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Project detail
Duration: 01.04.2021 — 31.03.2024
Funding resources
Ministerstvo školství, mládeže a tělovýchovy ČR - Společná technologická iniciativa ECSEL
- whole funder (2021-04-01 - 2024-03-31)Evropská unie - Horizon 2020
- whole funder (2021-04-01 - 2024-03-31)
On the project
The project targets the development of a model-based framework to support teams during the automated continuous development of CPSs by means of integrated AI-augmented solutions. The overall AIDOaRT infrastructure will work with existing data sources, including traditional IT monitoring, log events, along with software models and measurements. The infrastructure is intended to operate within the DevOps process combining software development and information technology (IT) operations. Moreover, AI technological innovations have to ensure that systems are designed responsibly and contribute to our trust in their behaviour (i.e., requiring both accountability and explainability). AIDOaRT aims to impact organizations where continuous deployment and operations management are standard operating procedures. DevOps teams may use the AIDOaRT framework to analyze event streams in real-time and historical data, extract meaningful insights from events for continuous improvement, drive faster deployments and better collaboration, and reduce downtime with proactive detection.
Description in CzechProjekt se zaměřuje na vývoj modelového rámce pro podporu týmů během automatizovaného nepřetržitého vývoje CPS pomocí integrovaných řešení rozšířených o AI. Celková infrastruktura AIDOaRT bude fungovat s existujícími zdroji dat, včetně tradičního monitorování IT, spolu se softwarovými modely a měřeními. Infrastruktura je určena k provozu v procesu DevOps, kombinujícím vývoj softwaru a operace informačních technologií (IT). Technologické inovace AI musí navíc zajistit, aby systémy byly navrženy odpovědně a přispěly k důvěře v jejich chování.
KeywordsSoftware engineering, operating systems, computer languages, Artificial intelligence, intelligent systems, multi agent systems
Key words in CzechSoftwarové inženýrství, operační systémy, počítačové jazyky, umělá inteligence, inteligentní systémy
Mark
101007350
Default language
English
People responsible
Hájková Gabriela, Mgr. - fellow researcherHomoliak Ivan, Ing., Ph.D. - fellow researcherJuříček Zdeněk - fellow researcherKocman Radim, Ing., Ph.D. - fellow researcherKolář Martin, M.Sc., Ph.D. et Ph.D. - fellow researcherKula Michal, Ing., Ph.D. - fellow researcherMatýšek Michal, Ing. - fellow researcherMusil Petr, Ing., Ph.D. - fellow researcherŠpaněl Michal, Ing., Ph.D. - fellow researcherZemčík Pavel, prof. Dr. Ing., dr. h. c. - fellow researcherSmrž Pavel, doc. RNDr., Ph.D. - principal person responsible
Units
Department of Computer Graphics and Multimedia - (2020-06-09 - 2024-03-31)Nitte Meenakshi Institute of Technology- (2020-06-09 - 2024-03-31)Mälardalen University - (2020-06-09 - 2024-03-31)
Results
ALI, A.; SMRŽ, P. Camera auto-calibration for complex scenes. In SPIE 11605. Rome: SPIE - the international society for optics and photonics, 2021. p. 1-11. ISBN: 978-1-5106-4041-2.Detail
BAMBUŠEK, D.; MATERNA, Z.; KAPINUS, M.; BERAN, V.; SMRŽ, P. How Do I Get There? Overcoming Reachability Limitations of Constrained Industrial Environments in Augmented Reality Applications. In 2023 IEEE Conference on Virtual Reality and 3D User Interfaces (VR). Shanghai: Institute of Electrical and Electronics Engineers, 2023. p. 115-122. ISBN: 979-8-3503-4815-6.Detail
CHLUBNA, T.; MILET, T.; ZEMČÍK, P.; KULA, M. Real-Time Light Field Video Focusing and GPU Accelerated Streaming. Journal of Signal Processing Systems for Signal Image and Video Technology, 2023, vol. 95, no. 6, p. 703-719. ISSN: 1939-8115.Detail
CHLUBNA, T.; ZEMČÍK, P.; MILET, T. Efficient Random-Access GPU Video Decoding for Light-Field Rendering. JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, 2024, vol. 2024, no. 102, p. 1-14. ISSN: 1047-3203.Detail
CHLUBNA, T.; MILET, T.; ZEMČÍK, P. Automatic 3D-Display-Friendly Scene Extraction from Video Sequences and Optimal Focusing Distance Identification. MULTIMEDIA TOOLS AND APPLICATIONS, 2024, vol. 83, no. 7, p. 1-29. ISSN: 1573-7721.Detail
APAROVICH, M.; KESIRAJU, S.; DUFKOVÁ, A.; SMRŽ, P. FIT BUT at SemEval-2023 Task 12: Sentiment Without Borders - Multilingual Domain Adaptation for Low-Resource Sentiment Classification. In Proceedings of the The 17th International Workshop on Semantic Evaluation (SemEval-2023). Toronto (online): Association for Computational Linguistics, 2023. p. 1518-1524. ISBN: 978-1-959429-99-9.Detail
CHLUBNA, T.; MILET, T.; ZEMČÍK, P. Lightweight All-Focused Light Field Rendering. COMPUTER VISION AND IMAGE UNDERSTANDING, 2024, vol. 244, no. 7, p. 7-8. ISSN: 1077-3142.Detail
CHLUBNA, T.; MILET, T.; ZEMČÍK, P. How Capturing Camera Trajectory Distortion Affects User Experience on Looking Glass 3D Display. MULTIMEDIA TOOLS AND APPLICATIONS, 2024, vol. 2024, no. 83, p. 20265-20287. ISSN: 1573-7721.Detail