---
_id: '13721'
abstract:
- lang: eng
text: In this study, we examined the possibility of detecting different types of
materials that contaminate carcasses during industrial pig slaughter using video
image analysis and artificial intelligence (AI). A camera system was installed
between evisceration and postmortem meat inspection on an industrial pig slaughter
line with a capacity of 12,000 pigs per day. The pigs were photographed using
five 2D cameras, and the images were analysed for contamination using an AI-based
algorithm. The setup, which was developed and installed by CLK GmbH, performed
under industrial conditions. In order to train the system, specifications were
created for the most frequently occurring types of contamination, namely, intestinal
contents, bile, stomach contents, and tubular rail fat. Afterward, the system
was trained using annotated images. In principle, the system was able to recognize
all types of contamination on the camera images; even pinhead-sized contaminations
were visible. The agreement between the algorithm and the results of an expert
assessor who assessed the images online agreed in 60% of the judgements. The agreement
between experts using onsite assessment and those using online assessment by images
was 73%. Thus, the kappa measure of agreement was κ = 0.1215 (p = 0.0199). Significantly
higher recognition rates appear to be possible by adjusting the algorithm and
increasing the number of training images. Thus, the system is a useful tool to
preselect contaminated carcasses and to support postmortem inspection.
article_number: '1698416'
author:
- first_name: Janna
full_name: Tholen, Janna
id: '80924'
last_name: Tholen
- first_name: Alina
full_name: Kirse, Alina
last_name: Kirse
- first_name: Alexander
full_name: Voß, Alexander
last_name: Voß
- first_name: Gereon
full_name: Schulze Althoff, Gereon
last_name: Schulze Althoff
- first_name: Lea
full_name: Strotkötter, Lea
last_name: Strotkötter
- first_name: Lothar
full_name: Kreienbrock, Lothar
last_name: Kreienbrock
- first_name: Matthias
full_name: Upmann, Matthias
id: '12666'
last_name: Upmann
citation:
ama: Tholen J, Kirse A, Voß A, et al. Detection of carcass contamination using video
image analysis during industrial pig slaughter. Frontiers in Food Science and
Technology. 2026;6. doi:10.3389/frfst.2026.1698416
apa: Tholen, J., Kirse, A., Voß, A., Schulze Althoff, G., Strotkötter, L., Kreienbrock,
L., & Upmann, M. (2026). Detection of carcass contamination using video image
analysis during industrial pig slaughter. Frontiers in Food Science and Technology,
6, Article 1698416. https://doi.org/10.3389/frfst.2026.1698416
bjps: Tholen J et al. (2026) Detection of Carcass Contamination Using
Video Image Analysis during Industrial Pig Slaughter. Frontiers in Food Science
and Technology 6.
chicago: Tholen, Janna, Alina Kirse, Alexander Voß, Gereon Schulze Althoff, Lea
Strotkötter, Lothar Kreienbrock, and Matthias Upmann. “Detection of Carcass Contamination
Using Video Image Analysis during Industrial Pig Slaughter.” Frontiers in Food
Science and Technology 6 (2026). https://doi.org/10.3389/frfst.2026.1698416.
chicago-de: Tholen, Janna, Alina Kirse, Alexander Voß, Gereon Schulze Althoff, Lea
Strotkötter, Lothar Kreienbrock und Matthias Upmann. 2026. Detection of carcass
contamination using video image analysis during industrial pig slaughter. Frontiers
in Food Science and Technology 6. doi:10.3389/frfst.2026.1698416,
.
din1505-2-1: 'Tholen, Janna ; Kirse, Alina ; Voß,
Alexander ; Schulze Althoff, Gereon
; Strotkötter, Lea ; Kreienbrock,
Lothar ; Upmann, Matthias:
Detection of carcass contamination using video image analysis during industrial
pig slaughter. In: Frontiers in Food Science and Technology Bd. 6. Lausanne,
Frontiers Media SA (2026)'
havard: J. Tholen, A. Kirse, A. Voß, G. Schulze Althoff, L. Strotkötter, L. Kreienbrock,
M. Upmann, Detection of carcass contamination using video image analysis during
industrial pig slaughter, Frontiers in Food Science and Technology. 6 (2026).
ieee: 'J. Tholen et al., “Detection of carcass contamination using video
image analysis during industrial pig slaughter,” Frontiers in Food Science
and Technology, vol. 6, Art. no. 1698416, 2026, doi: 10.3389/frfst.2026.1698416.'
mla: Tholen, Janna, et al. “Detection of Carcass Contamination Using Video Image
Analysis during Industrial Pig Slaughter.” Frontiers in Food Science and Technology,
vol. 6, 1698416, 2026, https://doi.org/10.3389/frfst.2026.1698416.
short: J. Tholen, A. Kirse, A. Voß, G. Schulze Althoff, L. Strotkötter, L. Kreienbrock,
M. Upmann, Frontiers in Food Science and Technology 6 (2026).
ufg: 'Tholen, Janna u. a.: Detection of carcass contamination using video
image analysis during industrial pig slaughter, in: Frontiers in Food Science
and Technology 6 (2026).'
van: Tholen J, Kirse A, Voß A, Schulze Althoff G, Strotkötter L, Kreienbrock L,
et al. Detection of carcass contamination using video image analysis during industrial
pig slaughter. Frontiers in Food Science and Technology. 2026;6.
date_created: 2026-04-30T13:02:33Z
date_updated: 2026-05-04T09:41:58Z
department:
- _id: DEP4028
- _id: DEP4029
doi: 10.3389/frfst.2026.1698416
intvolume: ' 6'
keyword:
- artificial intelligence (AI)
- bile contamination
- contamination detection
- faecal contamination
- slaughter hygiene
- tubular rail fat
language:
- iso: eng
place: Lausanne
publication: Frontiers in Food Science and Technology
publication_identifier:
issn:
- 2674-1121
publication_status: published
publisher: Frontiers Media SA
status: public
title: Detection of carcass contamination using video image analysis during industrial
pig slaughter
type: scientific_journal_article
user_id: '83781'
volume: 6
year: '2026'
...
---
_id: '13730'
abstract:
- lang: eng
text: 'This paper introduces an LLM-mediated AI Advisor that contextualizes and
synthesizes heterogeneous explainable AI (XAI) outputs to support fast and calibrated
misinformation judgments in time-sensitive social media settings. We define LLM-mediated
XAI as a process in which a large language model aggregates, prioritizes, and
translates heterogeneous XAI outputs into a context-sensitive explanation tailored
to the user’s decision situation. Semantic features, XAI modules and LLM-based
summarization and synthesis enable the generation of explanations that are adapted
in three ways: compressed for time-efficient decisions, translated into non-technical
language, and progressively expandable for deeper inspection. Through a mixed-methods
user study, including a quantitative study and a qualitative study, we analyze
how users interpret, challenge and strategically rely on LLM-mediated explanations
during real-world misinformation assessment tasks. The findings indicate that
the approach reduces time-to-decision and supports critical inspection without
inducing over-reliance. Progressive disclosure and different techniques to present
information favored different user needs while conversational functionality was
rarely used due to unclear benefits and fear of confusion.'
author:
- first_name: Valentin
full_name: Grimm, Valentin
id: '74000'
last_name: Grimm
- first_name: Jessica
full_name: Rubart, Jessica
id: '45672'
last_name: Rubart
orcid: 0000-0003-0937-3551
- first_name: Eelco
full_name: Herder, Eelco
last_name: Herder
- first_name: Carsten
full_name: Röcker, Carsten
id: '61525'
last_name: Röcker
citation:
ama: 'Grimm V, Rubart J, Herder E, Röcker C. LLM-Mediated XAI Explanations: An
AI Advisor for Fast and Calibrated Judgments on Potential Misinformation.
(Balke WT, Plötzky F, Spaniol M, et al., eds.). ACM; 2026:110-116. doi:https://doi.org/10.1145/3795513.3810452'
apa: 'Grimm, V., Rubart, J., Herder, E., & Röcker, C. (2026). LLM-Mediated XAI
Explanations: An AI Advisor for Fast and Calibrated Judgments on Potential Misinformation.
In W.-T. Balke, F. Plötzky, M. Spaniol, E. Herder, L. Manikonda, H. Liu, L.-D.
Ibáñez, R. Rezapour, & ACM Press (Eds.), WebSci Companion ’26: Companion
Publication of the 2026 18th ACM Web Science Conference (pp. 110–116). ACM.
https://doi.org/10.1145/3795513.3810452'
bjps: 'Grimm V et al. (2026) LLM-Mediated XAI Explanations: An
AI Advisor for Fast and Calibrated Judgments on Potential Misinformation,
Balke W-T et al. (eds). New York, USA: ACM.'
chicago: 'Grimm, Valentin, Jessica Rubart, Eelco Herder, and Carsten Röcker. LLM-Mediated
XAI Explanations: An AI Advisor for Fast and Calibrated Judgments on Potential
Misinformation. Edited by Wolf-Tilo Balke, Florian Plötzky, Marc Spaniol,
Eelco Herder, Lydia Manikonda, Haiming Liu, Luis-Daniel Ibáñez, Rezvaneh Rezapour,
and ACM Press. WebSci Companion ’26: Companion Publication of the 2026 18th
ACM Web Science Conference. New York, USA: ACM, 2026. https://doi.org/10.1145/3795513.3810452.'
chicago-de: 'Grimm, Valentin, Jessica Rubart, Eelco Herder und Carsten Röcker. 2026.
LLM-Mediated XAI Explanations: An AI Advisor for Fast and Calibrated Judgments
on Potential Misinformation. Hg. von Wolf-Tilo Balke, Florian Plötzky, Marc
Spaniol, Eelco Herder, Lydia Manikonda, Haiming Liu, Luis-Daniel Ibáñez, Rezvaneh
Rezapour, und ACM Press. WebSci Companion ’26: Companion Publication of the
2026 18th ACM Web Science Conference. New York, USA: ACM. doi:https://doi.org/10.1145/3795513.3810452,
.'
din1505-2-1: 'Grimm, Valentin ; Rubart, Jessica ; Herder,
Eelco ; Röcker, Carsten ;
Balke,
W.-T. ; Plötzky, F. ; Spaniol, M. ; Herder,
E. ; Manikonda, L. ; Liu, H. ; Ibáñez,
L.-D. ; Rezapour, R. ; u. a.
(Hrsg.): LLM-Mediated XAI Explanations: An AI Advisor for Fast and Calibrated
Judgments on Potential Misinformation. New York, USA : ACM, 2026'
havard: 'V. Grimm, J. Rubart, E. Herder, C. Röcker, LLM-Mediated XAI Explanations:
An AI Advisor for Fast and Calibrated Judgments on Potential Misinformation, ACM,
New York, USA, 2026.'
ieee: 'V. Grimm, J. Rubart, E. Herder, and C. Röcker, LLM-Mediated XAI Explanations:
An AI Advisor for Fast and Calibrated Judgments on Potential Misinformation.
New York, USA: ACM, 2026, pp. 110–116. doi: https://doi.org/10.1145/3795513.3810452.'
mla: 'Grimm, Valentin, et al. “LLM-Mediated XAI Explanations: An AI Advisor for
Fast and Calibrated Judgments on Potential Misinformation.” WebSci Companion
’26: Companion Publication of the 2026 18th ACM Web Science Conference, edited
by Wolf-Tilo Balke et al., ACM, 2026, pp. 110–16, https://doi.org/10.1145/3795513.3810452.'
short: 'V. Grimm, J. Rubart, E. Herder, C. Röcker, LLM-Mediated XAI Explanations:
An AI Advisor for Fast and Calibrated Judgments on Potential Misinformation, ACM,
New York, USA, 2026.'
ufg: 'Grimm, Valentin u. a.: LLM-Mediated XAI Explanations: An AI Advisor
for Fast and Calibrated Judgments on Potential Misinformation, hg. von Balke,
Wolf-Tilo u. a., New York, USA 2026.'
van: 'Grimm V, Rubart J, Herder E, Röcker C. LLM-Mediated XAI Explanations: An AI
Advisor for Fast and Calibrated Judgments on Potential Misinformation. Balke WT,
Plötzky F, Spaniol M, Herder E, Manikonda L, Liu H, et al., editors. WebSci Companion
’26: Companion Publication of the 2026 18th ACM Web Science Conference. New York,
USA: ACM; 2026.'
conference:
end_date: 2026-05-26
location: Braunschweig
name: 18th ACM Web Science Conference ; WebSci Companion '26
start_date: 2026-05-26
corporate_editor:
- ACM Press
date_created: 2026-05-05T16:16:34Z
date_updated: 2026-07-02T10:16:02Z
department:
- _id: DEP5023
- _id: DEP8008
- _id: DEP5027
doi: https://doi.org/10.1145/3795513.3810452
editor:
- first_name: Wolf-Tilo
full_name: Balke, Wolf-Tilo
last_name: Balke
- first_name: Florian
full_name: Plötzky, Florian
last_name: Plötzky
- first_name: Marc
full_name: Spaniol, Marc
last_name: Spaniol
- first_name: Eelco
full_name: Herder, Eelco
last_name: Herder
- first_name: Lydia
full_name: Manikonda, Lydia
last_name: Manikonda
- first_name: Haiming
full_name: Liu, Haiming
last_name: Liu
- first_name: Luis-Daniel
full_name: Ibáñez, Luis-Daniel
last_name: Ibáñez
- first_name: Rezvaneh
full_name: Rezapour, Rezvaneh
last_name: Rezapour
keyword:
- Large Language Model Mediation
- Explainable AI
- Decision Co- Pilot Systems
- Misinformation Detection
language:
- iso: eng
page: 110-116
place: New York, USA
publication: 'WebSci Companion ''26: Companion Publication of the 2026 18th ACM Web
Science Conference'
publication_identifier:
isbn:
- 979-8-4007-2492-3
publication_status: published
publisher: ACM
quality_controlled: '1'
status: public
title: 'LLM-Mediated XAI Explanations: An AI Advisor for Fast and Calibrated Judgments
on Potential Misinformation'
type: conference_editor_article
user_id: '89807'
year: '2026'
...
---
_id: '12383'
abstract:
- lang: eng
text: Data stories are about revealing and communicating insights from complex data.
In this paper, we propose conversational data stories, which support end users
in understanding the key findings of the data analysis at hand by natural language
conversation. Creating these stories manually means to put a lot of effort into
understanding the data and crafting visuals. With increasingly powerful generative
large language models (LLMs), natural language processing as well as automating
the creation of data stories is a promising field. We present a concept for a
conversational data storytelling system that integrates LLMs as well as explainable
AI. We present the collected requirements for our system concept and how the requirements
are addressed. To show the potential of our approach, we provide a use case scenario
and a discussion in this paper. This is supposed to serve as a basis for future
research that will aim at investigating the technical reliability and the user
experience of such a system.
author:
- first_name: Valentin
full_name: Grimm, Valentin
id: '74000'
last_name: Grimm
- first_name: Jessica
full_name: Rubart, Jessica
id: '45672'
last_name: Rubart
orcid: 0000-0003-0937-3551
- first_name: Patrick
full_name: Söhlke, Patrick
last_name: Söhlke
citation:
ama: Grimm V, Rubart J, Söhlke P. Conversational Data Stories. (Atzenbeck
C, Rubart J, ACM, eds.). ACM; 2024:6. doi:10.1145/3679058.3688631
apa: Grimm, V., Rubart, J., & Söhlke, P. (2024). Conversational Data Stories.
In C. Atzenbeck, J. Rubart, & ACM (Eds.), Proceedings of the 7th Workshop
on Human Factors in Hypertext (HUMAN’24) (p. 6). ACM. https://doi.org/10.1145/3679058.3688631
bjps: 'Grimm V, Rubart J and Söhlke P (2024) Conversational Data Stories,
Atzenbeck C, Rubart J, and ACM (eds). New York: ACM.'
chicago: 'Grimm, Valentin, Jessica Rubart, and Patrick Söhlke. Conversational
Data Stories. Edited by Claus Atzenbeck, Jessica Rubart, and ACM. Proceedings
of the 7th Workshop on Human Factors in Hypertext (HUMAN’24). New York: ACM,
2024. https://doi.org/10.1145/3679058.3688631.'
chicago-de: 'Grimm, Valentin, Jessica Rubart und Patrick Söhlke. 2024. Conversational
Data Stories. Hg. von Claus Atzenbeck, Jessica Rubart, und ACM. Proceedings
of the 7th Workshop on Human Factors in Hypertext (HUMAN’24). New York: ACM.
doi:10.1145/3679058.3688631,
.'
din1505-2-1: 'Grimm, Valentin ; Rubart, Jessica ; Söhlke,
Patrick ; Atzenbeck, C. ;
Rubart, J. ; ACM
(Hrsg.): Conversational Data Stories. New York : ACM, 2024'
havard: V. Grimm, J. Rubart, P. Söhlke, Conversational Data Stories, ACM, New York,
2024.
ieee: 'V. Grimm, J. Rubart, and P. Söhlke, Conversational Data Stories. New
York: ACM, 2024, p. 6. doi: 10.1145/3679058.3688631.'
mla: Grimm, Valentin, et al. “Conversational Data Stories.” Proceedings of the
7th Workshop on Human Factors in Hypertext (HUMAN’24), edited by Claus Atzenbeck
et al., ACM, 2024, p. 6, https://doi.org/10.1145/3679058.3688631.
short: V. Grimm, J. Rubart, P. Söhlke, Conversational Data Stories, ACM, New York,
2024.
ufg: 'Grimm, Valentin/Rubart, Jessica/Söhlke, Patrick: Conversational Data
Stories, hg. von Atzenbeck, Claus/Rubart, Jessica, ACM, New York 2024.'
van: 'Grimm V, Rubart J, Söhlke P. Conversational Data Stories. Atzenbeck C, Rubart
J, ACM, editors. Proceedings of the 7th Workshop on Human Factors in Hypertext
(HUMAN’24). New York: ACM; 2024.'
conference:
end_date: 2024-09-13
location: Poznan Poland
name: 7th Workshop on Human Factors in Hypertext (HUMAN)
start_date: 2024-09-10
corporate_editor:
- ACM
date_created: 2025-01-21T13:23:17Z
date_updated: 2026-07-02T10:24:17Z
department:
- _id: DEP8008
doi: 10.1145/3679058.3688631
editor:
- first_name: Claus
full_name: Atzenbeck, Claus
last_name: Atzenbeck
- first_name: Jessica
full_name: Rubart, Jessica
id: '45672'
last_name: Rubart
orcid: 0000-0003-0937-3551
keyword:
- Data Storytelling
- Conversational Assistant
- Conversational Data Storytelling
- Explainable AI
language:
- iso: eng
page: '6'
place: New York
publication: Proceedings of the 7th Workshop on Human Factors in Hypertext (HUMAN'24)
publication_identifier:
isbn:
- 979-8-4007-1120-6
publication_status: published
publisher: ACM
status: public
title: Conversational Data Stories
type: conference_editor_article
user_id: '89807'
year: '2024'
...
---
_id: '12689'
author:
- first_name: Benedikt
full_name: Latos, Benedikt
id: '84474'
last_name: Latos
- first_name: Daniela
full_name: Becks, Daniela
last_name: Becks
- first_name: Antoine
full_name: Gaillard, Antoine
last_name: Gaillard
- first_name: Martin
full_name: Perau, Martin
last_name: Perau
- first_name: 'Bernd '
full_name: 'Respondek, Bernd '
last_name: Respondek
- first_name: 'Michael '
full_name: 'Kranz, Michael '
last_name: Kranz
- first_name: 'Jan '
full_name: 'Kukulies, Jan '
last_name: Kukulies
- first_name: 'Christian '
full_name: 'Kruse, Christian '
last_name: Kruse
citation:
ama: Latos B, Becks D, Gaillard A, et al. Integration of Generative AI into a
Tool to Assist Participatory ESG Double Materiality Assessment for SMEs. (Humphreys
D, Common Ground Research Networks, eds.). University of Aveiro; 2024.
apa: Latos, B., Becks, D., Gaillard, A., Perau, M., Respondek, B., Kranz, M., Kukulies,
J., & Kruse, C. (2024). Integration of Generative AI into a tool to assist
participatory ESG double materiality assessment for SMEs. In D. Humphreys &
Common Ground Research Networks (Eds.), Twentieth International Conference
on Environmental, Cultural, Economic & Social Sustainability Conference Proceedings.
University of Aveiro.
bjps: 'Latos B et al. (2024) Integration of Generative AI into
a Tool to Assist Participatory ESG Double Materiality Assessment for SMEs,
Humphreys D and Common Ground Research Networks (eds). Aveiro: University of Aveiro.'
chicago: 'Latos, Benedikt, Daniela Becks, Antoine Gaillard, Martin Perau, Bernd Respondek,
Michael Kranz, Jan Kukulies, and Christian Kruse. Integration of Generative
AI into a Tool to Assist Participatory ESG Double Materiality Assessment for SMEs.
Edited by David Humphreys and Common Ground Research Networks. Twentieth International
Conference on Environmental, Cultural, Economic & Social Sustainability Conference
Proceedings. On Sustainability. Aveiro: University of Aveiro, 2024.'
chicago-de: 'Latos, Benedikt, Daniela Becks, Antoine Gaillard, Martin Perau, Bernd Respondek,
Michael Kranz, Jan Kukulies und Christian Kruse. 2024. Integration of Generative
AI into a tool to assist participatory ESG double materiality assessment for SMEs.
Hg. von David Humphreys und Common Ground Research Networks. Twentieth International
Conference on Environmental, Cultural, Economic & Social Sustainability Conference
Proceedings. On Sustainability. Aveiro: University of Aveiro.'
din1505-2-1: 'Latos, Benedikt ; Becks, Daniela ; Gaillard,
Antoine ; Perau, Martin ;
Respondek, Bernd ; Kranz,
Michael ; Kukulies, Jan
; Kruse, Christian ; Humphreys,
D. ; Common Ground Research Networks
(Hrsg.): Integration of Generative AI into a tool to assist participatory ESG
double materiality assessment for SMEs, On Sustainability. Aveiro :
University of Aveiro, 2024'
havard: B. Latos, D. Becks, A. Gaillard, M. Perau, B. Respondek, M. Kranz, J. Kukulies,
C. Kruse, Integration of Generative AI into a tool to assist participatory ESG
double materiality assessment for SMEs, University of Aveiro, Aveiro, 2024.
ieee: 'B. Latos et al., Integration of Generative AI into a tool to assist
participatory ESG double materiality assessment for SMEs. Aveiro: University
of Aveiro, 2024.'
mla: Latos, Benedikt, et al. “Integration of Generative AI into a Tool to Assist
Participatory ESG Double Materiality Assessment for SMEs.” Twentieth International
Conference on Environmental, Cultural, Economic & Social Sustainability Conference
Proceedings, edited by David Humphreys and Common Ground Research Networks,
University of Aveiro, 2024.
short: B. Latos, D. Becks, A. Gaillard, M. Perau, B. Respondek, M. Kranz, J. Kukulies,
C. Kruse, Integration of Generative AI into a Tool to Assist Participatory ESG
Double Materiality Assessment for SMEs, University of Aveiro, Aveiro, 2024.
ufg: 'Latos, Benedikt u. a.: Integration of Generative AI into a tool to
assist participatory ESG double materiality assessment for SMEs, hg. von Humphreys,
David, Common Ground Research Networks, Aveiro 2024 (On Sustainability).'
van: 'Latos B, Becks D, Gaillard A, Perau M, Respondek B, Kranz M, et al. Integration
of Generative AI into a tool to assist participatory ESG double materiality assessment
for SMEs. Humphreys D, Common Ground Research Networks, editors. Twentieth International
Conference on Environmental, Cultural, Economic & Social Sustainability Conference
Proceedings. Aveiro: University of Aveiro; 2024. (On Sustainability).'
conference:
end_date: 2024-01-26
location: Aveiro, Portugal
name: International Conference on Environmental, Cultural, Economic & Social Sustainability
University of Aveiro
start_date: 2024-01-24
corporate_editor:
- Common Ground Research Networks
date_created: 2025-03-11T11:55:12Z
date_updated: 2025-03-24T15:34:17Z
ddc:
- '330'
department:
- _id: DEP1500
editor:
- first_name: 'David '
full_name: 'Humphreys, David '
last_name: Humphreys
has_accepted_license: '1'
keyword:
- ESG
- AI
- SME
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.researchgate.net/publication/378144238_Integration_of_Generative_AI_into_a_tool_to_assist_participatory_ESG_double_materiality_assessment_for_SMEs?enrichId=rgreq-0160db4d253d366b90e49aaa0f00dea2-XXX&enrichSource=Y292ZXJQYWdlOzM3ODE0NDIzODtBUzoxMTQzMTI4MTIyMzQ0MzQ3MkAxNzA3NzI5MzY3NTI4&el=1_x_2&_esc=publicationCoverPdf
oa: '1'
place: Aveiro
publication: Twentieth International Conference on Environmental, Cultural, Economic
& Social Sustainability Conference Proceedings
publication_identifier:
eisbn:
- 978-1-963049-28-2
isbn:
- 978-1-963049-41-1
publication_status: published
publisher: University of Aveiro
series_title: On Sustainability
status: public
title: Integration of Generative AI into a tool to assist participatory ESG double
materiality assessment for SMEs
type: conference_editor_article
user_id: '83781'
year: '2024'
...
---
_id: '13169'
abstract:
- lang: eng
text: "KI.BAU is a project being developed and conducted at the Detmold School of
Design, part of the University of Applied Sciences and Arts Ostwestfalen-Lippe.
It focuses on researching the application of artificial intelligence (AI) in architectural
design, modelling, production and management processes, particularly on the communication
between users, processes and the building itself in various development and life-time
phases. Hence the research aims to develop new tools and AI-supported process
chains for the design, production and communication of architecture. This includes
the training and implementing prototypical machine learning algorithms to autonomously
evolve and optimize field-specific processes and workflows.\r\nAs mentioned above,
a critical question KI.BAU explores is how we, as planners, builders and users,
will communicate with architecture in the future, in its phases of creation and
use but also beyond. This also involves, besides virtual interfaces, examining
the physical interaction with a building, its behaviour, responsiveness and adaptation
to certain conditions. \r\nThe primary goal of the research at KI.BAU is to transform
architecture into an intelligent, to some degree self-sustaining, self-reflective
and maybe even evolving ‘ecological system’. This system should be comprehensively
linked with its creators, users, devices, computers, its (biological) environment
and networks. Consequently, a building must be viewed as an organism that communicates,
interacts and adapts to other connected or related organisms and entities.\r\n"
author:
- first_name: Hans
full_name: Sachs, Hans
id: '64589'
last_name: Sachs
citation:
ama: 'Sachs H. KI.BAU Artificial Intelligence in Architecture. In: Kretzer M, AADR
– Art Architecture Design Research, eds. Synthetic Realities: New Frontiers
in AI-Driven Design, Fabrication and Materiality. 1. AADR – Art Architecture
Design Research; 2024:14.'
apa: 'Sachs, H. (2024). KI.BAU Artificial Intelligence in Architecture. In M. Kretzer
& AADR – Art Architecture Design Research (Eds.), Synthetic realities:
New Frontiers in AI-driven Design, Fabrication and Materiality (1., p. 14).
AADR – Art Architecture Design Research.'
bjps: 'Sachs H (2024) KI.BAU Artificial Intelligence in Architecture. In
Kretzer M and AADR – Art Architecture Design Research (eds), Synthetic Realities:
New Frontiers in AI-Driven Design, Fabrication and Materiality, 1. Baunach:
AADR – Art Architecture Design Research, p. 14.'
chicago: 'Sachs, Hans. “KI.BAU Artificial Intelligence in Architecture.” In Synthetic
Realities: New Frontiers in AI-Driven Design, Fabrication and Materiality,
edited by Manuel Kretzer and AADR – Art Architecture Design Research, 1., 14.
Baunach: AADR – Art Architecture Design Research, 2024.'
chicago-de: 'Sachs, Hans. 2024. KI.BAU Artificial Intelligence in Architecture.
In: Synthetic realities: New Frontiers in AI-driven Design, Fabrication and
Materiality, hg. von Manuel Kretzer und AADR – Art Architecture Design Research,
14. 1. Baunach: AADR – Art Architecture Design Research.'
din1505-2-1: 'Sachs, Hans: KI.BAU
Artificial Intelligence in Architecture. In: Kretzer,
M. ; AADR – Art Architecture Design
Research (Hrsg.): Synthetic realities: New Frontiers in AI-driven Design,
Fabrication and Materiality. 1. Baunach : AADR – Art Architecture Design Research,
2024, S. 14'
havard: 'H. Sachs, KI.BAU Artificial Intelligence in Architecture, in: M. Kretzer,
AADR – Art Architecture Design Research (Eds.), Synthetic Realities: New Frontiers
in AI-Driven Design, Fabrication and Materiality, 1., AADR – Art Architecture
Design Research, Baunach, 2024: p. 14.'
ieee: 'H. Sachs, “KI.BAU Artificial Intelligence in Architecture,” in Synthetic
realities: New Frontiers in AI-driven Design, Fabrication and Materiality,
1., M. Kretzer and AADR – Art Architecture Design Research, Eds. Baunach: AADR
– Art Architecture Design Research, 2024, p. 14.'
mla: 'Sachs, Hans. “KI.BAU Artificial Intelligence in Architecture.” Synthetic
Realities: New Frontiers in AI-Driven Design, Fabrication and Materiality,
edited by Manuel Kretzer and AADR – Art Architecture Design Research, 1., AADR
– Art Architecture Design Research, 2024, p. 14.'
short: 'H. Sachs, in: M. Kretzer, AADR – Art Architecture Design Research (Eds.),
Synthetic Realities: New Frontiers in AI-Driven Design, Fabrication and Materiality,
1., AADR – Art Architecture Design Research, Baunach, 2024, p. 14.'
ufg: 'Sachs, Hans: KI.BAU Artificial Intelligence in Architecture, in: Kretzer,
Manuel, AADR – Art Architecture Design Research (Hgg.): Synthetic realities:
New Frontiers in AI-driven Design, Fabrication and Materiality, 1.,
Baunach 2024, S. 14.'
van: 'Sachs H. KI.BAU Artificial Intelligence in Architecture. In: Kretzer M, AADR
– Art Architecture Design Research, editors. Synthetic realities: New Frontiers
in AI-driven Design, Fabrication and Materiality. 1. Baunach: AADR – Art Architecture
Design Research; 2024. p. 14.'
corporate_editor:
- AADR – Art Architecture Design Research
date_created: 2025-09-11T10:50:08Z
date_updated: 2025-10-16T20:54:48Z
department:
- _id: DEP1624
- _id: DEP1055
edition: '1.'
editor:
- first_name: Manuel
full_name: Kretzer, Manuel
last_name: Kretzer
jel:
- A31
keyword:
- AI
- Artificial Intelligence
- Architecture
- Build Environment
- Building Construction
- Ecology of Architecture
language:
- iso: eng
page: '14'
place: Baunach
popular_science: '1'
publication: 'Synthetic realities: New Frontiers in AI-driven Design, Fabrication
and Materiality'
publication_identifier:
isbn:
- 978-3887781088
publication_status: published
publisher: AADR – Art Architecture Design Research
related_material:
link:
- relation: new_edition
url: https://aadr.info/product/synthetic-realities/
status: public
title: KI.BAU Artificial Intelligence in Architecture
type: book_chapter
user_id: '64589'
year: '2024'
...
---
_id: '13786'
abstract:
- lang: eng
text: Due to the superior job performing abilities and increasing computational
capabilities, collaborating with artificial-intelligence-based services (AIBS
or AI-based services) will be inevitable for employees in the service context.
AI-based services in the form of virtual (e.g., chatbot) or physical (e.g., service
robot) embodiments, which are characterized by a higher degree of autonomy and
are intended to augment the tasks of human employees in a highly collaborative
way, will increasingly become an integral part of employee’s work environment.
Semi-structured interviews and a focus group discussion have been used to identify
constructs driving employees’ perception of AI-based services and their impact
on wellbeing. Combined with a thorough literature analysis, relations between
the identified constructs have been derived from introducing a conceptual model
of employees’ willingness to collaborate (WTC). This study identifies technology
characteristics, job demands, resources, and control as constructs, directly influencing
employees’ perceived risk of AI-based services.
author:
- first_name: Stefanie
full_name: Paluch, Stefanie
last_name: Paluch
- first_name: Thomas
full_name: Wittkop, Thomas
id: '61636'
last_name: Wittkop
citation:
ama: 'Paluch S, Wittkop T. Role of Risk on Employees’ Willingness to Collaborate
with Artificial Intelligence and its Impact on Wellbeing. In: Sheth JN, Jain V,
Mogaji E, Ambika A, eds. Artificial Intelligence in Customer Service : The
Next Frontier for Personalized Engagement . Springer International Publishing
AG; 2023:281-302. doi:10.1007/978-3-031-33898-4_12'
apa: 'Paluch, S., & Wittkop, T. (2023). Role of Risk on Employees’ Willingness
to Collaborate with Artificial Intelligence and its Impact on Wellbeing. In J.
N. Sheth, V. Jain, E. Mogaji, & A. Ambika (Eds.), Artificial Intelligence
in Customer Service : The Next Frontier for Personalized Engagement (pp.
281–302). Springer International Publishing AG. https://doi.org/10.1007/978-3-031-33898-4_12'
bjps: 'Paluch S and Wittkop T (2023) Role of Risk on Employees’ Willingness
to Collaborate with Artificial Intelligence and Its Impact on Wellbeing. In Sheth
JN et al. (eds), Artificial Intelligence in Customer Service : The Next Frontier
for Personalized Engagement . Cham: Springer International Publishing AG,
pp. 281–302.'
chicago: 'Paluch, Stefanie, and Thomas Wittkop. “Role of Risk on Employees’ Willingness
to Collaborate with Artificial Intelligence and Its Impact on Wellbeing.” In Artificial
Intelligence in Customer Service : The Next Frontier for Personalized Engagement
, edited by Jagdish N. Sheth, Varsha Jain, Emmanuel Mogaji, and Anupama Ambika,
281–302. Cham: Springer International Publishing AG, 2023. https://doi.org/10.1007/978-3-031-33898-4_12.'
chicago-de: 'Paluch, Stefanie und Thomas Wittkop. 2023. Role of Risk on Employees’
Willingness to Collaborate with Artificial Intelligence and its Impact on Wellbeing.
In: Artificial Intelligence in Customer Service : The Next Frontier for Personalized
Engagement , hg. von Jagdish N. Sheth, Varsha Jain, Emmanuel Mogaji, und
Anupama Ambika, 281–302. Cham: Springer International Publishing AG. doi:10.1007/978-3-031-33898-4_12,
.'
din1505-2-1: 'Paluch, Stefanie ; Wittkop, Thomas: Role of Risk on Employees’
Willingness to Collaborate with Artificial Intelligence and its Impact on Wellbeing.
In: Sheth, J. N. ; Jain,
V. ; Mogaji, E. ; Ambika,
A. (Hrsg.): Artificial Intelligence in Customer Service : The Next Frontier
for Personalized Engagement . Cham : Springer International Publishing AG,
2023, S. 281–302'
havard: 'S. Paluch, T. Wittkop, Role of Risk on Employees’ Willingness to Collaborate
with Artificial Intelligence and its Impact on Wellbeing, in: J.N. Sheth, V. Jain,
E. Mogaji, A. Ambika (Eds.), Artificial Intelligence in Customer Service : The
Next Frontier for Personalized Engagement , Springer International Publishing
AG, Cham, 2023: pp. 281–302.'
ieee: 'S. Paluch and T. Wittkop, “Role of Risk on Employees’ Willingness to Collaborate
with Artificial Intelligence and its Impact on Wellbeing,” in Artificial Intelligence
in Customer Service : The Next Frontier for Personalized Engagement , J. N.
Sheth, V. Jain, E. Mogaji, and A. Ambika, Eds. Cham: Springer International Publishing
AG, 2023, pp. 281–302. doi: 10.1007/978-3-031-33898-4_12.'
mla: 'Paluch, Stefanie, and Thomas Wittkop. “Role of Risk on Employees’ Willingness
to Collaborate with Artificial Intelligence and Its Impact on Wellbeing.” Artificial
Intelligence in Customer Service : The Next Frontier for Personalized Engagement
, edited by Jagdish N. Sheth et al., Springer International Publishing AG,
2023, pp. 281–302, https://doi.org/10.1007/978-3-031-33898-4_12.'
short: 'S. Paluch, T. Wittkop, in: J.N. Sheth, V. Jain, E. Mogaji, A. Ambika (Eds.),
Artificial Intelligence in Customer Service : The Next Frontier for Personalized
Engagement , Springer International Publishing AG, Cham, 2023, pp. 281–302.'
ufg: 'Paluch, Stefanie/Wittkop, Thomas: Role of Risk on Employees’ Willingness
to Collaborate with Artificial Intelligence and its Impact on Wellbeing, in: Sheth,
Jagdish N. u. a. (Hgg.): Artificial Intelligence in Customer Service : The
Next Frontier for Personalized Engagement , Cham 2023, S. 281–302.'
van: 'Paluch S, Wittkop T. Role of Risk on Employees’ Willingness to Collaborate
with Artificial Intelligence and its Impact on Wellbeing. In: Sheth JN, Jain V,
Mogaji E, Ambika A, editors. Artificial Intelligence in Customer Service : The
Next Frontier for Personalized Engagement . Cham: Springer International Publishing
AG; 2023. p. 281–302.'
date_created: 2026-05-26T17:34:27Z
date_updated: 2026-05-27T12:09:44Z
department:
- _id: DEP3019
doi: 10.1007/978-3-031-33898-4_12
editor:
- first_name: Jagdish N.
full_name: Sheth, Jagdish N.
last_name: Sheth
- first_name: 'Varsha '
full_name: 'Jain, Varsha '
last_name: Jain
- first_name: 'Emmanuel '
full_name: 'Mogaji, Emmanuel '
last_name: Mogaji
- first_name: 'Anupama '
full_name: 'Ambika, Anupama '
last_name: Ambika
keyword:
- Artificial intelligence
- AI-based services
- Willingness to collaborate
- Employees’ wellbeing
language:
- iso: eng
page: 281–302
place: Cham
publication: 'Artificial Intelligence in Customer Service : The Next Frontier for
Personalized Engagement '
publication_identifier:
eisbn:
- '978-3-031-33898-4 '
isbn:
- 978-3-031-33897-7
publication_status: published
publisher: Springer International Publishing AG
status: public
title: Role of Risk on Employees’ Willingness to Collaborate with Artificial Intelligence
and its Impact on Wellbeing
type: book_chapter
user_id: '83781'
year: '2023'
...
---
_id: '10935'
abstract:
- lang: eng
text: One of the challenges in universities is to take into account the different
competences of students throughout the process of imparting knowledge. It is unlikely
that all students will grasp the course content in the same way, as they have
different abilities. Similarly, it is unrealistic for teachers to address all
the individual needs of each student at all times. In addition, maintaining learners'
attention to a particular topic is also an essential part of teaching. To overcome
these challenges, we are developing AI learning software as part of a research
project. The software generates learning scenarios for the students and takes
their individual competences into account. The research project focuses on the
field of automation technology, especially on programming, as programming skills
are usually required in automation environments. When solving the scenarios, students
receive immediate feedback on how well they have solved the task. Immediate automated
feedback not only meets the students' expectations of quick learning feedback,
but it also relieves the teaching staff in the assessment process. In addition,
the software includes an interactive user interface that allows learners to see
the results of their programming tasks in a simulated 3D environment. This approach
aims to maintain learners' attention over a longer learning period. This paper
describes the above aspects that are being developed in the research project and
previews the new learning opportunities that could arise from the use of AI.
author:
- first_name: Asmar
full_name: Ali, Asmar
id: '78685'
last_name: Ali
- first_name: Andreas
full_name: Deuter, Andreas
id: '62088'
last_name: Deuter
orcid: 0000-0002-6529-6215
citation:
ama: 'Ali A, Deuter A. An AI Assistant for Education in Automation. Journal of
international scientific publications / Science & Education Foundation : Educational
Alternatives . 2023;21:12-20. doi:10.62991/EA1996108906'
apa: 'Ali, A., & Deuter, A. (2023). An AI Assistant for Education in Automation.
Journal of International Scientific Publications / Science & Education
Foundation : Educational Alternatives , 21, 12–20. https://doi.org/10.62991/EA1996108906'
bjps: 'Ali A and Deuter A (2023) An AI Assistant for Education in Automation.
Journal of international scientific publications / Science & Education
Foundation : Educational Alternatives 21, 12–20.'
chicago: 'Ali, Asmar, and Andreas Deuter. “An AI Assistant for Education in Automation.”
Journal of International Scientific Publications / Science & Education
Foundation : Educational Alternatives 21 (2023): 12–20. https://doi.org/10.62991/EA1996108906.'
chicago-de: 'Ali, Asmar und Andreas Deuter. 2023. An AI Assistant for Education
in Automation. Journal of international scientific publications / Science &
Education Foundation : Educational Alternatives 21: 12–20. doi:10.62991/EA1996108906,
.'
din1505-2-1: 'Ali, Asmar ; Deuter,
Andreas: An AI Assistant for Education in Automation. In: Journal of
international scientific publications / Science & Education Foundation : Educational
Alternatives Bd. 21. [Erscheinungsort nicht ermittelbar], Info Invest (2023),
S. 12–20'
havard: 'A. Ali, A. Deuter, An AI Assistant for Education in Automation, Journal
of International Scientific Publications / Science & Education Foundation :
Educational Alternatives . 21 (2023) 12–20.'
ieee: 'A. Ali and A. Deuter, “An AI Assistant for Education in Automation,” Journal
of international scientific publications / Science & Education Foundation :
Educational Alternatives , vol. 21, pp. 12–20, 2023, doi: 10.62991/EA1996108906.'
mla: 'Ali, Asmar, and Andreas Deuter. “An AI Assistant for Education in Automation.”
Journal of International Scientific Publications / Science & Education
Foundation : Educational Alternatives , vol. 21, 2023, pp. 12–20, https://doi.org/10.62991/EA1996108906.'
short: 'A. Ali, A. Deuter, Journal of International Scientific Publications / Science
& Education Foundation : Educational Alternatives 21 (2023) 12–20.'
ufg: 'Ali, Asmar/Deuter, Andreas: An AI Assistant for Education in Automation,
in: Journal of international scientific publications / Science & Education
Foundation : Educational Alternatives 21 (2023), S. 12–20.'
van: 'Ali A, Deuter A. An AI Assistant for Education in Automation. Journal of international
scientific publications / Science & Education Foundation : Educational Alternatives
. 2023;21:12–20.'
conference:
end_date: 2023-08-26
location: Burgas
name: 14th International Conference Education, Research & Development
start_date: 2023-08-24
date_created: 2024-01-09T13:25:08Z
date_updated: 2026-07-06T08:12:41Z
department:
- _id: DEP7022
- _id: DEP1306
doi: 10.62991/EA1996108906
intvolume: ' 21'
keyword:
- ai education
- automated feedback
- automation education
- educational software
- programming
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.scientific-publications.net/en/article/1002566/
oa: '1'
page: 12-20
place: '[Erscheinungsort nicht ermittelbar]'
publication: 'Journal of international scientific publications / Science & Education
Foundation : Educational Alternatives '
publication_identifier:
issn:
- 1313-2571
publication_status: published
publisher: 'Info Invest '
status: public
title: An AI Assistant for Education in Automation
type: industry_journal_article
user_id: '83781'
volume: 21
year: '2023'
...
---
_id: '12994'
abstract:
- lang: eng
text: HUMAN 2023 is the 6th workshop of a series for the ACM Hypertext conferences.
The HUMAN workshop has a strong focus on the user and thus is complementary to
the strong machine analytics research direction that could be experienced in previous
conferences.The user-centric view on hypertext not only includes user interfaces
and interaction, but also discussions about hypertext application domains as well
as human-centered AI. Furthermore, the workshop raises the question of how original
hypertext ideas (e. g., Doug Engelbart’s "augmenting human intellect" [7] or Jeff
Conklin’s "hypertext as a computer-based medium for thinking and communication"
[6]) can improve today’s hypertext systems.
author:
- first_name: Jessica
full_name: Rubart, Jessica
id: '45672'
last_name: Rubart
orcid: 0000-0003-0937-3551
- first_name: Claus
full_name: Atzenbeck, Claus
last_name: Atzenbeck
citation:
ama: 'Rubart J, Atzenbeck C. HUMAN’23: 6th Workshop on Human Factors in Hypertext.
ACM; 2023. doi:10.1145/3603163.3610576'
apa: 'Rubart, J., & Atzenbeck, C. (2023). HUMAN’23: 6th Workshop on Human Factors
in Hypertext. In Proceedings of the 34th ACM Conference on Hypertext and Social
Media. 34th ACM Conference on Hypertext and Social Media, Rome, Italy. ACM.
https://doi.org/10.1145/3603163.3610576'
bjps: 'Rubart J and Atzenbeck C (2023) HUMAN’23: 6th Workshop on Human
Factors in Hypertext. New York, NY, USA: ACM.'
chicago: 'Rubart, Jessica, and Claus Atzenbeck. HUMAN’23: 6th Workshop on Human
Factors in Hypertext. Proceedings of the 34th ACM Conference on Hypertext
and Social Media. HT ’23. New York, NY, USA: ACM, 2023. https://doi.org/10.1145/3603163.3610576.'
chicago-de: 'Rubart, Jessica und Claus Atzenbeck. 2023. HUMAN’23: 6th Workshop
on Human Factors in Hypertext. Proceedings of the 34th ACM Conference on
Hypertext and Social Media. HT ’23. New York, NY, USA: ACM. doi:10.1145/3603163.3610576,
.'
din1505-2-1: 'Rubart, Jessica ; Atzenbeck, Claus: HUMAN’23: 6th Workshop
on Human Factors in Hypertext, HT ’23. New York, NY, USA : ACM, 2023'
havard: 'J. Rubart, C. Atzenbeck, HUMAN’23: 6th Workshop on Human Factors in Hypertext,
ACM, New York, NY, USA, 2023.'
ieee: 'J. Rubart and C. Atzenbeck, HUMAN’23: 6th Workshop on Human Factors in
Hypertext. New York, NY, USA: ACM, 2023. doi: 10.1145/3603163.3610576.'
mla: 'Rubart, Jessica, and Claus Atzenbeck. “HUMAN’23: 6th Workshop on Human Factors
in Hypertext.” Proceedings of the 34th ACM Conference on Hypertext and Social
Media, ACM, 2023, https://doi.org/10.1145/3603163.3610576.'
short: 'J. Rubart, C. Atzenbeck, HUMAN’23: 6th Workshop on Human Factors in Hypertext,
ACM, New York, NY, USA, 2023.'
ufg: 'Rubart, Jessica/Atzenbeck, Claus: HUMAN’23: 6th Workshop on Human Factors
in Hypertext, New York, NY, USA 2023 (HT ’23).'
van: 'Rubart J, Atzenbeck C. HUMAN’23: 6th Workshop on Human Factors in Hypertext.
Proceedings of the 34th ACM Conference on Hypertext and Social Media. New York,
NY, USA: ACM; 2023. (HT ’23).'
conference:
end_date: 2023-09-08
location: Rome, Italy
name: 34th ACM Conference on Hypertext and Social Media
start_date: 2023-09-04
date_created: 2025-06-18T13:24:37Z
date_updated: 2026-07-02T10:26:18Z
department:
- _id: DEP5023
- _id: DEP8008
doi: 10.1145/3603163.3610576
keyword:
- user interfaces
- information structuring
- decision making
- human-centered AI
- cognitive aspects
- scientific community
- digital humanities
- user interaction
- human factors
- user-centric
- annotation
- adaptive hypertext
- hypermedia
- collaboration
- information systems
- augmentation
- hypertext
- communication
- intercultural aspects
language:
- iso: eng
place: New York, NY, USA
publication: Proceedings of the 34th ACM Conference on Hypertext and Social Media
publication_identifier:
isbn:
- 979-8-4007-0232-7
publication_status: published
publisher: ACM
series_title: HT '23
status: public
title: 'HUMAN’23: 6th Workshop on Human Factors in Hypertext'
type: conference_editor_article
user_id: '89807'
year: '2023'
...
---
_id: '13020'
abstract:
- lang: eng
text: Developing AI systems for automatic train operation (ATO) requires developers
to have a deep understanding of the human tasks they are trying to replace. This
paper fills this gap and translates the regulatory requirements from the context
of German railways for the AI developer community. As a result, tasks such as
train’s path monitoring for collision prediction, signal detection, door operation,
etc. are identified. Based on this analysis, a functionally justified sensor setup
with detailed configuration requirements is presented. This setup was also evaluated
by a survey within the railway industry. The evaluated sensors include RGB/IR
cameras, LIDARs, radars and ultrasonic sensors. Calculations and estimates for
the evaluated sensors are presented graphically and included in this paper. However,
the ultimate sensor setup is still a subject of research. The results of this
paper also address the lack of training and test datasets for railway AI systems.
It is proposed to acquire research datasets that will allow the training of domain
adaptation algorithms to transform other datasets, thus increasing the number
of available datasets. The sensor setup is also recommended for such research
datasets.
article_number: '22'
author:
- first_name: Rustam
full_name: Tagiew, Rustam
last_name: Tagiew
- first_name: Dirk
full_name: Leinhos, Dirk
last_name: Leinhos
- first_name: Henrik
full_name: von der Haar, Henrik
last_name: von der Haar
- first_name: Christian
full_name: Klotz, Christian
last_name: Klotz
- first_name: Dennis
full_name: Sprute, Dennis
last_name: Sprute
- first_name: Jens
full_name: Ziehn, Jens
last_name: Ziehn
- first_name: Andreas
full_name: Schmelter, Andreas
id: '10982'
last_name: Schmelter
- first_name: Stefan
full_name: Witte, Stefan
id: '1605'
last_name: Witte
- first_name: Pavel
full_name: Klasek, Pavel
last_name: Klasek
citation:
ama: Tagiew R, Leinhos D, von der Haar H, et al. Sensor system for development of
perception systems for ATO. Discover Artificial Intelligence. 2023;3(1).
doi:10.1007/s44163-023-00066-4
apa: Tagiew, R., Leinhos, D., von der Haar, H., Klotz, C., Sprute, D., Ziehn, J.,
Schmelter, A., Witte, S., & Klasek, P. (2023). Sensor system for development
of perception systems for ATO. Discover Artificial Intelligence, 3(1),
Article 22. https://doi.org/10.1007/s44163-023-00066-4
bjps: Tagiew R et al. (2023) Sensor System for Development of Perception
Systems for ATO. Discover Artificial Intelligence 3.
chicago: Tagiew, Rustam, Dirk Leinhos, Henrik von der Haar, Christian Klotz, Dennis
Sprute, Jens Ziehn, Andreas Schmelter, Stefan Witte, and Pavel Klasek. “Sensor
System for Development of Perception Systems for ATO.” Discover Artificial
Intelligence 3, no. 1 (2023). https://doi.org/10.1007/s44163-023-00066-4.
chicago-de: Tagiew, Rustam, Dirk Leinhos, Henrik von der Haar, Christian Klotz,
Dennis Sprute, Jens Ziehn, Andreas Schmelter, Stefan Witte und Pavel Klasek. 2023.
Sensor system for development of perception systems for ATO. Discover Artificial
Intelligence 3, Nr. 1. doi:10.1007/s44163-023-00066-4,
.
din1505-2-1: 'Tagiew,
Rustam ; Leinhos, Dirk ;
von der Haar, Henrik ; Klotz,
Christian ; Sprute, Dennis
; Ziehn, Jens ; Schmelter,
Andreas ; Witte, Stefan ;
u. a.: Sensor system for development of perception systems for ATO. In:
Discover Artificial Intelligence Bd. 3. [Cham] , Springer International
Publishing (2023), Nr. 1'
havard: R. Tagiew, D. Leinhos, H. von der Haar, C. Klotz, D. Sprute, J. Ziehn, A.
Schmelter, S. Witte, P. Klasek, Sensor system for development of perception systems
for ATO, Discover Artificial Intelligence. 3 (2023).
ieee: 'R. Tagiew et al., “Sensor system for development of perception systems
for ATO,” Discover Artificial Intelligence, vol. 3, no. 1, Art. no. 22,
2023, doi: 10.1007/s44163-023-00066-4.'
mla: Tagiew, Rustam, et al. “Sensor System for Development of Perception Systems
for ATO.” Discover Artificial Intelligence, vol. 3, no. 1, 22, 2023, https://doi.org/10.1007/s44163-023-00066-4.
short: R. Tagiew, D. Leinhos, H. von der Haar, C. Klotz, D. Sprute, J. Ziehn, A.
Schmelter, S. Witte, P. Klasek, Discover Artificial Intelligence 3 (2023).
ufg: 'Tagiew, Rustam u. a.: Sensor system for development of perception systems
for ATO, in: Discover Artificial Intelligence 3 (2023), H. 1.'
van: Tagiew R, Leinhos D, von der Haar H, Klotz C, Sprute D, Ziehn J, et al. Sensor
system for development of perception systems for ATO. Discover Artificial Intelligence.
2023;3(1).
date_created: 2025-06-24T13:47:12Z
date_updated: 2025-06-24T13:51:24Z
department:
- _id: DEP5000
- _id: DEP5023
doi: 10.1007/s44163-023-00066-4
intvolume: ' 3'
issue: '1'
keyword:
- Automatic train operation
- ATO
- GoA3
- GoA4
- Perception
- AI
language:
- iso: eng
place: '[Cham] '
publication: Discover Artificial Intelligence
publication_identifier:
issn:
- 2731-0809
publication_status: published
publisher: 'Springer International Publishing '
quality_controlled: '1'
status: public
title: Sensor system for development of perception systems for ATO
type: scientific_journal_article
user_id: '83781'
volume: 3
year: '2023'
...
---
_id: '10645'
abstract:
- lang: eng
text: Artificial Intelligence (AI)-based applications promise great potential benefits
for companies. However, an isolated consideration of the technical system is not
sufficient for the design. Rather, it is necessary to design the entire work system
taking into account the socio-technical system approach. This enables the combination
of the strengths of people and intelligent systems. This paper presents an approach
for a socio-technical requirements elicitation in the design of AI-based systems
by adapting the HTO-analysis. First, a mission statement is developed. Based on
a detailed process modelling, existing data and systems are recorded. In addition,
all relevant stakeholder groups are included by conducting interviews and surveys.
Thus, the procedure enables the derivation of a comprehensive catalogue of requirements.
The application of the approach is illustrated by using an example from industrial
practice, the design of an intelligent workforce planning system.
author:
- first_name: Stefan
full_name: Gabriel, Stefan
last_name: Gabriel
- first_name: Dominik
full_name: Bentler, Dominik
last_name: Bentler
- first_name: Eva-Maria
full_name: Grote, Eva-Maria
last_name: Grote
- first_name: Caroline
full_name: Junker, Caroline
last_name: Junker
- first_name: David Meyer zu
full_name: Wendischhoff, David Meyer zu
last_name: Wendischhoff
- first_name: Michael
full_name: Bansmann, Michael
last_name: Bansmann
- first_name: Benedikt
full_name: Latos, Benedikt
last_name: Latos
- first_name: Daniela
full_name: Hobscheidt, Daniela
last_name: Hobscheidt
- first_name: Arno
full_name: Kühn, Arno
last_name: Kühn
- first_name: Roman
full_name: Dumitrescu, Roman
last_name: Dumitrescu
citation:
ama: 'Gabriel S, Bentler D, Grote EM, et al. Requirements analysis for an intelligent
workforce planning system: a socio-technical approach to design AI-based systems.
Procedia CIRP. 2022;109:431-436. doi:10.1016/j.procir.2022.05.274'
apa: 'Gabriel, S., Bentler, D., Grote, E.-M., Junker, C., Wendischhoff, D. M. zu,
Bansmann, M., Latos, B., Hobscheidt, D., Kühn, A., & Dumitrescu, R. (2022).
Requirements analysis for an intelligent workforce planning system: a socio-technical
approach to design AI-based systems. Procedia CIRP, 109, 431–436.
https://doi.org/10.1016/j.procir.2022.05.274'
bjps: 'Gabriel S et al. (2022) Requirements Analysis for an Intelligent
Workforce Planning System: A Socio-Technical Approach to Design AI-Based Systems.
Procedia CIRP 109, 431–436.'
chicago: 'Gabriel, Stefan, Dominik Bentler, Eva-Maria Grote, Caroline Junker, David
Meyer zu Wendischhoff, Michael Bansmann, Benedikt Latos, Daniela Hobscheidt, Arno
Kühn, and Roman Dumitrescu. “Requirements Analysis for an Intelligent Workforce
Planning System: A Socio-Technical Approach to Design AI-Based Systems.” Procedia
CIRP 109 (2022): 431–36. https://doi.org/10.1016/j.procir.2022.05.274.'
chicago-de: 'Gabriel, Stefan, Dominik Bentler, Eva-Maria Grote, Caroline Junker,
David Meyer zu Wendischhoff, Michael Bansmann, Benedikt Latos, Daniela Hobscheidt,
Arno Kühn und Roman Dumitrescu. 2022. Requirements analysis for an intelligent
workforce planning system: a socio-technical approach to design AI-based systems.
Procedia CIRP 109: 431–436. doi:10.1016/j.procir.2022.05.274,
.'
din1505-2-1: 'Gabriel,
Stefan ; Bentler, Dominik
; Grote, Eva-Maria ; Junker,
Caroline ; Wendischhoff, David Meyer
zu ; Bansmann, Michael ;
Latos, Benedikt ; Hobscheidt,
Daniela ; u. a.: Requirements analysis for an intelligent workforce
planning system: a socio-technical approach to design AI-based systems. In: Procedia
CIRP Bd. 109, Elsevier BV (2022), S. 431–436'
havard: 'S. Gabriel, D. Bentler, E.-M. Grote, C. Junker, D.M. zu Wendischhoff, M.
Bansmann, B. Latos, D. Hobscheidt, A. Kühn, R. Dumitrescu, Requirements analysis
for an intelligent workforce planning system: a socio-technical approach to design
AI-based systems, Procedia CIRP. 109 (2022) 431–436.'
ieee: 'S. Gabriel et al., “Requirements analysis for an intelligent workforce
planning system: a socio-technical approach to design AI-based systems,” Procedia
CIRP, vol. 109, pp. 431–436, 2022, doi: 10.1016/j.procir.2022.05.274.'
mla: 'Gabriel, Stefan, et al. “Requirements Analysis for an Intelligent Workforce
Planning System: A Socio-Technical Approach to Design AI-Based Systems.” Procedia
CIRP, vol. 109, 2022, pp. 431–36, https://doi.org/10.1016/j.procir.2022.05.274.'
short: S. Gabriel, D. Bentler, E.-M. Grote, C. Junker, D.M. zu Wendischhoff, M.
Bansmann, B. Latos, D. Hobscheidt, A. Kühn, R. Dumitrescu, Procedia CIRP 109 (2022)
431–436.
ufg: 'Gabriel, Stefan u. a.: Requirements analysis for an intelligent workforce
planning system: a socio-technical approach to design AI-based systems, in: Procedia
CIRP 109 (2022), S. 431–436.'
van: 'Gabriel S, Bentler D, Grote EM, Junker C, Wendischhoff DM zu, Bansmann M,
et al. Requirements analysis for an intelligent workforce planning system: a socio-technical
approach to design AI-based systems. Procedia CIRP. 2022;109:431–6.'
date_created: 2023-10-30T10:13:04Z
date_updated: 2023-10-31T15:40:36Z
department:
- _id: DEP1522
doi: 10.1016/j.procir.2022.05.274
extern: '1'
intvolume: ' 109'
keyword:
- socio-technial design socio-technial design
- requirements elicitation
- AI-human-collaboration
- 'work design : workforce planning requirements elicitation AI-human-collaboration
work design workforce planning'
language:
- iso: eng
page: 431-436
publication: Procedia CIRP
publication_identifier:
issn:
- 2212-8271
publication_status: published
publisher: Elsevier BV
quality_controlled: '1'
status: public
title: 'Requirements analysis for an intelligent workforce planning system: a socio-technical
approach to design AI-based systems'
type: journal_article
user_id: '83781'
volume: 109
year: '2022'
...
---
_id: '6910'
abstract:
- lang: eng
text: "AI is on the rise. Powerful cloud platforms and networked software components
can perform increasingly complex data evaluations and simulations. Recent research
and development projects1 show how great the potential of artificial intelligence
is for urban planning. However, despite the impressive, technical possibilities,
it currently remains unclear how planning stakeholders and the affected population
can be meaningfully involved in the intelligent processes of the \"black box\".
The authors are of the opinion that sustainable urban development planning not
only requires acceptance of the spatial planning result, as has been the case
up to now, but also requires acceptance of the increasingly digitally supported
planning process. For this reason, it must also be possible for laypersons to
understand the digital analysis and evaluation processes and to comprehend their
relevance and spatial interactions. Consequently, simulations must not only run
in the computers of the respective planning or engineering offices, but require
a simple, haptic analog translation that can also be used in participation processes
as already shown in the CityScope projects2. \r\nFor this project, the big revitalization
project of Deutzer Hafen in Cologne to a future district with more than 9.500
daily users is used as a case study in building a decision support system for
urban planning. It is composed of three parts: an agent-based model, a tangible
user interface and a synthetic population. The project enables users to get in
touch with an agent-based model (ABM) without any knowledge in coding or even
interacting with computers. It connects physical objects to digital information.
Based on the theories of Castiglione et.al.3 , Gehl4 , Shannon5 and Jacobs6 this
project shows how to use an artificial and analog simulation model to measure
the urban vitality of the public spaces in the district, based on the activity
and travelling patterns of the population. This is done by testing different scenarios
in which we change interactive parameters of the model: the use of the buildings
and the demographics of the population. We can then determine which scenarios
benefit the most life in the public spaces of the district, by finding areas of
interest or problematic ones. "
author:
- first_name: Amanda
full_name: Barbosa Jardim, Amanda
id: '76917'
last_name: Barbosa Jardim
- first_name: Maximilian
full_name: Müh, Maximilian
id: '74260'
last_name: Müh
- first_name: Axel
full_name: Häusler, Axel
id: '61520'
last_name: Häusler
orcid: 0009-0001-8565-8199
- first_name: Andrea
full_name: Kondziela, Andrea
id: '81431'
last_name: Kondziela
citation:
ama: 'Barbosa Jardim A, Müh M, Häusler A, Kondziela A. Synthetic and Tangible Agents
for an Activity-based Urban Planning Tool. In: Schrenk M, Popovich VV, Zeile P,
et al., eds. REAL CORP 2021: Cities 20.50, Creating Habitats for the 3rd
Millennium, Smart - Sustainable - Climate Neutral : Proceedings of 26th International
Conference on Urban Planning, Regional Development and Information Society.
CORP - Competence Center of Urban and Regional Planning; 2021. doi:10.48494/REALCORP2021.1049'
apa: 'Barbosa Jardim, A., Müh, M., Häusler, A., & Kondziela, A. (2021). Synthetic
and Tangible Agents for an Activity-based Urban Planning Tool. In M. Schrenk,
V. V. Popovich, P. Zeile, P. Elisei, C. Beyer, J. Ryser, G. Stöglehner, &
CORP – Competence Center of Urban and Regional Planning (Eds.), REAL CORP
2021: Cities 20.50, creating habitats for the 3rd millennium, smart - sustainable
- climate neutral : proceedings of 26th International Conference on Urban Planning,
Regional Development and Information Society. CORP - Competence Center of
Urban and Regional Planning. https://doi.org/10.48494/REALCORP2021.1049'
bjps: 'Barbosa Jardim A et al. (2021) Synthetic and Tangible Agents
for an Activity-Based Urban Planning Tool. In Schrenk M et al. (eds), REAL
CORP 2021: Cities 20.50, Creating Habitats for the 3rd Millennium, Smart - Sustainable
- Climate Neutral : Proceedings of 26th International Conference on Urban Planning,
Regional Development and Information Society. Wien: CORP - Competence Center
of Urban and Regional Planning.'
chicago: 'Barbosa Jardim, Amanda, Maximilian Müh, Axel Häusler, and Andrea Kondziela.
“Synthetic and Tangible Agents for an Activity-Based Urban Planning Tool.” In
REAL CORP 2021: Cities 20.50, Creating Habitats for the 3rd Millennium, Smart
- Sustainable - Climate Neutral : Proceedings of 26th International Conference
on Urban Planning, Regional Development and Information Society, edited by
Manfred Schrenk, Vasily V. Popovich, Peter Zeile, Pietro Elisei, Clemens Beyer,
Judith Ryser, Gernot Stöglehner, and CORP – Competence Center of Urban and Regional
Planning. Wien: CORP - Competence Center of Urban and Regional Planning, 2021.
https://doi.org/10.48494/REALCORP2021.1049.'
chicago-de: 'Barbosa Jardim, Amanda, Maximilian Müh, Axel Häusler und Andrea Kondziela.
2021. Synthetic and Tangible Agents for an Activity-based Urban Planning Tool.
In: REAL CORP 2021: Cities 20.50, creating habitats for the 3rd millennium,
smart - sustainable - climate neutral : proceedings of 26th International Conference
on Urban Planning, Regional Development and Information Society, hg. von Manfred
Schrenk, Vasily V. Popovich, Peter Zeile, Pietro Elisei, Clemens Beyer, Judith
Ryser, Gernot Stöglehner, und CORP – Competence Center of Urban and Regional Planning.
Wien: CORP - Competence Center of Urban and Regional Planning. doi:10.48494/REALCORP2021.1049,
.'
din1505-2-1: 'Barbosa Jardim, Amanda
; Müh, Maximilian ; Häusler,
Axel ; Kondziela, Andrea:
Synthetic and Tangible Agents for an Activity-based Urban Planning Tool. In: Schrenk, M. ; Popovich,
V. V. ; Zeile, P. ; Elisei, P. ; Beyer,
C. ; Ryser, J. ; Stöglehner,
G. ; CORP – Competence Center of
Urban and Regional Planning (Hrsg.): REAL CORP 2021: Cities 20.50,
creating habitats for the 3rd millennium, smart - sustainable - climate neutral :
proceedings of 26th International Conference on Urban Planning, Regional Development
and Information Society. Wien : CORP - Competence Center of Urban and Regional
Planning, 2021'
havard: 'A. Barbosa Jardim, M. Müh, A. Häusler, A. Kondziela, Synthetic and Tangible
Agents for an Activity-based Urban Planning Tool, in: M. Schrenk, V.V. Popovich,
P. Zeile, P. Elisei, C. Beyer, J. Ryser, G. Stöglehner, CORP – Competence Center
of Urban and Regional Planning (Eds.), REAL CORP 2021: Cities 20.50, Creating
Habitats for the 3rd Millennium, Smart - Sustainable - Climate Neutral : Proceedings
of 26th International Conference on Urban Planning, Regional Development and Information
Society, CORP - Competence Center of Urban and Regional Planning, Wien, 2021.'
ieee: 'A. Barbosa Jardim, M. Müh, A. Häusler, and A. Kondziela, “Synthetic and Tangible
Agents for an Activity-based Urban Planning Tool,” in REAL CORP 2021: Cities
20.50, creating habitats for the 3rd millennium, smart - sustainable - climate
neutral : proceedings of 26th International Conference on Urban Planning, Regional
Development and Information Society, M. Schrenk, V. V. Popovich, P. Zeile,
P. Elisei, C. Beyer, J. Ryser, G. Stöglehner, and CORP – Competence Center of
Urban and Regional Planning, Eds. Wien: CORP - Competence Center of Urban and
Regional Planning, 2021. doi: 10.48494/REALCORP2021.1049.'
mla: 'Barbosa Jardim, Amanda, et al. “Synthetic and Tangible Agents for an Activity-Based
Urban Planning Tool.” REAL CORP 2021: Cities 20.50, Creating Habitats for
the 3rd Millennium, Smart - Sustainable - Climate Neutral : Proceedings of 26th
International Conference on Urban Planning, Regional Development and Information
Society, edited by Manfred Schrenk et al., CORP - Competence Center of Urban
and Regional Planning, 2021, https://doi.org/10.48494/REALCORP2021.1049.'
short: 'A. Barbosa Jardim, M. Müh, A. Häusler, A. Kondziela, in: M. Schrenk, V.V.
Popovich, P. Zeile, P. Elisei, C. Beyer, J. Ryser, G. Stöglehner, CORP – Competence
Center of Urban and Regional Planning (Eds.), REAL CORP 2021: Cities 20.50,
Creating Habitats for the 3rd Millennium, Smart - Sustainable - Climate Neutral :
Proceedings of 26th International Conference on Urban Planning, Regional Development
and Information Society, CORP - Competence Center of Urban and Regional Planning,
Wien, 2021.'
ufg: 'Barbosa Jardim, Amanda u. a.: Synthetic and Tangible Agents for an
Activity-based Urban Planning Tool, in: Schrenk, Manfred u. a. (Hgg.):
REAL CORP 2021: Cities 20.50, creating habitats for the 3rd millennium, smart
- sustainable - climate neutral : proceedings of 26th International Conference
on Urban Planning, Regional Development and Information Society, Wien 2021.'
van: 'Barbosa Jardim A, Müh M, Häusler A, Kondziela A. Synthetic and Tangible Agents
for an Activity-based Urban Planning Tool. In: Schrenk M, Popovich VV, Zeile P,
Elisei P, Beyer C, Ryser J, et al., editors. REAL CORP 2021: Cities 2050, creating
habitats for the 3rd millennium, smart - sustainable - climate neutral : proceedings
of 26th International Conference on Urban Planning, Regional Development and Information
Society. Wien: CORP - Competence Center of Urban and Regional Planning; 2021.'
conference:
end_date: 2021-10-10
location: Wien
name: 'REAL CORP - International Conference on Urban Planning and Regional Development
in the Information Society '
start_date: 2021-10-07
corporate_editor:
- CORP – Competence Center of Urban and Regional Planning
date_created: 2021-12-16T10:57:54Z
date_updated: 2024-12-04T12:57:10Z
department:
- _id: DEP1055
- _id: DEP1028
doi: 10.48494/REALCORP2021.1049
editor:
- first_name: Manfred
full_name: Schrenk, Manfred
last_name: Schrenk
- first_name: Vasily V.
full_name: Popovich, Vasily V.
last_name: Popovich
- first_name: Peter
full_name: Zeile, Peter
last_name: Zeile
- first_name: Pietro
full_name: Elisei, Pietro
last_name: Elisei
- first_name: Clemens
full_name: Beyer, Clemens
last_name: Beyer
- first_name: Judith
full_name: Ryser, Judith
last_name: Ryser
- first_name: Gernot
full_name: Stöglehner, Gernot
last_name: Stöglehner
keyword:
- mart Cities
- Agent-based modelling
- KI/AI
- Participation
- Tangible Data
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.corp.at/archive/CORP2021_49.pdf
oa: '1'
place: Wien
publication: "\t REAL CORP 2021: Cities 20.50, creating habitats for the 3rd millennium,
smart - sustainable - climate neutral : proceedings of 26th International Conference
on Urban Planning, Regional Development and Information Society"
publication_identifier:
isbn:
- 978-3-9504945-0-1
publication_status: published
publisher: CORP - Competence Center of Urban and Regional Planning
quality_controlled: '1'
related_material:
link:
- relation: original
url: https://www.corp.at/archive/CORP2021_49.pdf
status: public
title: Synthetic and Tangible Agents for an Activity-based Urban Planning Tool
type: book_chapter
user_id: '83781'
year: '2021'
...