SARGPT: a tailored AI tool with a custom-designed interface for enhancing search and rescue teams' performance

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Tutor / Supervisor

Student

Kurnaz, Ozkan Berk

Document type

Master thesis

Date

2024

rights

Open AccessOpen Access

Publisher

Universitat Politècnica de Catalunya



Abstract

This thesis presents the design and development of an intuitive, user-friendly application specifically tailored for critical search and rescue (SAR) operations. The primary focus of this research is the integration of artificial intelligence (AI) to enhance the efficiency and effectiveness of SAR teams. By automating data processing and task management, the application aims to reduce the cognitive load on personnel, allowing them to perform their duties more efficiently under stressful and time-sensitive conditions. Key features of the application include a user-centric interface designed to ensure ease of use, even in high-pressure scenarios. The visual design incorporates clear and comprehensible icons, calming color schemes, and an efficient layout that allows for quick access to essential functions. Offline capabilities ensure that SAR teams can access critical information and tools even in remote areas without connectivity. Additionally, AI-supported automated processes such as form filling and task allocation significantly reduce administrative burdens, thereby increasing the speed and accuracy of operations. The application also includes continuous training and development support, providing SAR personnel with personalized learning paths to continuously improve their skills and knowledge. This integration of AI technologies and user-friendly interface design aims to streamline communication, enhance decision-making, and improve operational outcomes during critical incidents. In conclusion, the study demonstrates that the incorporation of AI-enhanced, user-centric interfaces can substantially improve the operational efficiency and effectiveness of SAR operations. The insights gained from this research offer valuable contributions to the future design and implementation of AI-driven tools for emergency response applications.
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