023 Nordic Machine Intelligence

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.