| id |
ecaade2023_239 |
| authors |
Tamke, Martin, Akbari, Shahriar, Chiujdea, Ruxandra, Nicholas, Paul and Ramsgaard Thomsen, Mette |
| year |
2023 |
| title |
A Computer Vision-Based Long-term Monitoring Framework for Biobased Materials |
| source |
Dokonal, W, Hirschberg, U and Wurzer, G (eds.), Digital Design Reconsidered - Proceedings of the 41st Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2023) - Volume 1, Graz, 20-22 September 2023, pp. 459–468 |
| doi |
https://doi.org/10.52842/conf.ecaade.2023.1.459
|
| summary |
In this paper, we describe an automated remote monitoring system to uncover the impact of environmental phenomena on 3D printed bio-polymers behaviour and lifespan. The novel fully automated in-service framework allows for long-term monitoring with a wide range of wired and optical sensors and to correlate and analyse the gathered data. A focus is set on non-invasive measurements with Computer Vision technology. Here we introduce a computational image pipeline that allows for automated analysis and feedback on monitored bio-composite samples and assemblies. The framework is easily deployable, cloud-based, and accessible remotely. We evaluate the function and reliability of the framework in two design cases indoors and outdoors and gather insight for future practice with bio-based materials on both design and in-service levels. |
| keywords |
Automated Monitoring, 3D printing, Biopolymer, Material Behaviour, Weathering |
| series |
eCAADe |
| email |
|
| full text |
 file.pdf (2,595,931 bytes) |
| references |
Content-type: text/plain
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| last changed |
2023/12/10 10:49 |
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