Non-standard situation detection in smart water metering

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2020-12-17 DOI:10.1515/comp-2020-0190

O. Kainz, E. Karpiel, R. Petija, M. Michalko, F. Jakab

引用次数: 0

Abstract

Abstract In this paper an algorithm for detection of nonstandard situations in smart water metering based on machine learning is designed. The main categories for nonstandard situation or anomaly detection and two common methods for anomaly detection are analyzed. The proposed solution needs to fit the requirements for correct, efficient and real-time detection of non-standard situations in actual water consumption with minimal required consumer intervention to its operation. Moreover, a proposal to extend the original hardware solution is described and implemented to accommodate the needs of the detection algorithm. The final implemented and tested solution evaluates anomalies in water consumption for a given time in specific day and month using machine learning with a semi-supervised approach.

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智能水表中的非标准状态检测

摘要本文设计了一种基于机器学习的智能水表非标准情况检测算法。分析了非标准状态或异常检测的主要类别以及两种常见的异常检测方法。所提出的解决方案需要满足在实际用水量中正确、高效和实时检测非标准情况的要求，同时对其操作进行最少的消费者干预。此外，描述并实现了扩展原始硬件解决方案的建议，以满足检测算法的需求。最终实现和测试的解决方案使用机器学习和半监督方法评估特定日期和月份给定时间的用水量异常。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.