Cloud technologies and data-driven algorithms for interferometric sensors.

The PhD project developed in these years started by studying the motivations behind Industry 4.0 and the most popular data-driven algorithms. The study was then oriented on the main success factors for the realization of a connected product continuing then for a study of the cloud in more detail. This study led me to analyze different components offered by the main providers, and to implement different solutions. The different solutions both at architectural and provider level allowed us to verify the differences between different implementations and their associated costs. The study of the cloud was then concluded with an exhaustive cost analysis that clearly highlights what are the gains or losses associated with the choice of a provider as a function of traffic exchanged. The study is then articulated on the more purely signal processing part, it is first presented the principle of operation of the interferometric sensor and then analyzes the main issues related to the signals produced by the instrument. It then analyzes the main strategies for solving the problems exposed, and the proposed solution also trying to explain how we arrived at that solution through the analysis of the main criticality of the signal. It concludes by analyzing the problems of implementation of the algorithmic part within the real sensor with limited processing capacity and the strategies undertaken to mitigate the impact of these issues on the final implementation. The analysis of the implementation is accompanied by some data about the timing with which it is possible to use the algorithm and its main limitations.