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https://doi.org/10.21256/zhaw-3487| Publication type: | Conference paper |
| Type of review: | Peer review (publication) |
| Title: | A hybrid approach for alarm verification using stream processing, machine learning and text analytics |
| Authors: | Sima, Ana-Claudia Stockinger, Kurt Affolter, Katrin Braschler, Martin Monte, Peter Kaiser, Lukas |
| DOI: | 10.21256/zhaw-3487 |
| Proceedings: | Proceedings of the 21st International Conference on Extending Database Technology |
| Conference details: | EDBT 2018, Vienna, Austria, 26-29 March 2018 |
| Issue Date: | 2018 |
| Publisher / Ed. Institution: | Association for Computing Machinery |
| ISBN: | 978-3-89318-078-3 |
| Language: | English |
| Subjects: | Database technology; Stream processing; Machine learning; Text analytics |
| Subject (DDC): | 006: Special computer methods |
| Abstract: | False alarms triggered by security sensors incur high costs for all parties involved. According to police reports, a large majority of alarms are false. Recent advances in machine learning can enable automatically classifying alarms. However, building a scalable alarm verification system is a challenge, since the system needs to: (1) process thousands of alarms in real-time, (2) classify false alarms with high accuracy and (3) perform historic data analysis to enable better insights into the results for human operators. This requires a mix of machine learning, stream and batch processing – technologies which are typically optimized independently. We combine all three into a single, real-world application. This paper describes the implementation and evaluation of an alarm verification system we developed jointly with Sitasys, the market leader in alarm transmission in central Europe. Our system can process around 30K alarms per second with a verification accuracy of above 90%. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/2180 |
| Fulltext version: | Published version |
| License (according to publishing contract): | CC BY-NC-ND 4.0: Attribution - Non commercial - No derivatives 4.0 International |
| Departement: | School of Engineering |
| Organisational Unit: | Institute of Computer Science (InIT) |
| Published as part of the ZHAW project: | SAVE - Smart Alarms & Verified Events |
| Appears in collections: | Publikationen School of Engineering |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| AlarmVerfication_EDBT2018.pdf | 1.71 MB | Adobe PDF |  View/Open |
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Sima, A.-C., Stockinger, K., Affolter, K., Braschler, M., Monte, P., & Kaiser, L. (2018). A hybrid approach for alarm verification using stream processing, machine learning and text analytics. Proceedings of the 21st International Conference on Extending Database Technology. https://doi.org/10.21256/zhaw-3487
Sima, A.-C. et al. (2018) ‘A hybrid approach for alarm verification using stream processing, machine learning and text analytics’, in Proceedings of the 21st International Conference on Extending Database Technology. Association for Computing Machinery. Available at: https://doi.org/10.21256/zhaw-3487.
A.-C. Sima, K. Stockinger, K. Affolter, M. Braschler, P. Monte, and L. Kaiser, “A hybrid approach for alarm verification using stream processing, machine learning and text analytics,” in Proceedings of the 21st International Conference on Extending Database Technology, 2018. doi: 10.21256/zhaw-3487.
SIMA, Ana-Claudia, Kurt STOCKINGER, Katrin AFFOLTER, Martin BRASCHLER, Peter MONTE und Lukas KAISER, 2018. A hybrid approach for alarm verification using stream processing, machine learning and text analytics. In: Proceedings of the 21st International Conference on Extending Database Technology. Conference paper. Association for Computing Machinery. 2018. ISBN 978-3-89318-078-3
Sima, Ana-Claudia, Kurt Stockinger, Katrin Affolter, Martin Braschler, Peter Monte, and Lukas Kaiser. 2018. “A Hybrid Approach for Alarm Verification Using Stream Processing, Machine Learning and Text Analytics.” Conference paper. In Proceedings of the 21st International Conference on Extending Database Technology. Association for Computing Machinery. https://doi.org/10.21256/zhaw-3487.
Sima, Ana-Claudia, et al. “A Hybrid Approach for Alarm Verification Using Stream Processing, Machine Learning and Text Analytics.” Proceedings of the 21st International Conference on Extending Database Technology, Association for Computing Machinery, 2018, https://doi.org/10.21256/zhaw-3487.
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