Correlating Time Series Signals and Event Logs in Embedded Systems

In many embedded systems, we face the problem of correlating signals characterising device operation (e.g., performance parameters, anomalies) with events describing internal device activities. This leads to the investigation of two types of data: time series, representing signal periodic samples in...

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Autores principales:	Kazimierz Krosman, Janusz Sosnowski
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	signal processing embedded systems data synchronisation issues device monitoring time series analysis Chemical technology TP1-1185
Acceso en línea:	https://doaj.org/article/7f3016852ffb45d2a1a87499a238802e
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id	oai:doaj.org-article:7f3016852ffb45d2a1a87499a238802e
record_format	dspace
spelling	oai:doaj.org-article:7f3016852ffb45d2a1a87499a238802e2021-11-11T19:07:52ZCorrelating Time Series Signals and Event Logs in Embedded Systems10.3390/s212171281424-8220https://doaj.org/article/7f3016852ffb45d2a1a87499a238802e2021-10-01T00:00:00Zhttps://www.mdpi.com/1424-8220/21/21/7128https://doaj.org/toc/1424-8220In many embedded systems, we face the problem of correlating signals characterising device operation (e.g., performance parameters, anomalies) with events describing internal device activities. This leads to the investigation of two types of data: time series, representing signal periodic samples in a background of noise, and sporadic event logs. The correlation process must take into account clock inconsistencies between the data acquisition and monitored devices, which provide time series signals and event logs, respectively. The idea of the presented solution is to classify event logs based on the introduced similarity metric and deriving their distribution in time. The identified event log sequences are matched with time intervals corresponding to specified sample patterns (objects) in the registered signal time series. The matching (correlation) process involves iterative time offset adjustment. The paper presents original algorithms to investigate correlation problems using the object-oriented data models corresponding to two monitoring sources. The effectiveness of this approach has been verified in power consumption analysis using real data collected from the developed Holter device. It is quite universal and can be easily adapted to other device optimisation problems.Kazimierz KrosmanJanusz SosnowskiMDPI AGarticlesignal processingembedded systemsdata synchronisation issuesdevice monitoringtime series analysisChemical technologyTP1-1185ENSensors, Vol 21, Iss 7128, p 7128 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	signal processing embedded systems data synchronisation issues device monitoring time series analysis Chemical technology TP1-1185
spellingShingle	signal processing embedded systems data synchronisation issues device monitoring time series analysis Chemical technology TP1-1185 Kazimierz Krosman Janusz Sosnowski Correlating Time Series Signals and Event Logs in Embedded Systems
description	In many embedded systems, we face the problem of correlating signals characterising device operation (e.g., performance parameters, anomalies) with events describing internal device activities. This leads to the investigation of two types of data: time series, representing signal periodic samples in a background of noise, and sporadic event logs. The correlation process must take into account clock inconsistencies between the data acquisition and monitored devices, which provide time series signals and event logs, respectively. The idea of the presented solution is to classify event logs based on the introduced similarity metric and deriving their distribution in time. The identified event log sequences are matched with time intervals corresponding to specified sample patterns (objects) in the registered signal time series. The matching (correlation) process involves iterative time offset adjustment. The paper presents original algorithms to investigate correlation problems using the object-oriented data models corresponding to two monitoring sources. The effectiveness of this approach has been verified in power consumption analysis using real data collected from the developed Holter device. It is quite universal and can be easily adapted to other device optimisation problems.
format	article
author	Kazimierz Krosman Janusz Sosnowski
author_facet	Kazimierz Krosman Janusz Sosnowski
author_sort	Kazimierz Krosman
title	Correlating Time Series Signals and Event Logs in Embedded Systems
title_short	Correlating Time Series Signals and Event Logs in Embedded Systems
title_full	Correlating Time Series Signals and Event Logs in Embedded Systems
title_fullStr	Correlating Time Series Signals and Event Logs in Embedded Systems
title_full_unstemmed	Correlating Time Series Signals and Event Logs in Embedded Systems
title_sort	correlating time series signals and event logs in embedded systems
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/7f3016852ffb45d2a1a87499a238802e
work_keys_str_mv	AT kazimierzkrosman correlatingtimeseriessignalsandeventlogsinembeddedsystems AT januszsosnowski correlatingtimeseriessignalsandeventlogsinembeddedsystems
_version_	1718431593955065856

Correlating Time Series Signals and Event Logs in Embedded Systems

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