Active Learning (AL)

This module provides a placeholder for AL systems i.e., AI systems that can consult an authority (e.g., a human) in the cases where they lack data/information to take proper decisions. DevelopersJSI Developed in ProjectDeveloped in STARSTAR TrendArtificial Intelligence TypesSoftwareMachine Learning Used in ProjectUsed in STAR

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AI Cyber-Defence Strategies (ACDS)

The module implements different strategies in response to various attacks against AI system, notably poisoning and evasion attacks. DevelopersUBITECH DetectPoisoning Attacks Adversarial AttemptsAdversarial Data Samples Developed in ProjectDeveloped in STARSTAR PreventEvasion Attacks TrendArtificial Intelligence TypesSoftwareData Protection Used in ProjectUsed in STAR

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AMR Safety

It is composed by a safety zone detector and a robot planner. The first module will be used to provide insights on the safe placement of robots in a manufacturing environment. TRL4 DevelopersTHALES, University of Groningen CommunicationEthernet Developed in ProjectDeveloped in STARSTAR ProvideInsightsSafety Zone Detection TrendIndustry 4.0Artificial Intelligence Type of Machine LearningSupervised Object ClassificationFrugal Learning […]

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Distributed Ledger Services for Data Reliability (DLSDR)

Distributed Ledger Services for Data Reliability (DLSDR) provides a decentralized data reliability solution for industrial AI algorithms configurations and results. It offers an Analytics Engine Configuration (AEC) Service that supports Analytics by providing the capability for distributing analytics manifest objects across multiple gateways. Additionally, it offers an Analytics Results Publishing (ARP) Service,  that makes it […]

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Explainable Artificial Intelligence (XAI) Models and Library

This module provides and executes Explainable Artificial Intelligence models and algorithms. DevelopersUNIPI Developed in ProjectDeveloped in STARSTAR TrendArtificial Intelligence TypesSoftwarePlatform Used in ProjectUsed in STAR

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Fatigue Monitoring System (FaMS)

FaMS uses artificial intelligence (AI) models relying on machine learning to estimate fatigue exertion level and mental stress of subjects based on static data (e.g., age, weight, etc.) as well as dynamic data (e.g., HR, EDA, skin temperature). DevelopersSUPSI AlgorithmMachine Learning Developed in ProjectDeveloped in STARSTAR TrendArtificial Intelligence TypesSoftwareSystem Used in ProjectUsed in STAR

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Feedback Module

The feedback module interfaces to some interaction modules (e.g., GUI or NLP) that enable the transfer of user data to the feedback module and vice versa. DevelopersJSI, QLECTOR Developed in ProjectDeveloped in STARSTAR TypesSoftwareData Analytics Used in ProjectUsed in STAR

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Human Centred Digital Twin (HDT)

The platform supports human in the loop processes provides feedback/results on workers’ safety and performance. DevelopersSUPSI Developed in ProjectDeveloped in STARSTAR MonitorWorkers TrendArtificial Intelligence TypesSoftwarePlatform Used in ProjectUsed in STAR

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Natural Language Processing (NLP)

Natural Language Processing related components, proof of concepts and recommendations to facilitate the interaction between humans and machines and to get contextual information enabling efficient collaboration. TRL3 DevelopersR2M Developed in ProjectDeveloped in STARSTAR Technical Categories (JRC)CommunicationNatural language processing TrendArtificial Intelligence TypesSoftwareMachine LearningSoftwareConsultancy and Support

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Production Processes Knowledge Base (PPKB)

This module consolidates domain knowledge about the production processes of the manufacturing environment. DevelopersJSI, QLECTOR Developed in ProjectDeveloped in STARSTAR TrendIndustry 4.0 TypesSoftwareData Management

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Risk Assessment and Mitigation Engine (RAME)

This module is destined to assess risk for assets associated with AI-based systems in manufacturing lines. DevelopersUBITECH Developed in ProjectDeveloped in STARSTAR ManagementAssetsVulnerabilitiesThreatsMitigation Actions TrendArtificial IntelligenceIndustry 4.0 TypesSoftwareData Protection Used in ProjectUsed in STAR

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Runtime Monitoring System (RMS)

RMS is a Data collection framework which provides the specifications and relevant implementation to enable a real time data collection, transformation, filtering, and management service to facilitate data consumers (i.e., analytic algorithms). The framework can be applied in IoT environments supporting solutions in various domains (e.g., Industrial, Cybersecurity, etc.). The design of the framework is […]

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