2024W

• Computer Engineering Practical / 191.005 / PR
• Computer Engineering Project / 191.006 / PR
• Home and Building Automation / 183.624 / VU
• Project in Computer Science 1 / 191.008 / PR
• Project in Computer Science 2 / 191.009 / PR
• Scientific Project Computer Engineering / 191.007 / PR

• Unleashing Sector-coupling Flexibility by means of an Energy Data Space
  2023 – 2027 / Austrian Research Promotion Agency (FFG)
• Demonstration of a participatory renewable energy community to enhance resilience
  2021 – 2025 / Austrian Research Promotion Agency (FFG)
  Publications: 188166 / 188275 / 188530 / 188415 / 193242 / 193244
• Open Building Automation Modeling - Open modeling of building automation over the entire building life cycle
  2021 – 2024 / Austrian Research Promotion Agency (FFG)
  Publications: 153165 / 189687 / 193999 / 204052 / 205729
• eywa: distributed power intelligence
  2017 – 2018 / Vienna Business Agency (WAW)

• Towards Open Modeling of Building Automation over the entire building life cycle / Sint, S., Knorr, F., Pannosch, J., Kromp Jürgen, & Bednar, T. (2024). Towards Open Modeling of Building Automation over the entire building life cycle. In T. Bednar & S. Sint (Eds.), BauSIM 2024 Companion Proceedings : 10te Konferenz von IBPSA-DACH, TU Wien, Österreich (pp. 34–34). https://doi.org/10.34726/7560
  Download: Posterbeitrag (1.16 MB)
  Project: openBAM (2021–2024)
• A Model-Driven Approach for Consistent Building Automation Control Logic Design and Deployment / Knorr, F., Pannosch, J., & Steindl, G. (2024). A Model-Driven Approach for Consistent Building Automation Control Logic Design and Deployment. In 2024 International Conference on Control, Automation and Diagnosis (ICCAD). 2024 International Conference on Control, Automation and Diagnosis (ICCAD), Paris, France. https://doi.org/10.1109/ICCAD60883.2024.10553923
  Project: openBAM (2021–2024)
• Reference Model for Building Automation / Pannosch, J., & Kastner, W. (2023). Reference Model for Building Automation. In 2023 IEEE 28th International Conference on Emerging Technologies and Factory Automation (ETFA) (pp. 1–4). IEEE. https://doi.org/10.1109/ETFA54631.2023.10275528
  Project: openBAM (2021–2024)
• KNX-IoT Digital Twin / Pannosch, J., & Steindl, G. (2023). KNX-IoT Digital Twin. In Presentation and Papers KNX Scientific Conference 2023. KNX Scientific Partnership Conference 2023, Barcelona, Spain. http://hdl.handle.net/20.500.12708/191934
  Project: AFOM (2021–2024)
• Smart Homes: Wie sicher sind sie und wie lassen sie sich schützen? / Pannosch, J. (2022, July 19). Smart Homes: Wie sicher sind sie und wie lassen sie sich schützen? [Interview]. A-SIT Zentrum für sichere Informationstechnologie – Austria. http://hdl.handle.net/20.500.12708/192254
• Decentralized Management Framework for heterogeneous Devices in FM / Preindl, T., Pannosch, J., Kastner, W., Redlein, A., & Baretschneider, C. (2021). Decentralized Management Framework for heterogeneous Devices in FM. Journal Für Facility Management, WIEN(21), 26–38. http://hdl.handle.net/20.500.12708/138387
• Reliable data forecasting for building automation systems / Pannosch, J. (2018). Reliable data forecasting for building automation systems [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2018.37417
  Download: PDF (4.19 MB)
• Adaptive learning-based time series prediction framework for building energy management / Schachinger, D., Pannosch, J., & Kastner, W. (2018). Adaptive learning-based time series prediction framework for building energy management. In 2018 IEEE International Conference on Industrial Electronics for Sustainable Energy Systems (IESES). IEEE International Conference on Industrial Electronics for Sustainable Energy Systems (IESES 2018), Hamilton, New Zealand, Non-EU. IEEE. https://doi.org/10.1109/ieses.2018.8349919

• Improving energy community interoperability: a web of things approach / Esterbauer, L. (2022). Improving energy community interoperability: a web of things approach [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2022.92304
  Download: PDF (1.82 MB)