
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.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 3 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
