Heer, Ditmer (2025) Methods to identify deviating flowsensors. Internship report thesis, Data Science and Society (DSS).
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Abstract
Vitens is the largest drinking water company of the Netherlands, providing drinking water to the provinces of Utrecht, Gelderland, Overijssel, Flevoland and Friesland. For my internship I researched several methods for the identification of deviating flowsensors in this large network of which the quality must be maintained. This involved literature research to sensor failure and calibration, the creation of synthetic data, the development of several machine learning models and the search for relevant evaluation metrics for these models. The final product consists of an advice on how to further build upon the developed methods and what other possibilities could be explored in the future. It is supported by the results of different versions of machine learning models I build and available literature and research. This internship report will cover these 3 and a half months at Vitens, including some more information about the company, my project and my development during my internship.
| Item Type: | Thesis (Internship report) |
|---|---|
| Name supervisor: | Bouman, L. |
| Date Deposited: | 14 Jan 2026 13:59 |
| Last Modified: | 14 Jan 2026 13:59 |
| URI: | https://campus-fryslan.studenttheses.ub.rug.nl/id/eprint/779 |
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