AUTONOMOUS SEARCH AND RESCUE DRONE WITH REAL-TIME YOLO OBJECT DETECTION AND GPS NAVIGATION USING RASPBERRY PI 4

Ulpan Turmaganbet; Dana Turlykozhayeva; Sayat Akhtanov; Symbat Temesheva; Nurzhan Ussipov; Mingliang Tao

doi:10.31489/2026N3/116-125

Authors

Ulpan Turmaganbet PhD student, Department of Physics and Technology, al-Farabi Kazakh National University, Almaty, Kazakhstan
Dana Turlykozhayeva PhD, Researcher, Lecturer, Department of Physics and Technology, al-Farabi Kazakh National University, Almaty, Kazakhstan
Sayat Akhtanov PhD, Researcher, Senior Lecturer, Department of Physics and Technology, al-Farabi Kazakh National University , Almaty, Kazakhstan
Symbat Temesheva PhD student, Department of Physics and Technology, al-Farabi Kazakh National University, Almaty, Kazakhstan
Nurzhan Ussipov PhD, Researcher, Lecturer, Department of Physics and Technology, al-Farabi Kazakh National University, Kazakhstan
Mingliang Tao PhD, Researcher, Professor, School of Electronics and Information, Northwestern Polytechnical University, Xian, China

DOI:

https://doi.org/10.31489/2026N3/116-125

Keywords:

Unmanned aerial vehicles, search and rescue, object detection, computer vision, autonomous navigation, embedded systems, real-time processing

Abstract

The development of intelligent unmanned aerial vehicles with onboard computer vision capabilities is increasingly relevant to search and rescue operations. However, real-time human detection on compact UAV platforms remains challenging due to limited computational resources, varying environmental conditions, and the small size of distant targets. This study presents a UAV-based human detection and localization system integrating a Raspberry Pi 4 Model B, YOLOv8, and u-blox NEO-M8N GPS. The system performs onboard processing of the video stream and associates detected targets with the UAV's geographical position. The YOLOv8 model was trained using the VisDrone2019-DET dataset and evaluated through real-world flight experiments under different distances, altitudes, and lighting conditions. The system achieved an average detection confidence of 0.67, with a maximum confidence of 0.81, and a real-time processing speed of 4–8 FPS. Human targets were detected at distances of up to 30 m, while GPS positioning errors ranged from 1.6 to 2.8 m, with a mean error of approximately 2.12 m. The results demonstrate the capability of the proposed UAV platform to perform onboard human detection and GPS-based localization in real-time, providing a basis for UAV-assisted search and rescue applications.

Author's detail

Ulpan Turmaganbet, PhD student, Department of Physics and Technology, al-Farabi Kazakh National University, Almaty, Kazakhstan

Turmaganbet, Ulpan - PhD student, Department of Physics and Technology, al-Farabi Kazakh National University, Almaty, Kazakhstan; https://orcid.org/0009-0002-3782-425X ; uturmaganbet@gmail.com

Dana Turlykozhayeva, PhD, Researcher, Lecturer, Department of Physics and Technology, al-Farabi Kazakh National University, Almaty, Kazakhstan

Turlykozhayeva, Dana - PhD, Researcher, Lecturer, Department of Physics and Technology, al-Farabi Kazakh National University, Almaty, Kazakhstan; https://orcid.org/0000-0002-7326-9196; turlykozhayeva.dana@kaznu.edu,kz

Sayat Akhtanov, PhD, Researcher, Senior Lecturer, Department of Physics and Technology, al-Farabi Kazakh National University , Almaty, Kazakhstan

Akhtanov, Sayat - PhD, Researcher, Senior Lecturer, Department of Physics and Technology, al-Farabi Kazakh National University , Almaty, Kazakhstan; https://orcid.org/0000-0002-9705-8000; akhtanov.sayat@kaznu.edu.kz

Symbat Temesheva, PhD student, Department of Physics and Technology, al-Farabi Kazakh National University, Almaty, Kazakhstan

Temesheva, Symbat - PhD student, Department of Physics and Technology, al-Farabi Kazakh National University, Almaty, Kazakhstan; https://orcid.org/0009-0000-2795-9586; temesheva_symbat4@live.kaznu.kz

Nurzhan Ussipov, PhD, Researcher, Lecturer, Department of Physics and Technology, al-Farabi Kazakh National University, Kazakhstan

Ussipov, Nurzhan – PhD, Researcher, Lecturer, Department of Physics and Technology, al-Farabi Kazakh National University, Kazakhstan; https://orcid.org/0000-0002-2512-3280; ussipov.nurzhan@kaznu.kz

Mingliang Tao, PhD, Researcher, Professor, School of Electronics and Information, Northwestern Polytechnical University, Xian, China

Mingliang, Tao - PhD, Researcher, Professor, School of Electronics and Information, Northwestern Polytechnical University, Xian, China, https://orcid.org/0000-0002-0329-7124; mltao@nwpu.edu.cn

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AUTONOMOUS SEARCH AND RESCUE DRONE WITH REAL-TIME YOLO OBJECT DETECTION AND GPS NAVIGATION USING RASPBERRY PI 4