AI-Driven Analysis of Heterogeneous Wastewater Network Data

This presentation explores the analysis of heterogeneous geospatial data from various sources through the application of artificial intelligence (AI) tools. Wastewater networks are used as a case study to address challenges such as data completion, multi-source integration, and managing diverse data formats, including Geographic Information Systems (GIS), analog maps, and pipe inspection videos, all derived from real-world data. We will review some solutions developed under the European project Starwars (STormwAteR and WastewAteR networkS heterogeneous data AI-driven management). These solutions are based on innovative models and tools that employ logical and graph-based representations of heterogeneous data. Specifically, we aim to represent different data types — such as GIS, ITV inspection videos, and maps — as annotated graphs, incorporating the uncertainty stemming from incomplete or inconsistent information.