Industrial IoT Technologies and Applications. 4th EAI International Conference, Industrial IoT 2020, Virtual Event, December 11, 2020, Proceedings

Research Article

Towards Construction Progress Estimation Based on Images Captured on Site

  • @INPROCEEDINGS{10.1007/978-3-030-71061-3_9,
        author={Peter Hevesi and Ramprasad Chinnaswamy Devaraj and Matthias Tsch\o{}pe and Oliver Petter and Janis Nikolaus Elfert and Vitor Fortes Rey and Marco Hirsch and Paul Lukowicz},
        title={Towards Construction Progress Estimation Based on Images Captured on Site},
        proceedings={Industrial IoT Technologies and Applications. 4th EAI International Conference, Industrial IoT 2020, Virtual Event, December 11, 2020, Proceedings},
        proceedings_a={INDUSTRIALIOT},
        year={2021},
        month={7},
        keywords={Construction progress estimation Neural networks Computer vision},
        doi={10.1007/978-3-030-71061-3_9}
    }
    
  • Peter Hevesi
    Ramprasad Chinnaswamy Devaraj
    Matthias Tschöpe
    Oliver Petter
    Janis Nikolaus Elfert
    Vitor Fortes Rey
    Marco Hirsch
    Paul Lukowicz
    Year: 2021
    Towards Construction Progress Estimation Based on Images Captured on Site
    INDUSTRIALIOT
    Springer
    DOI: 10.1007/978-3-030-71061-3_9
Peter Hevesi1, Ramprasad Chinnaswamy Devaraj2, Matthias Tschöpe1, Oliver Petter1, Janis Nikolaus Elfert1, Vitor Fortes Rey1, Marco Hirsch1, Paul Lukowicz1
  • 1: German Research Center for Artificial Intelligence (DFKI)
  • 2: University of Kaiserslautern

Abstract

State of the art internet of things (IoT) and mobile monitoring systems promise to help gathering real time progress information from construction sites. However, on remote sites the adaptation of those technologies is frequently difficult due to a lack of infrastructure and often harsh and dynamic environments. On the other hand, visual inspection by experts usually allows a quick assessment of a project’s state. In some fields, drones are already commonly used to capture aerial footage for the purpose of state estimation by domain experts.