Preprint Article Version 2 Preserved in Portico This version is not peer-reviewed

Anomaly Detection in Particulate Matter Sensor Using Hypothesis Pruning Generative Adversarial Network

Version 1 : Received: 3 January 2020 / Approved: 4 January 2020 / Online: 4 January 2020 (06:03:08 CET)
Version 2 : Received: 13 February 2020 / Approved: 14 February 2020 / Online: 14 February 2020 (05:23:15 CET)

How to cite: Park, Y.H.; Park, W.S.; Kim, Y.B. Anomaly Detection in Particulate Matter Sensor Using Hypothesis Pruning Generative Adversarial Network. Preprints 2020, 2020010028. https://doi.org/10.20944/preprints202001.0028.v2 Park, Y.H.; Park, W.S.; Kim, Y.B. Anomaly Detection in Particulate Matter Sensor Using Hypothesis Pruning Generative Adversarial Network. Preprints 2020, 2020010028. https://doi.org/10.20944/preprints202001.0028.v2

Abstract

World Health Organization (WHO) provides the guideline for managing the Particulate Matter (PM) level because when the PM level is higher, it threats the human health. For managing PM level, the procedure for measuring PM value is needed firstly. We use Tapered Element Oscillating Microbalance (TEOM)-based PM measuring sensors because it shows higher cost-effectiveness than Beta Attenuation Monitor (BAM)-based sensor. However, TEOM-based sensor has higher probability of malfunctioning than BAM-based sensor. In this paper, we call the overall malfunction as an anomaly, and we aim to detect anomalies for the maintenance of PM measuring sensors. We propose a novel architecture for solving the above aim that named as Hypothesis Pruning Generative Adversarial Network (HP-GAN). We experimentally compare the several anomaly detection architectures to certify ours performing better.

Keywords

anomaly detection; generative adversarial network; multiple hypothesis; particulate matter

Subject

Computer Science and Mathematics, Information Systems

Comments (1)

Comment 1
Received: 14 February 2020
Commenter: Park YeongHyeon
Commenter's Conflict of Interests: Author
Comment: Author information has changed. Due to internal circumstances, one of the authors is removed. Also, the detail description of the manuscript is changed.
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