EventsThe 5th International Electronic Conference on Applied Sciences
Published
This submission belongs to the session S4. Electrical, Electronics and Communications Engineering of the event The 5th International Electronic Conference on Applied Sciences
Published date
04 Dec, 2024
Academic Editor
author-avatarFrancesco Arcadio
Citation
Aviegail Bacudo Bobadilla, Gabriel Lyane Pating Arevalo, Rajan Mole del Castillo Macaraig, Felix Christofer Guzman Valdez, Eufemia Acol Garcia, Charles Garces Juarizo, Unmanned Amphibious Robot in Aiding Post-typhoon Heavy Flooding Response Using LoRa-based Communication and YOLOv5, in Proceedings of The 5th International Electronic Conference on Applied Sciences, 4 December–6 December 2024, MDPI: Basel, Switzerland
Share
Email
Facebook
Twitter
LinkedIn

Unmanned Amphibious Robot in Aiding Post-typhoon Heavy Flooding Response Using LoRa-based Communication and YOLOv5

Gabriel Lyane Pating Arevalo 1
Rajan Mole del Castillo Macaraig 1
Felix Christofer Guzman Valdez 1
1. Department of Electronics Engineering, Pamantasan ng Lungsod ng Maynila, Philippines
Abstract

In the Philippines, about twenty (20) typhoons occur annually, causing heavy flooding which poses risks that lead to injuries and casualties despite preparedness measures. This study addresses the problem of hindered rescue efforts due to limited resources, dangerous access to flooded areas, and damaged communication infrastructures by introducing an innovative solution: an unmanned amphibious robot for search and monitoring tasks. The developed robot is capable of locating human presence and help needed while providing a live video feed. Evaluations demonstrated the capabilities of the robot to navigate both on land and water with respective speeds of 1.2 m/s and 0.205 m/s over a 120-m LoRa communication. The live video feed quality highlights the feasibility of a 4G LTE network for real-time display. The trained YOLOv5 model had high accuracy in detecting human presence and help needed over 3.5m and 7m distances with 90% and 93.33%, respectively. GPS coordinate reception yields good results in open areas only. There was also a seamless integration of data from the robot to the local website, offering accessible data. Limitations arose when live video feed streaming and YOLOv5 processing were performed simultaneously. This research contributes to aiding post-typhoon heavy flooding response by developing an unmanned amphibious robot, offering insights into its performance and potential for real-world applications in disaster response scenarios.

Keywords
heavy flooding
LoRa
machine learning
Unmanned Amphibious Robot
Poster
UAR-Poster-ASEC-2024-Conference.pdf
Complex electrochemical assessment of the antioxidant properties of essential oils
Application of image analysis in the assessment of ‘Mejhoul’ date fruit quality under freezing storage.