Visualizing Streaming Data in Industrial Scale IoT Systems

Antero Taivalsaari; Tommi Mikkonen

doi:10.1145/3672608.3707790

Visualizing Streaming Data in Industrial Scale IoT Systems

Antero Taivalsaari, Tommi Mikkonen

Computing Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

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Abstract

In a complex IoT system with thousands of data streams, it can be difficult to comprehend the overall dynamic state of the system while also being able to quickly detect and pinpoint problems that occur in individual devices and streams. Over the years, we have experimented with a variety of techniques for visualizing large-scale streaming data systems to enable viewing of their behavior in a quick, "at-a-glance"fashion. In this paper we summarize the lessons that we have learned over the years, as well as provide an overview of the Haywire system that we have developed in response to the visualization challenges that arise in the context of industrial scale IoT systems.

Original language	English
Title of host publication	40th Annual ACM Symposium on Applied Computing, SAC 2025
Publisher	ACM
Pages	663-670
Number of pages	8
ISBN (Electronic)	979-8-4007-0629-5
DOIs	https://doi.org/10.1145/3672608.3707790
Publication status	Published - 14 May 2025
Publication type	A4 Article in conference proceedings
Event	Annual ACM Symposium on Applied Computing - Catania, Italy Duration: 31 Mar 2025 → 4 Apr 2025

Conference

Conference	Annual ACM Symposium on Applied Computing
Country/Territory	Italy
City	Catania
Period	31/03/25 → 4/04/25

Keywords

data visualization
edge computing
fog computing
internet of things
IoT
message brokers
programmable world
stream processing
streaming data

Publication forum classification

Publication forum level 1

ASJC Scopus subject areas

Software

Access to Document

10.1145/3672608.3707790Licence: CC BY

3672608.3707790Final published version, 1.84 MBLicence: CC BY

https://urn.fi/URN:NBN:fi:tuni-202506177269Licence: CC BY

Cite this

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title = "Visualizing Streaming Data in Industrial Scale IoT Systems",

abstract = "In a complex IoT system with thousands of data streams, it can be difficult to comprehend the overall dynamic state of the system while also being able to quickly detect and pinpoint problems that occur in individual devices and streams. Over the years, we have experimented with a variety of techniques for visualizing large-scale streaming data systems to enable viewing of their behavior in a quick, {"}at-a-glance{"}fashion. In this paper we summarize the lessons that we have learned over the years, as well as provide an overview of the Haywire system that we have developed in response to the visualization challenges that arise in the context of industrial scale IoT systems.",

keywords = "data visualization, edge computing, fog computing, internet of things, IoT, message brokers, programmable world, stream processing, streaming data",

author = "Antero Taivalsaari and Tommi Mikkonen",

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AU - Mikkonen, Tommi

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AB - In a complex IoT system with thousands of data streams, it can be difficult to comprehend the overall dynamic state of the system while also being able to quickly detect and pinpoint problems that occur in individual devices and streams. Over the years, we have experimented with a variety of techniques for visualizing large-scale streaming data systems to enable viewing of their behavior in a quick, "at-a-glance"fashion. In this paper we summarize the lessons that we have learned over the years, as well as provide an overview of the Haywire system that we have developed in response to the visualization challenges that arise in the context of industrial scale IoT systems.

KW - data visualization

KW - edge computing

KW - fog computing

KW - internet of things

KW - IoT

KW - message brokers

KW - programmable world

KW - stream processing

KW - streaming data

U2 - 10.1145/3672608.3707790

DO - 10.1145/3672608.3707790

M3 - Conference contribution

AN - SCOPUS:105006470348

SP - 663

EP - 670

BT - 40th Annual ACM Symposium on Applied Computing, SAC 2025

PB - ACM

T2 - Annual ACM Symposium on Applied Computing

Y2 - 31 March 2025 through 4 April 2025

ER -

Visualizing Streaming Data in Industrial Scale IoT Systems

Abstract

Conference

Keywords

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ASJC Scopus subject areas

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