Towards industrial assistance systems: Experiences of applying multi-sensor fusion in harsh environments

Michael Haslgrübler; Benedikt Gollan; Alois Ferscha

doi:10.1007/978-3-030-27950-9_9

Towards industrial assistance systems: Experiences of applying multi-sensor fusion in harsh environments

Michael Haslgrübler^*
, Benedikt Gollan
, Alois Ferscha

^*Corresponding author for this work

Institute of Pervasive Computing

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

Abstract

With the availability of miniaturized low cost sensors and the general availability and easy applicability of algorithms for activity recognition, we investigate how various sensors can be deployed in a harsh environment, the industrial shop-floor. We review related work and provide an in-depth review of our own experiences were sensors wer used to enable recognition of activity, task progress and also mental and cognitive states of assembly workers. The recognition process is based on stationary and wearable devices. We describe in detail the used sensors, the challenges of fusing the data from these various sources together in real-time and how to interpret that data semantically.

Original language	English
Title of host publication	Physiological Computing Systems - International Conferences, PhyCS 2016, PhyCS 2017, PhyCS 2018, Revised and Extended Selected Papers
Editors	Andreas Holzinger, Alan Pope, Hugo Plácido da Silva
Publisher	Springer Verlag
Pages	158-179
Number of pages	22
ISBN (Print)	9783030279493
DOIs	https://doi.org/10.1007/978-3-030-27950-9_9
Publication status	Published - 2019
Event	3rd International Conference on Physiological Computing Systems, PhyCS 2016, 4th International Conference on Physiological Computing Systems, PhyCS 2017 and 5th International Conference on Physiological Computing Systems, PhyCS 2018 - Seville, Spain Duration: 19 Sept 2018 → 21 Sept 2018

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10057 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	3rd International Conference on Physiological Computing Systems, PhyCS 2016, 4th International Conference on Physiological Computing Systems, PhyCS 2017 and 5th International Conference on Physiological Computing Systems, PhyCS 2018
Country/Territory	Spain
City	Seville
Period	19.09.2018 → 21.09.2018

Fields of science

102009 Computer simulation
102020 Medical informatics
102013 Human-computer interaction
102019 Machine learning
211902 Assistive technologies
102022 Software development
202017 Embedded systems
211912 Product design
102021 Pervasive computing
102025 Distributed systems
102 Computer Sciences

JKU Focus areas

Digital Transformation

Access to Document

10.1007/978-3-030-27950-9_9

Cite this

Haslgrübler, M., Gollan, B., & Ferscha, A. (2019). Towards industrial assistance systems: Experiences of applying multi-sensor fusion in harsh environments. In A. Holzinger, A. Pope, & H. Plácido da Silva (Eds.), Physiological Computing Systems - International Conferences, PhyCS 2016, PhyCS 2017, PhyCS 2018, Revised and Extended Selected Papers (pp. 158-179). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10057 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-27950-9_9

Haslgrübler, Michael ; Gollan, Benedikt ; Ferscha, Alois. / Towards industrial assistance systems : Experiences of applying multi-sensor fusion in harsh environments. Physiological Computing Systems - International Conferences, PhyCS 2016, PhyCS 2017, PhyCS 2018, Revised and Extended Selected Papers. editor / Andreas Holzinger ; Alan Pope ; Hugo Plácido da Silva. Springer Verlag, 2019. pp. 158-179 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Towards industrial assistance systems: Experiences of applying multi-sensor fusion in harsh environments",

abstract = "With the availability of miniaturized low cost sensors and the general availability and easy applicability of algorithms for activity recognition, we investigate how various sensors can be deployed in a harsh environment, the industrial shop-floor. We review related work and provide an in-depth review of our own experiences were sensors wer used to enable recognition of activity, task progress and also mental and cognitive states of assembly workers. The recognition process is based on stationary and wearable devices. We describe in detail the used sensors, the challenges of fusing the data from these various sources together in real-time and how to interpret that data semantically.",

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author = "Michael Haslgr{\"u}bler and Benedikt Gollan and Alois Ferscha",

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year = "2019",

doi = "10.1007/978-3-030-27950-9\_9",

language = "English",

isbn = "9783030279493",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "158--179",

editor = "Andreas Holzinger and Alan Pope and \{Pl{\'a}cido da Silva\}, Hugo",

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}

Haslgrübler, M, Gollan, B & Ferscha, A 2019, Towards industrial assistance systems: Experiences of applying multi-sensor fusion in harsh environments. in A Holzinger, A Pope & H Plácido da Silva (eds), Physiological Computing Systems - International Conferences, PhyCS 2016, PhyCS 2017, PhyCS 2018, Revised and Extended Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10057 LNCS, Springer Verlag, pp. 158-179, 3rd International Conference on Physiological Computing Systems, PhyCS 2016, 4th International Conference on Physiological Computing Systems, PhyCS 2017 and 5th International Conference on Physiological Computing Systems, PhyCS 2018, Seville, Spain, 19.09.2018. https://doi.org/10.1007/978-3-030-27950-9_9

Towards industrial assistance systems: Experiences of applying multi-sensor fusion in harsh environments. / Haslgrübler, Michael; Gollan, Benedikt; Ferscha, Alois.
Physiological Computing Systems - International Conferences, PhyCS 2016, PhyCS 2017, PhyCS 2018, Revised and Extended Selected Papers. ed. / Andreas Holzinger; Alan Pope; Hugo Plácido da Silva. Springer Verlag, 2019. p. 158-179 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10057 LNCS).

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

TY - GEN

T1 - Towards industrial assistance systems

T2 - 3rd International Conference on Physiological Computing Systems, PhyCS 2016, 4th International Conference on Physiological Computing Systems, PhyCS 2017 and 5th International Conference on Physiological Computing Systems, PhyCS 2018

AU - Haslgrübler, Michael

AU - Gollan, Benedikt

AU - Ferscha, Alois

N1 - Publisher Copyright: © Springer Nature Switzerland AG 2019.

PY - 2019

Y1 - 2019

N2 - With the availability of miniaturized low cost sensors and the general availability and easy applicability of algorithms for activity recognition, we investigate how various sensors can be deployed in a harsh environment, the industrial shop-floor. We review related work and provide an in-depth review of our own experiences were sensors wer used to enable recognition of activity, task progress and also mental and cognitive states of assembly workers. The recognition process is based on stationary and wearable devices. We describe in detail the used sensors, the challenges of fusing the data from these various sources together in real-time and how to interpret that data semantically.

AB - With the availability of miniaturized low cost sensors and the general availability and easy applicability of algorithms for activity recognition, we investigate how various sensors can be deployed in a harsh environment, the industrial shop-floor. We review related work and provide an in-depth review of our own experiences were sensors wer used to enable recognition of activity, task progress and also mental and cognitive states of assembly workers. The recognition process is based on stationary and wearable devices. We describe in detail the used sensors, the challenges of fusing the data from these various sources together in real-time and how to interpret that data semantically.

KW - Challenges

KW - Industrial application multi-sensor fusion

KW - Sensor evaluation

KW - Stational sensors

KW - Wearable sensors

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U2 - 10.1007/978-3-030-27950-9_9

DO - 10.1007/978-3-030-27950-9_9

M3 - Conference proceedings

AN - SCOPUS:85072830106

SN - 9783030279493

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 158

EP - 179

BT - Physiological Computing Systems - International Conferences, PhyCS 2016, PhyCS 2017, PhyCS 2018, Revised and Extended Selected Papers

A2 - Holzinger, Andreas

A2 - Pope, Alan

A2 - Plácido da Silva, Hugo

PB - Springer Verlag

Y2 - 19 September 2018 through 21 September 2018

ER -

Haslgrübler M, Gollan B, Ferscha A. Towards industrial assistance systems: Experiences of applying multi-sensor fusion in harsh environments. In Holzinger A, Pope A, Plácido da Silva H, editors, Physiological Computing Systems - International Conferences, PhyCS 2016, PhyCS 2017, PhyCS 2018, Revised and Extended Selected Papers. Springer Verlag. 2019. p. 158-179. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-27950-9_9

Towards industrial assistance systems: Experiences of applying multi-sensor fusion in harsh environments

Abstract

Publication series

Conference

Fields of science

JKU Focus areas

Access to Document

Other files and links

Pro2Future - Products and Production Systems of the Future

Attentive Machines: Man and Machines in ICT based Production Systems of the Future

Cite this

Towards industrial assistance systems: Experiences of applying multi-sensor fusion in harsh environments

Abstract

Publication series

Conference

Fields of science

JKU Focus areas

Access to Document

Other files and links

Projects

Pro2Future - Products and Production Systems of the Future

Attentive Machines: Man and Machines in ICT based Production Systems of the Future

Cite this