Time-Series Anomaly Detection for Sensor Data: Models, Metrics, and Methodologies—A Review
- DOI
- 10.1109/jsen.2025.3616395
- Published
- 2025-12-15
- Container
- IEEE Sensors Journal
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1109/jsen.2025.3616395,
title = {Time-Series Anomaly Detection for Sensor Data: Models, Metrics, and Methodologies—A Review},
author = {Mohamad Issam Sayyaf and Pavel Pascacio and Ni Zhu and Valerie Renaudin},
year = {2025},
journal = {IEEE Sensors Journal},
doi = {10.1109/jsen.2025.3616395},
url = {https://doi.org/10.1109/jsen.2025.3616395}
}RIS
TY - JOUR TI - Time-Series Anomaly Detection for Sensor Data: Models, Metrics, and Methodologies—A Review AU - Mohamad Issam Sayyaf AU - Pavel Pascacio AU - Ni Zhu AU - Valerie Renaudin PY - 2025 JO - IEEE Sensors Journal DO - 10.1109/jsen.2025.3616395 UR - https://doi.org/10.1109/jsen.2025.3616395 ER -
APA
Sayyaf, M. I., Pascacio, P., Zhu, N., & Renaudin, V. (2025). Time-Series Anomaly Detection for Sensor Data: Models, Metrics, and Methodologies—A Review. IEEE Sensors Journal. https://doi.org/10.1109/jsen.2025.3616395
Source records
- crossref · retrieved 2026-09-26T03:25:37.160Z