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Rechnerarchitektur - Arbeitsgruppe Bernd Becker
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Beteiligte Mitarbeiter

Professur für Rechnerarchitektur
Benjamin Voelker, M.Sc. Entwickler / Kontakt


The growing request for eco-feedback and smart living concepts accelerated the development of Non-Intrusive Load Monitoring (NILM) algorithms during the last decade. Comparing and evaluating these algorithms still remains challenging due to the absence of a common benchmark datasets, and missing best practises for their application. Despite the fact that multiple datasets were recorded for the purpose of comparing NILM algorithms, many researchers still have to record their own dataset in order to meet the requirements of their specific application. Adding ground truth labels to these datasets is a cumbersome and time consuming process as it requires an expert to visually inspect all the data manually. Therefore, we propose the Annoticity inspection and labeling tool which simplifies the process of visualizing and labeling of electricity data.

It is realized as a web application and provides direct access to various publicly available electricity datasets.

Users can add labels manually, review automatically generated labels, or modify existing label sets.

The labels can be downloaded in various file formats including an option to store the labels with the original data.

Preliminary results indicate that the effort of generating event labels is reduced by 80% using our tool.

The tool is hosted at:

Benjamin Voelker, M.Sc.
Benjamin Völker, Marc Pfeifer, Philipp M. Scholl, and Bernd Becker. FIRED: A Fully-labeled hIgh-fRequency Electricity Disaggregation Dataset. 7th ACM International Conference on Systems for Energy Efficient Buildings (BuildSys), 2020

Benjamin Völker, Marc Pfeifer, Philipp M. Scholl, and Bernd Becker. Annoticity: A Smart Annotation Tool and Data Browser for Electricity Datasets. 5th Workshop on Non-Intrusive Load Monitoring (NILM 2020 @ BuildSys)