"Title: Monitoring Concrete Pouring with Knowledge Graph-Enhanced Computer Vision: A Case Study from Munich, Germany
Authors: Pfitzner, Fabian (1);
Hu, Songbo (2);
Braun, Alex (1);
Borrmann, André (1);
Fang, Yihai (2)
Affiliation: 1: Chair of Computational Modeling and Simulation, Technical University of Munich, Germany;
2: Department of Civil Engineering, Monash University, Australia
Keywords: construction monitoring, computer vision, knowledge graphs, process reasoning
Session: Data Sensing & Acquisition
Paper Link: 10.35490/EC3.2024.177
Abstract: This paper introduces a novel approach for monitoring concrete pouring. Traditional manual tracking methods are tedious, while automated solutions, such as Computer Vision (CV)-enabled methods, are challenged with occulted data and limited adaptability to diverse crane behaviour patterns. We propose a knowledge graph-enhanced CV method that combines context knowledge with object recognition. This approach analyses tower crane behaviours and their interactions with workers, truck mixers, and building elements, providing a detailed and resilient interpretation of concrete pouring progress. Preliminary findings reveal the method’s capacity to interpret incomplete data and comprehend complex site dynamics, demonstrating promising potential in a real-world scenario."
