AI REDGIO 5.0 Collaborative Intelligence Platform: Difference between revisions
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== Asset Description == | == Asset Description == | ||
Revision as of 14:54, 7 October 2025
Facilitating Human-AI collaboration through cutting-edge AI capabilities [[File:Step 1.png |thumb|right|Image 1: The AI REDGIO 5.0 Collaborative Intelligence Platform]]
Asset Description
The AI REDGIO 5.0 Collaborative Intelligence Platform is a solution at the forefront of Industry 5.0. The idea is to combine various technological advancements to redefine industrial landscapes. The platform facilitates Human-AI collaboration by integrating cutting-edge AI capabilities. In this way, the platform is intended to illustrate the potential of connected devices, sensors, and machines through real-time data fusion and analysis, driving optimal decision-making and resource allocation.
Features
| Feature | Description |
|---|---|
| Integration of Advanced Technologies | Integration of cutting-edge technologies, including AI-driven analytics, and Internet of Things (IoT)-enabled devices to create a synergistic ecosystem |
| Human-Machine Interaction | Facilitating interaction between human operators and machines |
| Support of Real-time Operations | The platform works in tandem with real-time data analytics on IoT data |
| Continuous Learning and Knowledge Management | Storage in a knowledge-sharing and learning management repository |
| Collaborative Innovation | Fostering a culture of collaborative innovation, where human operators can interact with AI for improved processes and final product |
User Journey
Our platform adopts a practical problem-solving approach, data analysis, and process optimisation. This subsection offers a comprehensive usage walkthrough, explaining the interaction of the user with the Collaborative Intelligence Platform as a whole, and as a part of the user's MLOps operations and tools they already use.
- Onboarding and User Authentication: Ensure secure access to the system, safeguarding sensitive data and mitigating potential security breaches
- Integrating IoT and Smart Devices: The integration of IoT and smart devices using a methodology for the interconnection of heterogeneous devices
- AI-driven Data Analytics and Insights: The system can start working to detect patterns, anomalies, and trends within the data through ML algorithms
- Human-Machine Interaction and Augmentation: Coordination of actions between human operators and machines, emphasising augmentation rather than substitution
- Real-Time Process Optimisation: Automatically adjusting operational parameters in response to changing conditions and input provided by the user through the #Collaborative Intelligence Component
- Knowledge Base and Learning Management: Exploring the knowledge repository containing organisational know-how, accumulated insights, and best practices
- Collaborative Innovation and Continuous Improvement: The ultimate goal of Collaborative Intelligence: facilitating cross-functional collaboration and iterative enhancement through data analytics, human-machine collaboration, and organisational knowledge
Collaborative Intelligence Platform Components
The AI REDGIO 5.0 Collaborative Intelligence Platform is comprised of 3 underlying components.
| Component | Description | Type | Status |
|---|---|---|---|
| Collaborative Intelligence Component | Allows the human operator to accept or reject a manufactured product. This component has an interface that can be configured around various metrics including, but not limited to, accuracy, interpretability, speed, etc | User-facing | Working Prototype |
| Pipeline Creation Component | Easily create, configure, and deploy workflows in various work environments. This component acts as the backbone of a robust and efficient workflow management system, enabling organisations to optimise their processes and achieve higher productivity | User-facing | Work in Progress |
| Interfacing Component | Connects the operator interface with hardware and housing pre-trained models ready for deployment in manufacturing environments. This component acts as the bridge between the digital and physical realms of experiments | Backend | Working Prototype |
Usage Walkthroughs
How to use the AI REDGIO 5.0 Collaborative Intelligence Platform
Collaborative Intelligence Component
The human operator can assess the results of the AI/ML models and provide feedback with regards to 3 aspects (accuracy, energy-efficiency, latency) through the Collaborative Intelligence (C.I) component. The human operator's feedback is propagated back to the AI/ML analytics tool of the user to perform the relevant adjustments to the model configuration for results optimisation.
1. Entering the C.I Platform
- Navigate to the url https://github.com/AI-REDGIO-5-0/ci-component
- Enter your credentials (Note: User registration and account creation is managed by Software Competence Centre Hagenberg - SCCH)
2. Data and ML/AI results inspection
After successfully entering the platform, you are led to the C.I Dashboard, where you can review your data and provide feedback.
- Upload Data: First you need to provide the data that you want to inspect. (Note: Data are manually onboarded. In upcoming releases, the onboarding will happen through integration with the user's AI/ML tools and system.)
- Select ML/AI evaluation axis: ML/AI models can be evaluated based on various parameters. Click one of the available radio buttons (accuracy, energy-efficiency, latency) to instantiate the Table and the charts with the corresponding data and provide your feedback
- View the data: The Table is loaded with the data from the integrated dataset (containing the ML/AI results). You can select in a dropdown the ML/AI output feature that you would like to inspect.
3. Human provides feedback to AI
- Provide feedback: Check the value of the output feature per row and provide feedback on the ML/AI performance with regards to the evaluation axis you have selected. You provide feedback in the form of Yes (i.e., the ML/AI model for the specific output feature value was accurate/energy-efficient/fast) or No (i.e. the ML/AI model for the specific output feature value was not accurate/not energy-efficient/slow)
- Check the evaluation charts: The bar charts that appear on the top of the C.I Dashboard provide an overview of the ML/AI evaluation by the human operator so far
- Export findings: You can click on the option 'Print Non-OK Rows to a File' to export the rows marked as non-ok and further use them afterwards
4. AI is adjusted according to Human Feedback
Interplay with Input Analysis Tool
To further assist the data scientists and other users in making sense of their data, thus enhancing human-AI collaboration, the AI REDGIO 5.0 Collaborative Intelligence Platform works in tandem with the Input Analysis tool.
How it works
The human operator can explore through the Data Analysis Dashboard their data and perform input analysis based on user-selected aspects and thresholds to find correlations between features.
1. Upload input data to C.I Dashboard and navigate to the Data Analysis Dashboard
- Go to the main Dashboard page of the C.I Dashboard
- Click 'Choose file' and select the input data file from the directory
- Click 'Upload csv' to onboard your input data
- Click the 'Input Analysis' hyperlink to be led to the relevant tool to inspect your data
2. Perform input analysis
After clicking on the hyperlink, you are led to the Data Analysis Dashboard. Through the integration with the C.I Platform, the onboarded input data are available there in order to perform your exploration.
- Select Data Analysis aspects: Through the Data Analysis Dashboard you can select the analysis aspects, including the pairs of columns to compare, the missing value imputation method, the numeric conversion method. Additionally, you can set the thresholds for the analysis (Pearson correlation, Spearman rank correlation, Euclidean similarity)
- Review the analysis results: In the provided graphs you can see the visualised results of the analysis.
Resources
- Code available in Github
- Created by Software Competence Center Hagenberg - SCCH
- Contact jorge.martinez-gil@scch.at