Andrea Burattin

Associate Professor
Technical University of Denmark


Viola: Detecting Violations of Behaviors from Streams of Sensor Data

G. Di Federico, G. Meroni, A. Burattin
Abstract
Paper cover

Sensor networks and the Internet of Things enable the easy collection of environmental data. With this data it is possible to perceive the activities carried out in an environment. For example, in healthcare, sensor data could be used to identify and monitor the daily routine of people with dementia. In fact, changes in routines could be a symptom of the worsening of the disease. Streaming conformance checking techniques aim at identifying in real-time, from a stream of events, whether the observed behavior differs from the expected one. However, they require a stream of activities, not sensor data. The artifact-driven process monitoring approach combines the structure of the control-flow with the data in an E-GSM model. This paper presents VIOLA, the first technique capable of automatically mining an E-GSM model from a labeled sensor data log, which is then suitable for runtime monitoring from an unlabeled sensor stream to accomplish our goal (i.e., streaming conformance checking). This approach is implemented and has been validated with synthetic sensor data and a real-world example.

Paper Information and Files

In Proceedings of the BP-Meet-IoT Workshop (BP-Meet-IoT 2022); Utrecht, The Netherlands; September 11, 2023.

General rights

Copyright and moral rights for the publications made accessible in the public website are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.

If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.

Latest website update: 17 June 2024.