TY - GEN
T1 - Integrating AI Assistants to Advance GIS Application Usability
AU - Shahu, Ambika
AU - Cipot, Patrick
AU - Asteriou, Philipp
AU - Wintersberger, Philipp
AU - Michahelles, Florian
N1 - Publisher Copyright:
© 2025 Copyright held by the owner/author(s).
PY - 2025/11/18
Y1 - 2025/11/18
N2 - Geographic Information Systems (GIS) help users work with location data, but can be difficult to use due to poor design and complex features. The use of AI, especially through Large Language Models (LLMs), can make these systems easier to access and use. To advance the integration of AI technologies within GIS, we introduced a novel AI-driven map assistant called ’MapGPT’. We conducted a usability study with 10 participants who completed six tasks and the UEQ-S and SUS questionnaires. The findings of our study indicated that integrating LLM technology into GIS interactions via conversational interfaces proved beneficial in terms of simplifying complex processes and enhancing overall user experience. Our contributions include the demonstration of the practical application of LLMs in GIS, illustrating how AI can improve the usability of GIS tools. In light of the findings of our usability study, we provide recommendations for forthcoming map-based AI assistants.
AB - Geographic Information Systems (GIS) help users work with location data, but can be difficult to use due to poor design and complex features. The use of AI, especially through Large Language Models (LLMs), can make these systems easier to access and use. To advance the integration of AI technologies within GIS, we introduced a novel AI-driven map assistant called ’MapGPT’. We conducted a usability study with 10 participants who completed six tasks and the UEQ-S and SUS questionnaires. The findings of our study indicated that integrating LLM technology into GIS interactions via conversational interfaces proved beneficial in terms of simplifying complex processes and enhancing overall user experience. Our contributions include the demonstration of the practical application of LLMs in GIS, illustrating how AI can improve the usability of GIS tools. In light of the findings of our usability study, we provide recommendations for forthcoming map-based AI assistants.
KW - Geographic Information Systems
KW - Large Language Models
KW - Map-Based AI Assistants
KW - Usability study
KW - Voice-based Interfaces
UR - https://www.scopus.com/pages/publications/105025570030
U2 - 10.1145/3770501.3770502
DO - 10.1145/3770501.3770502
M3 - Conference contribution
T3 - IOT 2025 - Proceedings of the 15th International Conference on the Internet of Things 2025
SP - 1
EP - 8
BT - IOT 2025 - Proceedings of the 15th International Conference on the Internet of Things 2025
A2 - Nastic, Stefan
A2 - Michahelles, Florian
A2 - Ristov, Sashko
A2 - Dazzi, Patrizio
A2 - Wolling, Florian
ER -