Proceedings of the 8th FIRST 2024 International Conference on Global Innovations (FIRST-ESCSI 2024 )

<Previous Article In Volume
Next Article In Volume>

Yolo Method and Wifi Signal Capture on Drones to Detect Missing Victims

Authors
R. A. Halimatussa’diyah1, Sholihin Sholihin1, *, Mutiar Mutiar1, Eka Susanti1
1Politeknik Negeri Sriwijaya, Srijaya Negara Stret, Palembang, 30139, Indonesia
*Corresponding author. Email: sholihin@polsri.ac.id
Corresponding Author
Sholihin Sholihin
Available Online 1 May 2025.
DOI
10.2991/978-94-6463-678-9_5How to use a DOI?
Keywords
Drone; Raspberry Pi; Camera; Yolo Method; Global Positioning System; nodemcu ESP8266; arduino IDE; telegram
Abstract

Increasingly developing technology has opened up new opportunities in various aspects of life, including in military operations. The research focuses on developing to detect Yolo and Wifi signals using drones as a search and rescue tool for missing soldiers on the field of operations. The loss of a soldier on a military mission poses a great risk to both the missing individual and the rescue team. Therefore, technological solutions that are able to provide fast and accurate results are needed. The method developed involves the use of Raspberry Pi devices and cameras on drones to take real-time images and Wifi signal capture and Nodemcu ESP8266 on drones supported by Global Positioning System processes to improve location tracking. The system works by detecting images from Raspberry Pi devices and WiFi signals from Nodemcu ESP8266 devices carried by soldiers the Telegram application to get victim coordination. Therefore, it aims to increase responsiveness and effectiveness in rescuing victims of missing soldiers on the battlefield, through the application of advanced Yolo technology and the integration of real-time communication.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the 8th FIRST 2024 International Conference on Global Innovations (FIRST-ESCSI 2024 )
Series
Advances in Engineering Research
Publication Date
1 May 2025
ISBN
978-94-6463-678-9
ISSN
2352-5401
DOI
10.2991/978-94-6463-678-9_5How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - R. A. Halimatussa’diyah
AU  - Sholihin Sholihin
AU  - Mutiar Mutiar
AU  - Eka Susanti
PY  - 2025
DA  - 2025/05/01
TI  - Yolo Method and Wifi Signal Capture on Drones to Detect Missing Victims
BT  - Proceedings of the 8th FIRST 2024 International Conference on Global Innovations (FIRST-ESCSI 2024 )
PB  - Atlantis Press
SP  - 45
EP  - 49
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-678-9_5
DO  - 10.2991/978-94-6463-678-9_5
ID  - Halimatussa’diyah2025
ER  -