@inproceedings{6bb3fb6c9e5a49c3950cbf531fe1c4dc,
title = "Framework for process discovery from sensor data",
abstract = "Process mining can give valuable insights into how real-life activities are performed when extracting meaningful activities instances from raw sensor events. However, in many cases, the event data generated during the execution of a process is at a much lower level of abstraction, and, in some cases, even continuous, e.g., sensor data. This paper presents a framework to discover activities and process models from event location sensor data. The framework is flexible enough to be applied to any data set from raw sensor data.",
keywords = "Event Abstraction, Framework, Process Mining, Raw Sensor Data",
author = "Agnes Koschmider and Dominik Janssen and Felix Mannhardt",
year = "2020",
language = "English",
series = "CEUR Workshop Proceedings",
publisher = "CEUR-WS.org",
pages = "32--38",
editor = "Agnes Koschmider and Judith Michael and Bernhard Thalheim",
booktitle = "EMISA 2020 : Enterprise Modeling and Information Systems Architectures 2020",
note = "10th International Workshop on Enterprise Modeling and Information Systems Architectures, EMISA 2020 ; Conference date: 14-05-2020 Through 15-05-2020",
}