IoT Architecture and Solutions for Predictive Maintenance of Mobile Machinery

Jani Hietala; Kalle Raunio; Tero Jokinen; Petri Kaarmila

doi:10.1109/IECON49645.2022.9968653

IoT Architecture and Solutions for Predictive Maintenance of Mobile Machinery

Jani Hietala
, Kalle Raunio
, Tero Jokinen
, Petri Kaarmila

BA55 Knowledge driven design

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

3 Citations (Scopus)

Abstract

Continuous development of advanced web and IoT technologies facilitate new solutions for scalable data management systems. Data can be transferred over the internet efficiently in standardized formats. We propose a system architecture applicable to both mobile machinery and other industries. We introduce standards and technologies for collecting and analysing data in addition to exchanging the data in cloud applications and with partner systems. Data is exchanged in a standardized MIMOSA CCOM format over efficient MQTT communication protocol for near real-time updates of operation. Eclipse Arrowhead framework is used to securely manage the edge and cloud services. VTT O&M Analytics provide predictive maintenance services for mobile machinery based on the collected data. We describe in detail a system designed for collecting and analysing data from the combination seed drill. Our architecture facilitates monitoring and predictive maintenance, thus improving crop yields and OEE.

Original language	English
Title of host publication	IECON 2022 - 48th Annual Conference of the IEEE Industrial Electronics Society
Publisher	IEEE Institute of Electrical and Electronic Engineers
Number of pages	6
ISBN (Electronic)	978-1-6654-8025-3
ISBN (Print)	978-1-6654-8026-0
DOIs	https://doi.org/10.1109/IECON49645.2022.9968653
Publication status	Published - 9 Dec 2022
MoE publication type	A4 Article in a conference publication
Event	48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022 - Brussels, Belgium Duration: 17 Oct 2022 → 20 Oct 2022

Conference

Conference	48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022
Country/Territory	Belgium
City	Brussels
Period	17/10/22 → 20/10/22

Keywords

CCOM
MQTT
arrowhead
Arrowhead

Access to Document

10.1109/IECON49645.2022.9968653

Cite this

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title = "IoT Architecture and Solutions for Predictive Maintenance of Mobile Machinery",

abstract = "Continuous development of advanced web and IoT technologies facilitate new solutions for scalable data management systems. Data can be transferred over the internet efficiently in standardized formats. We propose a system architecture applicable to both mobile machinery and other industries. We introduce standards and technologies for collecting and analysing data in addition to exchanging the data in cloud applications and with partner systems. Data is exchanged in a standardized MIMOSA CCOM format over efficient MQTT communication protocol for near real-time updates of operation. Eclipse Arrowhead framework is used to securely manage the edge and cloud services. VTT O\&M Analytics provide predictive maintenance services for mobile machinery based on the collected data. We describe in detail a system designed for collecting and analysing data from the combination seed drill. Our architecture facilitates monitoring and predictive maintenance, thus improving crop yields and OEE.",

keywords = "CCOM, MQTT, arrowhead, Arrowhead",

author = "Jani Hietala and Kalle Raunio and Tero Jokinen and Petri Kaarmila",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022 ; Conference date: 17-10-2022 Through 20-10-2022",

year = "2022",

month = dec,

day = "9",

doi = "10.1109/IECON49645.2022.9968653",

language = "English",

isbn = "978-1-6654-8026-0",

booktitle = "IECON 2022 - 48th Annual Conference of the IEEE Industrial Electronics Society",

publisher = "IEEE Institute of Electrical and Electronic Engineers",

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}

Hietala, J, Raunio, K , Jokinen, T & Kaarmila, P 2022, IoT Architecture and Solutions for Predictive Maintenance of Mobile Machinery. in IECON 2022 - 48th Annual Conference of the IEEE Industrial Electronics Society., 9968653, IEEE Institute of Electrical and Electronic Engineers, 48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022, Brussels, Belgium, 17/10/22. https://doi.org/10.1109/IECON49645.2022.9968653

IoT Architecture and Solutions for Predictive Maintenance of Mobile Machinery. / Hietala, Jani; Raunio, Kalle ; Jokinen, Tero et al.
IECON 2022 - 48th Annual Conference of the IEEE Industrial Electronics Society. IEEE Institute of Electrical and Electronic Engineers, 2022. 9968653.

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

TY - GEN

T1 - IoT Architecture and Solutions for Predictive Maintenance of Mobile Machinery

AU - Hietala, Jani

AU - Raunio, Kalle

AU - Jokinen, Tero

AU - Kaarmila, Petri

PY - 2022/12/9

Y1 - 2022/12/9

N2 - Continuous development of advanced web and IoT technologies facilitate new solutions for scalable data management systems. Data can be transferred over the internet efficiently in standardized formats. We propose a system architecture applicable to both mobile machinery and other industries. We introduce standards and technologies for collecting and analysing data in addition to exchanging the data in cloud applications and with partner systems. Data is exchanged in a standardized MIMOSA CCOM format over efficient MQTT communication protocol for near real-time updates of operation. Eclipse Arrowhead framework is used to securely manage the edge and cloud services. VTT O&M Analytics provide predictive maintenance services for mobile machinery based on the collected data. We describe in detail a system designed for collecting and analysing data from the combination seed drill. Our architecture facilitates monitoring and predictive maintenance, thus improving crop yields and OEE.

AB - Continuous development of advanced web and IoT technologies facilitate new solutions for scalable data management systems. Data can be transferred over the internet efficiently in standardized formats. We propose a system architecture applicable to both mobile machinery and other industries. We introduce standards and technologies for collecting and analysing data in addition to exchanging the data in cloud applications and with partner systems. Data is exchanged in a standardized MIMOSA CCOM format over efficient MQTT communication protocol for near real-time updates of operation. Eclipse Arrowhead framework is used to securely manage the edge and cloud services. VTT O&M Analytics provide predictive maintenance services for mobile machinery based on the collected data. We describe in detail a system designed for collecting and analysing data from the combination seed drill. Our architecture facilitates monitoring and predictive maintenance, thus improving crop yields and OEE.

KW - CCOM

KW - MQTT

KW - arrowhead

KW - Arrowhead

UR - https://www.scopus.com/pages/publications/85143891741

U2 - 10.1109/IECON49645.2022.9968653

DO - 10.1109/IECON49645.2022.9968653

M3 - Conference article in proceedings

SN - 978-1-6654-8026-0

BT - IECON 2022 - 48th Annual Conference of the IEEE Industrial Electronics Society

PB - IEEE Institute of Electrical and Electronic Engineers

T2 - 48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022

Y2 - 17 October 2022 through 20 October 2022

ER -

IoT Architecture and Solutions for Predictive Maintenance of Mobile Machinery

Abstract

Conference

Keywords

Access to Document

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Applying MIMOSA CCOM to modern web interfaces

MIMOSA for Condition-based Maintenance

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