GISAI2025: AI-Driven MultiGIS 2025 Ho Chi Minh, Viet Nam, November 24, 2025

Conference website	https://hakiri.github.io/GISAI2025/
Submission link	https://easychair.org/conferences/?conf=gisai2025
Submission deadline	August 20, 2025

The main goal of this workshop is to advance the development of scalable, high-performance GIS systems by exploring novel software, hardware, and architectural solutions. A key focus is on leveraging AI-driven techniques for data integration, outlier detection, and multi-source data consolidation to enhance the accuracy and reliability of GIS applications.

The workshop will also address the ethical and regulatory challenges of AI in GIS, promoting transparency, privacy, fairness, and compliance through interdisciplinary collaboration. Additionally, it will highlight the role of GIS-backed geostatistical AI analysis in risk management, urban planning, and environmental monitoring. Participants will discuss innovative data management approaches, including novel database systems and the integration of IoT and robotic data into GIS platforms.

The workshop will also explore real-time and edge computing solutions for spatiotemporal data processing in field applications. A strong emphasis will be placed on fostering open-source development and community engagement, ensuring accessibility, interoperability, and cross-disciplinary collaboration to drive future innovations in GIS technology. 

Submission Guidelines

All papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome:

• Submissions must be in an electronic form as PDF format and should be uploaded using the conference website. The submitted paper should be at most 8-12 printed pages, following the Communications in Computer and Information Science (Springer CCIS) format.
• Posters describing innovative aspects of MultiGIS are also welcome. The authors have to accommodate 4 to 6 pages paper describing their contribution

List of Topics

• Scalable Architectures and Performance Optimization for GIS 

  • Novel software and hardware solutions to enhance GIS performance 

  • High-performance computing (HPC) and cloud-based GIS systems 

  • Edge computing for real-time spatiotemporal data processing 

  • Scalable GIS architectures for big data applications 

• AI-Driven Data Integration and Outlier Detection 

  • Automatic tools for detecting outliers and consolidating data from multiple sources 

  • AI and machine learning for geospatial data cleaning and validation 

  • Multi-source data fusion techniques for GIS applications 

  • Handling heterogeneous data in GIS: challenges and solutions 

• GIS for Risk Management and Urban/Rural Planning 

  • AI-backed geostatistical analysis for risk assessment and disaster management 

  • GIS applications in smart cities and sustainable urban planning 

  • Monitoring climate change and environmental risks using GIS and AI 

  • Rural development and precision agriculture with GIS 

• Policy, Ethics, and Best Practices in AI for GIS 

  • Ensuring transparency, privacy, and fairness in GIS-based AI applications 

  • Regulatory compliance and certification of AI-driven GIS tools 

  • Cross-disciplinary approaches for ethical GIS applications 

  • Developing guidelines for responsible geospatial AI deployment 

• Next-Generation Data Management for GIS 

  • Novel database systems for efficient storage and retrieval of GIS data 

  • Integration of IoT and robotic data with GIS platforms 

  • Semantic data modeling for GIS applications 

  • Knowledge management systems for large-scale geospatial data 

• Real-Time GIS and Edge Computing 

  • AI-driven real-time GIS analytics for decision-making 

  • Edge computing solutions for spatiotemporal data processing in the field 

  • GIS-enabled IoT networks for smart infrastructure 

  • Challenges and solutions for handling large-scale GIS data on the edge 

• Open-Source GIS Tools and Community Engagement 

  • Developing open-source GIS platforms and tools 

  • Enhancing accessibility and interoperability in GIS software 

  • Community-driven approaches to GIS tool development 

Committees

Program Committee

• Bassem Sallemi, Université de Perpignan Via Domitia, France

• Ibrahim Javed, The University of British Columbia, Canada

• Wolfgang Arendt, Chalmers University of Technology, Germany

Organizing committee

• - Shareeful Islam Anglia Ruskin University, UK
• - Maryam Iman Anglia Ruskin University, UK
• - Akram Hakiri University of PAU & Pays de l'Adour, France
• - Marc Frincu Universitatea de Vest din Timișoara, Romania

Invited Speakers

• Speaker 1
• Speaker 2
• Speaker 3

Publication

• Submissions must be in an electronic form as PDF format and should be uploaded using the conference website. The submitted paper should be at most 8-12 printed pages . Papers that fail to comply with length limit will be rejected. Submissions will be peer-reviewed by at least 3 peer reviewers. After the preliminary notification date, authors rebut by evidence and arguments all reviewer inquiries and their comments. Based on the rebuttal feedback, reviewers notify authors with the final decision. Selection criteria will include: relevance, significance, impact, originality, technical soundness, and quality of presentation. Preference will be given to submissions that take strong or challenging positions on important emergent topics related to Digital Ecosystems. At least one author should attend the conference to present the paper.

• Publication: The conference Proceedings will be published and indexed by the Communications in Computer and Information Science (Springer CCIS) .
• Submission: All paper submissions for MEDES-2025 will be via Easychair .

Venue

The conference will be held in Ho chi minh, Vietnam in conjunction with MEDES-2025: https://hakiri.github.io/GISAI2025/

Contact

All questions about submissions should be emailed to Akram Hakiri <akram.hakiri@gmail.com>

Sponsors