Der Interreg Programmraum Österreich-Bayern ist eine Region mit einer hohen Anzahl von (kleinen und mittelständischen) Unternehmen (KMU), die der Produktion und Fertigung von Produktionsanlagen zugeordnet werden können. Künstliche Intelligenz (KI) ist eine Schlüsseltechnologie der industriellen Digitalisierung. Sie bietet großes Potential im Bereich der Optimierung verschiedenster Aspekte von Produktionsprozessen (z.B. Ressourcenverbrauch, Energieverbrauch, Emissionsreduktion, Qualitätsverbesserungen, Predictive Maintenance). Jedoch umfasst das Thema KI so viele Bausteine/Methoden (siehe Auflistung unten), dass Unternehmen - insbesondere KMU - damit überfordert sind und diese Potentiale nicht ausschöpfen können. Gründe sind zum einen fehlende Fachexpertise und zum anderen eine derzeit für die Unternehmen unwägbare Komplexität und Risiken in der Anwendung. Das vorliegende Projekt entwickelt ein grenzübergreifendes Kompetenznetzwerk, das grundlegende Bausteine für KI-basierte Optimierungen in der industriellen Fertigung untersucht, erforscht und entwickelt, präsentiert und damit für KMU den Zugang zum gezielten Einsatz von KI in Produktions- und Instandhaltungs-Prozessen erleichtert. Dabei wird klar herausgearbeitet, welche KI-Bausteine/Methoden für welche industriellen Fertigungsaufgaben die passendsten sind. Zu den KI-Bausteinen/Methoden zählen 1) Digital Twins, Robotik & KI-gestützte Modellbildung, 2) Systems-Engineering Prozesse, 3) Wissensrepräsentation, 4) Datenanalyse- sowie Optimierungs- & Lernverfahren, 5) Anwendungsleitfaden für den Einsatz von KI in der Fertigung. Die Projektteilnehmer bündeln das notwendige Know-how, um eine für Europa als vorteilhaft erachtete Reindustrialisierung basierend auf neuesten Technologien, hier vorranging der Nutzbarmachung von KI in industriellen Produktions- und Instandhaltungsprozessen durch KMU, voranzutreiben.

The OntoCommons project's overall objective is to bring together and coordinate activities of the most relevant EU stakeholders for the development of an Ontology Commons EcoSystem (OCES), consisting of ontologies and tools following specific standardization rules, that can be effectively used as foundation for data documentation in the industrial domain, in order to facilitate data sharing and valorisation and overcome the existing interoperability bottlenecks.

In the CampaNeo project, an open platform will be developed on which private and public institutions can create campaigns and collect and analyze vehicle data in real-time. The goal is to set up a prototype platform for secure campaign-based data collection in Hanover, Wolfsburg and in cross-regional scenarios, as well as the implementation of the first smart use cases based on the campaign data. The focus is in particular on the data ownerships of vehicle owners and the traceability of data processing. The analysis of vehicle sensor data (e.g. for the detection of driving behavior, finding of driver efficiency scores, anomaly detection, etc.) requires the creation and use of models of machine learning (ML). Among others, the CampaNeo project aims to address issues related to the efficient use of ML models, taking into account data quality and data protection aspects for real-time vehicle data. The results of the CampaNeo project include technologies and analysis techniques that are useful for many user groups such as municipalities, fleet management providers, insurance companies and service providers in the fields of data science and mobility. These results are validated together with business users in selected application scenarios and economically and scientifically exploited by the consortium and associated partners.

The objective of smashHit is to assure trusted and secure sharing of data streams from both personal and industrial platforms, needed to build sectorial and cross-sectorial services, by establishing a Framework for processing of data owner consent and legal rules and effective contracting, as well as joint security and privacy preserving mechanisms. The vision of smashHit is to overcome obstacles in the rapidly growing Data Economy which is characterized by heterogeneous technical designs and proprietary implementations, locking business opportunities due to the inconsistent consent and legal rules among different data-sharing platforms actors and operators. The Framework will provide methods and tools, such as Smart Data Dispatcher, to assure common consent over data shared using semantic models of consent and legal rules. The new tools include trace-ability of use of data, data fingerprinting and automatic contracting among the data owners, data providers, service providers and users. These tools are specifically critical for enormous volumes on data streaming from the usage of mass products with cyber physical features (e.g. vehicles). These data streams offer new opportunities to build innovative services, but their combination with other personal and industrial data is subject to complex ownership and consent aspects, as the data streaming from these products belong to persons or organizations who are owners or users of the products. The project will be based on the solutions developed or under development in previous and current projects (AutoMat, Cross-CPP, CAMPANEO, DALICC, etc.). smashHit will be driven by 2 industrial Business Cases involving several existing industrial and personal data platforms owned by the leading data providers in three diverse sectors (automotive industry, insurance, smart city), and will provide 3 demonstrators of various applications of the developed solutions.

The main objective of Talking Knowledge Graphs project is to improve goal-oriented dialog systems such as Intelligent Personal Assistants (e.g., Amazon Alexa, Google Assistant, Siri) with the help of Knowledge Graphs. There are already industrial-grade frameworks for managing the conversational aspects of such systems, however goal oriented aspects are still has to be dealt with manually, which creates a major bottleneck on the development of such systems. The project aims to enable semi-automated creation of service and data driven dialogs and bring this technology to production-ready systems.