Three-dimensional thermography is a recent technique—with various fields of application—that consists of combining thermography with 3D spatial data in order to obtain 3D thermograms, high information objects that allow one to overcome some limitations of 2D thermograms, to enhance the thermal monitoring and the detection of abnormalities. In this paper we present an integration methodology that can be applied to merge data acquired from a generic thermal camera and a generic laser scanner, and has the peculiarity of keeping the two devices completely decoupled and independent, so that thermal and geometrical data can be acquired at different times and no rigid link is needed between the two devices. In this way, the stand-alone capability of each device is not affected, and the data fusion is applied only when necessary. In the second part, the real effectiveness of our approach is tested on a 3D-printed object properly designed. Furthermore, one example of an application of our methodology in the cultural heritage field is presented, with an eye to preservation and restoration: the integration is applied to a marble statue called Madonna with the Child, a fine work of the Florentine sculptor Agostino di Duccio (1418–1481). The results suggest that the method can be successfully applicable to a large set of scenarios. However, additional tests are needed to improve the robustness.

No abstract

No abstract

Automation has been introduced more and more into the role of air traffic control (ATC). As with many other areas of human activity, automation has the objective of reducing the complexity of the task so that performance is optimised and safer. However, automation can also have negative effects on cognitive processing and the performance of the controllers. In this paper, we present the progress made at AUTOPACE, a European project in which research is carried out to discover what these negative effects are and to propose measures to mitigate them. The fundamental proposal of the project is to analyse, predict, and mitigate these negative effects by assessing the complexity of ATC in relation to the mental workload experienced by the controller. Hence, a highly complex situation will be one with a high mental workload and a low complex situation will be one in which the mental workload is low.