CHIST-ERA Call 2023 - 14ème Appel à Projets de l'ERA-NET CHIST-ERA (Call 2023) 2024

AI integrated framework for intelligent geospatial handling and robust operation in MultiGIS applications – AI4MultiGIS

Submission summary

Summary

MultiGIS provides precise and real-time spatiotemporal data analysis, which greatly benefits various applications including environmental monitoring, sustainable development, resilience-building, and urban planning. Despite wider adoption of MultiGIS applications, there are significant challenges remaining, notably relating to data collection, generation, storage, and real-time data processing from a set of diverse heterogeneous sources within MultiGIS environments. Due to limited data availability in most of the MultiGIS applications, it is necessary to generate synthetic data to enrich MultiGIS representations. Existing GIS-backed geostatistical AI tools can address some of these challenges but are limited with spatial autocorrelation and lack plug and play integration with existing tools as well as assurance of transparency, privacy, fairness, regulatory compliance of AI-enabled MultiGIS applications.

AI4MultiGIS offers an integrated framework for MultiGIS data generation and management, which aims to enhance the overall GIS capabilities for optimised processing chain of MultiGIS applications. The project will deliver innovative solutions to collect and consolidate the data from diverse sources. It will develop techniques for automated outlier detection for reliable data processing, real-time spatiotemporal data processing for informed decision making and plug and play capabilities using a cloud-integrated AI platform for multi-modal data integration. AI4MultiGIS considers assurance of responsible AI within the AI-enabled MultiGIS applications through development and implementation of policy and best-practice guidelines. Finally, AI4MultiGIS is evaluated through two pilot case studies to demonstrate their effectiveness and wider adoption of AI4MultiGIS in different MultiGIS applications beyond the project.

Relevance to the topic addressed in the call

The AI4MultiGIS project perfectly aligns with the MultiGIS call, by enhancing overall GIS system capability through novel methods to optimise MultiGIS data collection, processing, storage, and presentation. AI4MultiGIS will develop an intelligent data pipeline for data collection and generation from diverse sources with high accuracy and reliability, blockchain-based decentralised approach to manage and share the data across multiple stakeholders. AI4MultiGIS will develop algorithms and methodologies to enhance the processing and analysis of cross-model and multi-modal GIS data and plug and play capabilities for integration of developed models with existing GIS tools to analyse real and synthetic data. Finally, development of policy and best practice will regulate the assurance of responsible AI through the life cycle of MultiGIS and assist in compliance with relevant regulation.

Project coordination

Shareeful Islam (Anglia Ruskin University)

The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.

Partnership

ARU Anglia Ruskin University
UVT West University of Timisoara
LUT Lappeenranta-Lahti University of Technology
LIUPPA LABORATOIRE D'INFORMATIQUE DE L'UNIVERSITE DE PAU ET DES PAYS DE L'ADOUR

Help of the ANR 274,443 euros
Beginning and duration of the scientific project: January 2025 - 36 Months

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