A Real-time Temperature Anomaly Detection Method for IoT Data

Wei Liu, Hongyi Jiang, Dandan Che, Lifei Chen, Qingshan Jiang

Abstract

Temperature control plays a vital part in medical supply management, of which effective monitoring and anomaly detection ensure that the medication storage is maintained properly to meet health and safety requirements. In this paper, an unsupervised temperature anomaly detection method, called DTAD (Dynamic Threshold Anomaly Detection), is proposed to detect anomalies in real-time temperature time series. The DTAD sets dynamic thresholds based on the Smoothed Z-Score Algorithm, rather than set fixed thresholds of a temperature range by experience. The comparative evaluation is performed on the DTAD and four other commonly employed methods, the results of which shows that the DTAD reaches a higher accuracy and a better time efficiency. The DTAD is fully automated and can be used in developing a real-time IoT temperature anomaly detection system for medical equipment.

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Paper Citation


in Harvard Style

Liu W., Jiang H., Che D., Chen L. and Jiang Q. (2020). A Real-time Temperature Anomaly Detection Method for IoT Data.In Proceedings of the 5th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS, ISBN 978-989-758-426-8, pages 112-118. DOI: 10.5220/0009410001120118


in Bibtex Style

@conference{iotbds20,
author={Wei Liu and Hongyi Jiang and Dandan Che and Lifei Chen and Qingshan Jiang},
title={A Real-time Temperature Anomaly Detection Method for IoT Data},
booktitle={Proceedings of the 5th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS,},
year={2020},
pages={112-118},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009410001120118},
isbn={978-989-758-426-8},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 5th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS,
TI - A Real-time Temperature Anomaly Detection Method for IoT Data
SN - 978-989-758-426-8
AU - Liu W.
AU - Jiang H.
AU - Che D.
AU - Chen L.
AU - Jiang Q.
PY - 2020
SP - 112
EP - 118
DO - 10.5220/0009410001120118