Reference and Solution Architecture for GenAI- and GIS-Enhanced
Physical Activity Interventions: Towards Implementing the
AI4Motion Platform

J 2025

Reference and Solution Architecture for GenAI- and GIS-Enhanced Physical Activity Interventions: Towards Implementing the AI4Motion Platform

DOLEŽEL, Michal a Radim LÍSKOVEC

Základní údaje

Originální název

Reference and Solution Architecture for GenAI- and GIS-Enhanced Physical Activity Interventions: Towards Implementing the AI4Motion Platform

Autoři

DOLEŽEL, Michal a Radim LÍSKOVEC

Vydání

Journal of Medical Systems, Springer, 2025, 0148-5598

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

30304 Public and environmental health

Stát vydavatele

Spojené státy

Utajení

není předmětem státního či obchodního tajemství

Odkazy

URL

Impakt faktor

Impact factor: 5.700 v roce 2024

Označené pro přenos do RIV

Organizační jednotka

Přírodovědecká fakulta

Klíčová slova anglicky

LLM; LBS; API; LLaMA; Digital Health Intervention; Geofencing

Štítky

RIV ne

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 26. 11. 2025 10:24, Mgr. Marie Novosadová Šípková, DiS.

Anotace

V originále

Digital Behaviour Change Interventions (DBCIs) aim at improving individual health by engaging various means of Information and Communication Technology (ICT), including mobile apps and wearables. Participant intervention fatigue may happen when DBCIs become too frequent, repetitive, demanding, or lack perceived relevance, and this may result in participants’ reduced motivation and adherence over time. Advancing technology-supported engagement mechanisms is therefore of utmost importance. To address this problem, we present a reference and solution architecture based on open-source technologies and open Application Programming Interfaces (Open APIs). First, we integrated a Large Language Model (LLM) component into the DBCI design. Second, to support context-awareness, we enhanced this integration by adding a Geographic Information Systems (GIS) element. Our pilot implemented AI4Motion platform targets both personalization and contextualization aspects of DBCIs. Our work contributes to the emerging discussion on LLM/GIS-related system design patterns for digital platforms supporting Ecological Momentary Assessment (EMA), Experience Sampling Method (ESM), and Just-in-Time Adaptive Interventions (JITAIs).

Citovat

DOLEŽEL, Michal a Radim LÍSKOVEC. Reference and Solution Architecture for GenAI- and GIS-Enhanced Physical Activity Interventions: Towards Implementing the AI4Motion Platform. Journal of Medical Systems. Springer, 2025, roč. 49, č. 1, s. 150-155. ISSN 0148-5598. Dostupné z: https://doi.org/10.1007/s10916-025-02269-x.

@article{2529465,
   author = {Doležel, Michal and Lískovec, Radim},
   article_number = {1},
   doi = {https://doi.org/10.1007/s10916-025-02269-x},
   keywords = {LLM; LBS; API; LLaMA; Digital Health Intervention; Geofencing},
   language = {eng},
   issn = {0148-5598},
   journal = {Journal of Medical Systems},
   note = {R. Lískovec bude publikaci vykazovat pouze za OSU. Nevykazovat do RIV za PřF MU. Domluveno dne 26.11.2025.},
   title = {Reference and Solution Architecture for GenAI- and GIS-Enhanced Physical Activity Interventions: Towards Implementing the AI4Motion Platform},
   url = {https://link.springer.com/article/10.1007/s10916-025-02269-x},
   volume = {49},
   year = {2025}
}

TY  - JOUR
ID  - 2529465
AU  - Doležel, Michal - Lískovec, Radim
PY  - 2025
TI  - Reference and Solution Architecture for GenAI- and GIS-Enhanced Physical Activity Interventions: Towards Implementing the AI4Motion Platform
JF  - Journal of Medical Systems
VL  - 49
IS  - 1
SP  - 150
EP  - 150
PB  - Springer
SN  - 01485598
N1  - R. Lískovec bude publikaci vykazovat pouze za OSU. Nevykazovat do RIV za PřF MU. Domluveno dne 26.11.2025.
KW  - LLM
KW  - LBS
KW  - API
KW  - LLaMA
KW  - Digital Health Intervention
KW  - Geofencing
UR  - https://link.springer.com/article/10.1007/s10916-025-02269-x
N2  - Digital Behaviour Change Interventions (DBCIs) aim at improving individual health by engaging various means of Information and Communication Technology (ICT), including mobile apps and wearables. Participant intervention fatigue may happen when DBCIs become too frequent, repetitive, demanding, or lack perceived relevance, and this may result in participants’ reduced motivation and adherence over time. Advancing technology-supported engagement mechanisms is therefore of utmost importance. To address this problem, we present a reference and solution architecture based on open-source technologies and open Application Programming Interfaces (Open APIs). First, we integrated a Large Language Model (LLM) component into the DBCI design. Second, to support context-awareness, we enhanced this integration by adding a Geographic Information Systems (GIS) element. Our pilot implemented AI4Motion platform targets both personalization and contextualization aspects of DBCIs. Our work contributes to the emerging discussion on LLM/GIS-related system design patterns for digital platforms supporting Ecological Momentary Assessment (EMA), Experience Sampling Method (ESM), and Just-in-Time Adaptive Interventions (JITAIs).
ER  -

DOLEŽEL, Michal a Radim LÍSKOVEC. Reference and Solution Architecture for GenAI- and GIS-Enhanced Physical Activity Interventions: Towards Implementing the AI4Motion Platform. \textit{Journal of Medical Systems}. Springer, 2025, roč.~49, č.~1, s.~150-155. ISSN~0148-5598. Dostupné z: https://doi.org/10.1007/s10916-025-02269-x.

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