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Enhancing GIS With Artificial Intelligence

AI Integrated Framework for Intelligent Geospatial Handling and Robust Operation in MultiGIS Applications (AI4MultiGIS)

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MultiGIS | AI Principles | Trustworthy

MultiGIS Process

Data
Collection

Remote sensing, GPS surveys, and environmental sensors.

Data
Integration

Cloud storage, big data management, and spatial databases.

Multidimensional Processing

2D/3D spatial analysis, spectral analysis, and AI-based pattern recognition.

Visualization Modeling

Interactive maps, simulations, and augmented reality.

Decision-Making Implementation

Smart policy development and strategic planning.

Key Objectives

Objectives of AI4MultiGIS

The AI4MultiGIS project aims to deliver an integrated framework that optimizes the processing chain of MultiGIS data to support robust operations of GIS-enabled applications and services.

Automated Data Collection & Preprocessing

  • Develop AI-driven approaches to integrate real-time IoT data, remote sensing insights, and diverse datasets.
  • Address challenges in spatial data accuracy, synchronization, and inconsistencies.
  • Reduce data integration time by at least 30% and uncertainty levels by 20%​.

Real-Time Spatiotemporal Data Processing

  • Implement a federated reinforcement learning framework for processing vast multi-dimensional geospatial data.
  • Optimize computing efficiency for faster decision-making and response time.

Geostatistical AI Analysis & Decision Support

  • Develop a cloud-integrated AI platform for multi-modal GIS data interpretation.
  • Enhance predictive analytics capabilities using machine learning models.

Responsible AI Governance & Policy Development

  • Establish policies and best practices to ensure the fairness, transparency, and compliance of AI-enabled MultiGIS applications with the EU AI Act and other global regulations.
  • Improve fairness in decision-making by at least 50%​.

Work Packages | Deliverables

Project Update

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Session 1: Analyzing the Past Using GIS and AI

Speaker: Prof. Marc Frincu (West University of Timisoara, Romania)

  • Harnessing multispectral satellite images for archaeology & climate research
  • Semi-automated skyscape analysis using AI
  • Applications in heritage preservation and site classification

Session 2: Preventing Inference Attacks in Crowdsourcing

Speaker: Prof. Richard Chbeir (University of Pau and Pays de l’Adour, France)

  • Addressing privacy risks in geolocated data sharing
  • Context-aware anonymization using Bayesian networks
  • Protecting personal data while preserving utility in urban and mobility analysis

 

Events

Past Event

AI for MultiGIS Workshop

  • May 8, 2025 | 14:00–16:00
  • Vanue: LAB307, Anglia Ruskin University, Cambridge, UK
  • Topics: Analyzing the Past Using GIS and AI | Preventing Inference Attacks in Crowdsourcing
Agenda

Upcoming Event

AI-Driven MultiGIS 2025 Workshop

  • Submission deadline: August 20, 2025
  • Acceptance notification: September 05, 2025
  • Workshop Date: November 24, 2025
Workshop
Event Details
AI4MultiGIS is an innovative framework designed to optimize the processing chain of MultiGIS data, ensuring robust GIS-enabled applications and services.
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Important

Contact US

  • Project Coordinator: Associate Prof. Shareeful Islam
  • shareeful.islam@aru.ac.uk
  • School of Computing and Information Science, Cambridge Campus
    Anglia Ruskin University, East Rd, Cambridge CB1 1PT, UK

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