The deliverable D3.2 “Scalability and edge computing optimization” presents the updates of the heterogeneous IoT data sources encountered in the three pilots of the AD4GD project. The first pilot concerns the water quantity and quality in the lakes located in Berlin, Germany. The second pilot studies the biodiversity in the region of Catalonia. Finally, the third pilot is dedicated to the air quality. All the pilots are using IoT data and different components and building blocks were developed during the AD4GD project. The updates of these components are described in this deliverable. Furthermore, the SIMPL middleware initiative is also discussed in the deliverable D3.2. The edge computing is an important part of the Internet of Things in the context of the AD4GD project: this topic is presented in a dedicated chapter where different Key Performance Indicators (KPIs) related to edge computing are specified. Finally, some actions to improve these KPIs are proposed, followed by several recommendations.

This deliverable builds upon D5.1 and outlines progress in applying Artificial Intelligence and High-Performance Computing within the AD4GD project. It details the use of AI models in pilot studies, such as water level prediction in Berlin lakes and connectivity mapping in Catalonia, highlighting the AI models ability to process complex environmental data efficiently. The document also presents the development of user-friendly interfaces that make these advanced tools accessible to non-expert stakeholders, promoting informed decision-making. Additionally, it reports on the integration of HPC resources to support AI model training and execution, enhancing performance and scalability. The deliverable concludes with reflections on the benefits, limitations, and future directions of these technologies in AD4GD pilots.