Work package 3

Human-centric interaction and data exploration

Objectives

To handle unskilled IT end-users and complex IoRT devices, data and analytics methods, this WP proposes a set of methods based on intuitive interaction techniques to remotely control IoRT devices and allow end-users to easily explore data, and enable an understandable restitution of analysis results. Gender + aspects are investigated in this WP.

Task 3.1 Devices interaction

This task will propose: Intuitive interactive visual interfaces allowing unskilled IoRT end-users to visualize robots and sensors activities, by means of (advanced) geovisualization methods; New interaction methods based on new visual query engines and chatbots based on AI (such as LLM) for robots control.

Task 3.2 Findability and explainability

It proposes methods for allowing IT unskilled end-users to query complex and heterogeneous data, by means of (i) new visualization paradigms, (ii) gender inclusive LLM methods. Moreover, the analysis methods based on AI are accompanied with explainable AI techniques, making AI models more transparent and interpretable

Task 3.3 Interaction architectures

Different edge-fog cloud architectures will be tested to grant real-time performances according to once proposed in Task 1.3 and 2.3.

Task 3.4 Experiments

Proposals will be put to the test against real data and with real end-users.

Task 3.5 Gender+ Interaction, Visualization, and Language Processing Method

This task focuses on designing interaction methods, interfaces, explainability approaches, and LLM solutions that integrate both quantitative and qualitative gender+ inclusion variables. It proposes innovative, gender-inclusive visualization and interface design methods, along with quantitative gender+ scores to evaluate the inclusivity of the resulting products.It will also propose strategies for choosing end-users and designing experiments and tests with gender+awareness.