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| Hauptverfasser: | , , , , |
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| Format: | Recurso digital |
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| Veröffentlicht: |
Zenodo
2024
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| Schlagworte: | |
| Online-Zugang: | https://doi.org/10.5281/zenodo.18161427 |
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Inhaltsangabe:
- Natural disasters, such as earthquakes, can have catastrophic effects on human lives and infrastructure. Earthquake rescue operations are challenging, often requiring rapid response to locate and rescue survivors trapped in the rubble. Detection by rescue workers becomes time consuming and due to the vast area, that gets affected it becomes more difficult. Hence a lot of times humans are buried among the debris, and it become impossible to detect them. A timely rescue can only save the people who are buried and wounded. Detection by rescue workers becomes time consuming and due to the vast area, that gets affected it becomes more difficult. So, the project proposes an autonomous robotic vehicle that moves in the earthquake prone area and helps in identifying the alive people and rescue operations. This project abstract outlines the development of an Artificial Intelligence-Based Human-Detecting Robot designed to assist in earthquake rescue missions. Key components of this project include machine learning, and Embedded design, integrated into a single platform to detect and locate humans trapped under debris during an earthquake. In this based live human detecting robot for earthquake rescue operation project, a new method for detecting surviving humans in destructed environments using simulated autonomous robot is proposed.