TY  - JOUR
A1  - Ulmer, Jessica
A1  - Braun, Sebastian
A1  - Cheng, Chi-Tsun
A1  - Dowey, Steve
A1  - Wollert, Jörg
T1  - A human factors-aware assistance system in manufacturing based on gamification and hardware modularisation
JF  - International Journal of Production Research
N2  - Assistance systems have been widely adopted in the manufacturing sector to facilitate various processes and tasks in production environments. However, existing systems are mostly equipped with rigid functional logic and do not provide individual user experiences or adapt to their capabilities. This work integrates human factors in assistance systems by adjusting the hardware and instruction presented to the workers’ cognitive and physical demands. A modular system architecture is designed accordingly, which allows a flexible component exchange according to the user and the work task. Gamification, the use of game elements in non-gaming contexts, has been further adopted in this work to provide level-based instructions and personalised feedback. The developed framework is validated by applying it to a manual workstation for industrial assembly routines.
KW  - Human factors
KW  - assistance system
KW  - gamification
KW  - adaptive systems
KW  - manufacturing
Y1  - 2023
U6  - https://doi.org/10.1080/00207543.2023.2166140
SN  - 0020-7543 (Print)
SN  - 1366-588X (Online)
PB  - Taylor & Francis
ER  - 
TY  - CHAP
A1  - Dey, Thomas
A1  - Elsen, Ingo
A1  - Ferrein, Alexander
A1  - Frauenrath, Tobias
A1  - Reke, Michael
A1  - Schiffer, Stefan
ED  - Makedon, Fillia
T1  - CO2 Meter: a do-it-yourself carbon dioxide measuring device for the classroom
T2  - PETRA '21: Proceedings of the 14th Pervasive Technologies Related to Assistive Environments Conference
N2  - In this paper we report on CO2 Meter, a do-it-yourself carbon dioxide measuring device for the classroom. Part of the current measures for dealing with the SARS-CoV-2 pandemic is proper ventilation in indoor settings. This is especially important in schools with students coming back to the classroom even with high incidents rates. Static ventilation patterns do not consider the individual situation for a particular class. Influencing factors like the type of activity, the physical structure or the room occupancy are not incorporated. Also, existing devices are rather expensive and often provide only limited information and only locally without any networking. This leaves the potential of analysing the situation across different settings untapped. Carbon dioxide level can be used as an indicator of air quality, in general, and of aerosol load in particular. Since, according to the latest findings, SARS-CoV-2 can be transmitted primarily in the form of aerosols, carbon dioxide may be used as a proxy for the risk of a virus infection. Hence, schools could improve the indoor air quality and potentially reduce the infection risk if they actually had measuring devices available in the classroom. Our device supports schools in ventilation and it allows for collecting data over the Internet to enable a detailed data analysis and model generation. First deployments in schools at different levels were received very positively. A pilot installation with a larger data collection and analysis is underway.
KW  - embedded hardware
KW  - sensor networks
KW  - information systems
KW  - education
KW  - do-it-yourself
Y1  - 2021
SN  - 9781450387927
U6  - https://doi.org/10.1145/3453892.3462697
N1  - PETRA '21: The 14th PErvasive Technologies Related to Assistive Environments Conference Corfu Greece 29 June 2021- 2 July 2021
SP  - 292
EP  - 299
PB  - Association for Computing Machinery
CY  - New York
ER  -