Active Learning (AL)

This module provides a placeholder for AL systems i.e., AI systems that are able to consult an authority (e.g., a human) in cases where they lack data/information to take proper decisions.

AI Cyber-Defence Strategies (ACDS)

The module implements different strategies in response to various attacks against AI system, notably poisoning and evasion attacks.

Autonomous Mobile Robot (AMR) planner using safety zone detection

It is composed form a safety zone detector and a robot planner. The first module will used to provide insights on the safe placement of robots in a manufacturing environment.

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…

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.) and dynamic data (e.g. HR, EDA, skin temperature).

Feedback Module

The feedback module interfaces to some interaction module (e.g., GUI or NLP) that enables the transferring of user data to the feedback module and vice versa.

Human Digital Twin Core Infrastructure

The platform support human in the loop processes and to provide feedback/results on workers’ safety and performance.

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.

Production Processes Knowledge Base (PPKB)

This module consolidates domain knowledge about the production processes of the manufacturing environment.

Risk Assessment and Mitigation Engine (RAME)

The module is destined to assess risk for assets associated with AI-based systems in manufacturing lines.

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, etch.). The design of the framework is…

Security Policies Manager (SPM) – Security Policies Repository (SPR)

This module specifies and configures security policies that are destined to govern the operation of the DPT, AI Cyber-Defence and RAME modules.
To top