@inproceedings{iber_auditory_2019, address = {Nottingham, UNited Kingdom}, title = {Auditory {Augmented} {Reality} for {Cyber} {Physical} {Production} {Systems}}, isbn = {978-1-4503-7297-8}, doi = {10.1145/3356590.3356600}}, abstract = {We describe a proof-of-concept approach on the sonification of estimated operation states of 3D printing processes. The results of this study form the basis for the development of an “intelligent” noise protection headphone as part of Cyber Physical Production Systems, which provides auditorily augmented information to machine operators and enables radio communication between them. Further application areas are implementations in control rooms (equipped with multichannel loudspeaker systems) and utilization for training purposes. The focus of our research lies on situation-specific acoustic processing of conditioned machine sounds and operation related data with high information content, considering the often highly auditorily influenced working knowledge of skilled workers. As a proof-of-concept the data stream of error probability estimations regarding partly manipulated 3D printing processes was mapped to three sonification models, giving evidence about momentary operation states. The neural network applied indicates a high accuracy ({\textgreater}93\%) concerning error estimation distinguishing between normal and manipulated operation states. None of the manipulated states could be identified by listening. An auditory augmentation, respectively sonification of these error estimations provides a considerable benefit to process monitoring.}, booktitle = {{AudioMostly} ({AM}'19)}, publisher = {ACM New York, NY, USA}, author = {Iber, Michael and Lechner, Patrik and Jandl, Christian and Mader, Manuel and Reichmann, Michael}, year = {2019}, note = {Projekt: IML}, keywords = {Auditory Display, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Forschungsgruppe Media Creation, Immersive Media (AR, VR, 360°), Institut für Creative Media Technologies, Smart Manufacturing, Vortrag, best, best-lbiber, peer-reviewed, ⚠️ Invalid DOI}, } @inproceedings{jandl_bluedat_2018, address = {Kiel, Germany}, title = {{BlueDAT} - {A} conceptual framework for smart asset tracking using {Bluetooth} 5 in industrial enviroment}, url = {http://amies-2018.international-symposium.org/proceedings_2018/Jandl_Schoeffer_Weninger_Moser_AmiEs_2018_Paper.pdf}, abstract = {In course of digitization of production facilities, tracking of assets in the supply chain becomes increasingly relevant for the manufacturing industry. Asset tracking refers to the method of tracking physical production orders, either by scanning bar code labels on production bins or by using tags with UWB, GPS, BLE or RFID technology attached to the bins that transmit their location to a suitable system. Current research and development projects use the Bluetooth (BT) standard 4.2. Although BT 4.2 is very energy-efficient and good results are achieved and considering the test results of current BT 4.2 AT systems, this paper describes the structure and prototypical implementation of a low-cost BT 5 Asset Tracking System. This open system is characterized by the reduction of unnecessary data transmission, greater configurability (e.g. transmission interval) and a generally higher intelligence of the individual receiving stations. Therefore, we expect a higher accuracy and reliability due to the collaboration of the receiving stations. The objective is to create a system that can be used economically for industrial companies while still providing adequate results in the area recognition of assets. The proposed solution is expected to reduce the costs associated with tracking and managing assets and improve asset utilization and operational efficiency.}, booktitle = {International {Symposium} on {Ambient} {Intelligence} and {Embedded} {Systems} - {AmiES} 2018}, author = {Jandl, Christian and Schöffer, Lucas and Weninger, Christoph and Moser, Thomas}, year = {2018}, keywords = {Forschungsgruppe Digital Technologies, Institut für Creative Media Technologies, Wiss. Beitrag, peer-reviewed, ⛔ No DOI found}, } @inproceedings{girsule_data_2020, address = {Vienna (Austria)}, title = {Data {Acquisition} {Approaches} for {AI}-supported {Metal} {Processing}}, url = {https://ieeexplore.ieee.org/document/9211935}, doi = {10/ghs5v9}, abstract = {Due to increasing digitalisation, it is possible to digitally map the production of sheet metal profiles from configuration to production. In our research project we design, implement and evaluate a knowledge- and rule-based system in cooperation with a sheet metal profile manufacturer using a modern production machine. One big challenge hereby is the data acquisition to perform a producibility assessment. In many cases only the positive (producible) production data is stored and negative data is discarded during the production process. In this paper, we present approaches to generate and collect negative training data for a machine learning approach using a data generator and feedback from manufacturing experts to perform a predictive manufacturing assessment.}, language = {en}, booktitle = {{ETFA} 2020 - {IEEE} 25th {International} {Conference} on {Emerging} {Technologies} and {Factory} {Automation}}, author = {Girsule, Bernhard and Rottermanner, Gernot and Jandl, Christian and Kreiger, Mylene and Moser, Thomas and Fuchs, Patricia}, year = {2020}, note = {Projekt: Wikant}, keywords = {Eintrag überprüfen, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Digital Technologies, Forschungsgruppe Media Computing, Green OA, Institut für Creative Media Technologies, Institutional Access, Smart Manufacturing, Wiss. Beitrag, peer-reviewed}, pages = {4}, } @article{iber_auditory_2020, title = {Auditory augmented process monitoring for cyber physical production systems}, issn = {1617-4909, 1617-4917}, url = {http://link.springer.com/10.1007/s00779-020-01394-3}, doi = {10/ghz24q}, language = {en}, urldate = {2020-03-30}, journal = {Personal and Ubiquitous Computing}, author = {Iber, Michael and Lechner, Patrik and Jandl, Christian and Mader, Manuel and Reichmann, Michael}, month = mar, year = {2020}, note = {Projekt: IML}, keywords = {Auditory Display, Eintrag überprüfen, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Forschungsgruppe Media Creation, Green OA, Immersive Media (AR, VR, 360°), Institut für Creative Media Technologies, Open Access, Smart Manufacturing, Wiss. Beitrag, best, best-lbiber, peer-reviewed}, } @inproceedings{jandl_sensitrack_2019, address = {Zaragossa,Spain}, title = {{SensiTrack} - {A} {Privacy} by {Design} {Concept} for industrial {IoT} {Applications}}, abstract = {In the course of further digitization of industrial manufacturing, companies are using tracking systems to monitor their production processes. This creates a large amount of data with location references, having an influence on the employees privacy – especially if personal references to employees are possible. To investigate this topic, a use case was carried out in an industrial environment. Therefore, a self-developed asset tracking (AT) system was developed and compared with a Commercialof- the-shelf (COTS) AT-System with regard to functionality and employee privacy. One mayor finding was that the Bluetooth Low Energy (BLE) based legacy system has weaknesses with regard to privacy, e.g. the advertising-data of mobile devices of the employees were stored in the cloud application of the system provider. This data can be used to determine the position of employees. With the self-developed system these weaknesses were avoided by using a Privacy by Design (PbD) approach. Therefore, this paper focuses on employee privacy in industrial AT applications and provides a PbD concept for wireless sensor networks in industrial environments.}, publisher = {IEEE Xplore}, author = {Jandl, Christian and Nurgazina, Jamilya and Schöffer, Lucas and Reichl, Christian and Wagner, Markus and Moser, Thomas}, month = sep, year = {2019}, note = {Projekt: SensiTrack}, keywords = {Forschungsgruppe Digital Technologies, Institut für Creative Media Technologies, Smart Manufacturing, Vortrag, Wiss. Beitrag, peer-reviewed}, } @misc{jandl_aarip-virtual_2019, title = {{AARiP}-{Virtual} {Reality} {App} for {Oculus} {Go}}, abstract = {VR-App zum Evaluieren der Sonifikation im Usecase AARiP (IML Projekt)}, author = {Jandl, Christian and Mader, Christian and Iber, Michael}, month = sep, year = {2019}, note = {Projekt: IML}, keywords = {Forschungsgruppe Digital Technologies, Forschungsgruppe Media Creation, Immersive Media (AR, VR, 360°), Institut für Creative Media Technologies}, } @incollection{bertschler_prufungsvorbereitung_2015, address = {Glückstadt}, title = {Prüfungsvorbereitung für {Medizinstudierende}: {Empfehlungen} für die {Entwicklung} einer {M}-{Learning} {Applikation}}, isbn = {978-3-86488-090-2}, booktitle = {Forum {Medientechnik} {Next} {Generation}, {New} {Ideas}: {Beiträge} der {Tagung} 2015 an der {Fachhochschule} {St}. {Pölten}}, publisher = {Verlag Werner Hülsbusch}, author = {Bertschler, Martin and Gritz, Patricia-Nicole and Gvodzen, Ana and Jandl, Christian and Pfersmann, Wilhelm and Scheucher, Theres-Sophie and Zeller, Bernhard and Blumenstein, Kerstin and Schmiedl, Grischa}, year = {2015}, keywords = {2015, Department Medien und Digitale Technologien, Department Technologie, Forschungsgruppe Digital Technologies, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Publikationstyp Präsentation, Publikationstyp Schriftpublikation, peer-reviewed}, pages = {157--171}, }