The Mobilising Agenda ATE – Alliance for Energy Transition aims to strengthen the competitiveness and resilience of companies in the energy sector by creating innovative and export-oriented products and solutions. This initiative is based on the technology and expertise developed and consolidated within the sector, positioning Portugal at the forefront of decarbonisation and fostering an effective energy transition.

Together with the other project partners, the CCG/ZGDV is laying the foundations for the development of the interoperable platform “AIIoT,” which will facilitate data exchange and the creation of digital services in a collaborative framework aimed at reducing costs and technological complexity. This platform will enable the integration of different cloud providers in a multi-tenant environment (multiple users), allowing various stakeholders to develop, test, and deploy innovative solutions in an agile and efficient manner.

The CCG/ZGDV plays a central role in this project by developing several modules that ensure the platform's functionality and effectiveness (Fig. 1). Notably, the Data Collection Module ensures the automation of information flow from different sources, such as IoT sensors and heterogeneous databases. This module is essential to guarantee the efficient capture of relevant data for energy management.

Another key contribution is the Data Pre-Processing and Standardisation Module, which structures and organises data to ensure its quality, eliminating inconsistencies and ensuring compliance with international standards such as NGSI-LD and Smart Data Models. In addition, the Distributed Query Engine, also developed by CCG/ZGDV, optimises the execution of queries over large volumes of data, enabling parallel and distributed processing without the need for replication, thereby improving system efficiency.

Regarding Artificial Intelligence (AI), CCG/ZGDV is implementing modules for “AI Model Training and Validation”, which are essential for optimising energy management. These models are trained using large datasets and validated to ensure their effectiveness in real-world scenarios. Furthermore, “Model Monitoring and Maintenance” mechanisms are being developed to ensure the ongoing effectiveness of the algorithms used over time and their adaptation to changes in the energy sector.

 

With these contributions, a robust, flexible, and accessible platform is being established. This platform will facilitate the adoption of digital services by companies of various sizes, thereby reducing costs and technological complexity. The ATE project, as a whole, not only drives innovation but also democratises access to digital solutions, enabling an inclusive and sustainable digital transformation in the energy sector.

 

By: Tiago Pereira, Senior Researcher EPMQ (Software Engineering and Data Intelligence)