The integration of the Internet of Things (IoT) with AI, known as AIoT, generates vast amounts of data critical for improving AI systems and enabling smarter, more efficient operations in vital business and infrastructure areas. However, challenges such as the high costs of data collection, labour intensity, limitations in data availability and scale, and confidentiality rights restrict the availability of realistic datasets. These constraints necessitate the use of offline modelling and simulation, which struggle to accurately represent real-world environments due to variability in human behaviour and events. While Machine Learning (ML) techniques aim to bridge the gap between real and synthetic data, their application is complex without a thorough understanding of the semantics of smart spaces. Real data in usable formats for AIoT systems is often scarce, posing difficulties in training AI models. Moreover, datasets are frequently imbalanced, with common behaviours over-represented, and the dynamic nature of smart spaces requires AIoT systems to adapt continually to changes and unmodeled phenomena.

To address these challenges, the PANDORA project is developing a framework to prepare and deliver comprehensive datasets for AI models in AIoT systems, enhancing their autonomy, trustworthiness, and energy efficiency. The project objectives include advancing research excellence in resilient, transparent, and human-centered AI approaches for optimized and autonomous data processing and use. It aims to provide novel methods, mechanisms, and tools for creating customizable and trustworthy datasets for model-based AI developments, supporting robust and energy-efficient “data in AI” pipelines across the computing continuum. PANDORA also seeks to deliver a cross-sector and multi-variant smart data space to implement its framework and validate data-enabled trustworthy AI mechanisms in real-life scenarios. Furthermore, it fosters synergetic approaches within EU industrial and scientific research communities, promotes international collaboration on efficient and trustworthy AI methods, and enhances multidisciplinary competencies in industrial AI, data, and robotics while embracing open innovation.

ITML’s role in the project

ITML’s contribution to the project involves several key activities, including the generation of trustworthy and customized datasets using AI-based techniques, with a specific focus on techniques that minimize data redundancy and complexity, addressing both the raw data level and the semantic level through dimensionality reduction. Additionally, ITML coordinates data collection from the pilot sites prior to the implementation of use cases, ensuring that all activities comply with GDPR regulations through the deployment of Data Fusion Bus which will be customized and configured with respect to the end users’ needs.

For more information, visit the official project website: https://pandora-heu.eu/

Acknowledgment

The project PANDORA has received funding from the European Union’s Horizon Europe Research and Innovation Programme under the Grant Agreement No. 101135775.