Virtual Field Service Ecosystem (VSE) using AR (Augmented Reality) collaboration with SiemensAG
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- Studentoppgaver (TN-IDE) 
With the huge advancement of technologies, our viewpoint to see, hear, observe and feel the surroundings around us is changing every single moment. Building a virtual ecosystem is an idea which needs much time and effort. The purpose of this project is building an ecosystem with AR applications combining machine learning features. In this way, users can gain access to information in a very interactive, contextualized ways which provide a deeper understanding of the physical problems around them and how to solve them easily. A smart machine learning algorithm is only possible if the data provided is concrete and huge to perform any thorough analysis. In this experiment, huge data containing different significant features of a single feed production machine from Siemens is provided where the quality of the product is depended on pressure. Analysis of that data is performed showing graphs, selecting features, validations, mathematical implementations or statistical analysis to propose a model. The significant part of the model building is predicting pressure value for advanced maintenance of the machine and accuracy of the model must be high. The predicted data, analysis of graphs and validation results is proposed to be stored on a cloud system. The AR application is supposed to show ML results. This includes showing every data that is stored in the cloud in the AR application. That way the AR and machine learning are combined in a single application which has the possibility to be extended later for bigger solutions.
Master's thesis in Computer science