NAIS 2022 Keynote: AI- and Robotics-enabled systems, a forward leap into real life applications
Looking forward to presenting my keynote titled “AI- and Robotics-enabled systems, a forward leap into real life applications” at the 2022 symposium of the Norwegian AI Society on May 31 - June 1, OsloMet - Oslo Metropolitan University.
AI- and Robotics-enabled systems are becoming more and more relevant for real life applications. This technology may enable society to a conceptual leap forward especially concerning demanding real-life scenarios. In this talk, different scenarios will be considered, including AI- and robotics-enabled systems for the Industry 4.0, wearable robotics, intelligent health, human-robot interaction/collaboration, and search-and-rescue (SAR).
More information: https://www.aisociety.no/nais2022/
2022, April, 7
Filippo Sanfilippo
education,
robotics,
hands,
virtual reality,
augmented reality (ar),
metaverse
0
Dissemination of the latest results from our AugmentedWearEdu project
Today, Professor Tomas Blažauskas gave a talk to disseminate the latest results from our AugmentedWearEdu project. It was a pleasure to participate to the event organised by Vida Drąsutė at Kaunas University of Technology, Lithuania.
This research is funded by the European Union through the Erasmus+ Program under Grant 2020-1-NO01-KA203-076540, project title Integrating virtual and AUGMENTED reality with WEARable technology into engineering EDUcation (AugmentedWearEdu), https://augmentedwearedu.uia.no/. This work was also supported by the Top Research Centre Mechatronics (TRCM), University of Agder (UiA), Norway.
I really thank all the project partners and I congratulate all of them for their contribution.
Adaptive ML-based technique for renewable energy system power forecasting in hybrid PV-Wind farms power conversion systems
A new paper has been published in the journal Energy Conversion and Management. The selected article is:
Muhammad Hamza Zafar, Noman Mujeeb Khan, Majad Mansoor, Adeel Feroz Mirza, Syed Kumayl Raza Moosavi, Filippo Sanfilippo. Adaptive ML-based technique for renewable energy system power forecasting in hybrid PV-Wind farms power conversion systems. Energy Conversion and Management, Volume 258, 2022, 115564, ISSN 0196-8904, https://doi.org/10.1016/j.enconman.2022.115564.
This work is supported by the Top Research Centre Mechatronics (TRCM), University of Agder (UiA).
I really thank all my co-authors and I congratulate all of them for their contribution.
Filippo Sanfilippo