TRIFFID: Autonomous Robotic Aid For Increasing First Responders Efficiency
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F25%3A43976563" target="_blank" >RIV/49777513:23520/25:43976563 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/11166443/" target="_blank" >https://ieeexplore.ieee.org/document/11166443/</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/EEITE65381.2025.11166443" target="_blank" >10.1109/EEITE65381.2025.11166443</a>
Alternative languages
Result language
angličtina
Original language name
TRIFFID: Autonomous Robotic Aid For Increasing First Responders Efficiency
Original language description
The increasing complexity of natural disaster incidents demands innovative technological solutions to support first responders in their efforts. This paper introduces the TRIFFID system, a comprehensive technical framework that integrates unmanned ground and aerial vehicles with advanced artificial intelligence functionalities to enhance disaster response capabilities across wildfires, urban floods, and post-earthquake search and rescue missions. By leveraging state-of-the-art autonomous navigation, semantic perception, and human-robot interaction technologies, TRIFFID provides a sophisticated system composed of the following key components: hybrid robotic platform, centralized ground station, custom communication infrastructure, and smartphone application. The defined research and development activities demonstrate how deep neural networks, knowledge graphs, and multimodal information fusion can enable robots to autonomously navigate and analyze disaster environments, reducing personnel risks and accelerating response times. The proposed system enhances emergency response teams by providing advanced mission planning, safety monitoring, and adaptive task execution capabilities. Moreover, it ensures real-time situational awareness and operational support in complex and risky situations, facilitating rapid and precise information collection and coordinated actions.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20205 - Automation and control systems
Result continuities
Project
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Continuities
R - Projekt Ramcoveho programu EK
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2025 6th International Conference in Electronic Engineering & Information Technology (EEITE)
ISBN
979-8-3315-4419-5
ISSN
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e-ISSN
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Number of pages
9
Pages from-to
1-9
Publisher name
IEEE
Place of publication
Chania
Event location
Chania
Event date
Jun 4, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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