This chapter presents a comprehensive utilization of unmanned aerial vehicles (UAVs) in disaster response, leveraging the YOLOv8 (You Only Look Once) object detection model for real-time human identification. The UAVs, equipped with this state-of-the-art model, efficiently capture and transmit images of human subjects to a ground station, serving as a centralized hub for further analysis. This human detection system significantly enhances situational awareness during search and rescue operations, contributing to quicker response times in disaster-stricken areas. Additionally, our UAVs are outfitted with devices designed to extend WiFi signals, thereby establishing a robust communication network in disaster zones where traditional infrastructure may be compromised. This dual-functionality approach, integrating advanced computer vision and communication technology, represents a holistic solution to the challenges faced in disaster management, positioning UAVs as versatile tools for responsive and efficient disaster response systems. This framework serves as a foundational structure, laying the groundwork for the development of more dependable, swifter disaster event detection, and energy-efficient disaster management systems based on UAV networks.


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    Titel :

    Unmanned Aerial Vehicles (UAVs) for High-Altitude Human Detection: A Review and Prospects


    Weitere Titelangaben:

    Lect. Notes in Networks, Syst.


    Beteiligte:
    Tuba, Milan (Herausgeber:in) / Akashe, Shyam (Herausgeber:in) / Joshi, Amit (Herausgeber:in) / Bhardwaj, Shaswat (Autor:in) / Agrawal, Vyom (Autor:in) / Vats, Prashant (Autor:in)

    Kongress:

    International Conference on ICT for Sustainable Development ; 2024 ; Goa, India August 08, 2024 - August 09, 2024



    Erscheinungsdatum :

    03.05.2025


    Format / Umfang :

    12 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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