Prototypes of intelligent robots for first aid in natural disasters: A bibliometric analysis

Setiawan, Johan (2025) Prototypes of intelligent robots for first aid in natural disasters: A bibliometric analysis. Multidisciplinary Reviews, 9 (7). ISSN 2595-3982

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Abstract

The increasing frequency and complexity of natural disasters have intensified global demand for intelligent robotic systems that can support first aid and emergency response. This study presents a systematic literature review (SLR) and bibliometric analysis of research on smart robots applied to disaster scenarios. Using the Scopus database, 153 records were initially retrieved with the keywords “disaster” and “smart robot.” After applying PRISMA-based screening and inclusion criteria, 54 peer-reviewed publications were analyzed using the Bibliometrix R package. The analysis identifies key trends in robotic technologies, artificial intelligence algorithms, and design innovations for disaster response. Results highlight the growing research emphasis on unmanned aerial vehicles (UAVs), ground and snake robots, and the integration of sensors, IoT, and machine learning for real-time victim detection and navigation. Despite notable technological progress, critical challenges persist in field deployment, robot coordination, and human–robot interaction in crisis settings. This study contributes to the disaster robotics field by synthesizing existing knowledge, identifying underexplored areas, and proposing research directions to enhance the operational effectiveness of robotic systems in future emergencies.

Item Type:	Article
Creators:	Setiawan, Johan
Contributors:
Keywords:	disaster robotics first aid unmanned systems AI algorithms bibliometric analysis systematic review
Subjects:	600 Technology (Applied Sciences) > 620 Engineering > 629 Other Branches of Engineering (Aerospace, Aviation, Astronautics, Robotics)
Divisions:	Faculty of Engineering & Informatics > Information System
Date Deposited:	03 Feb 2026 08:58
URI:	https://kc.umn.ac.id/id/eprint/44535

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