Design Of Rubble Analyzer Probe Using ML For Earthquake
Abhishek Sebastian, R Pragna, K Vishal Vythianathan, Dasaraju Sohan Sai, U Shiva Sri Hari Al, R Anirudh, Apurv Choudhary
arXiv:2311.02087v13 citationsh-index: 3
Originality Synthesis-oriented
AI Analysis
This addresses the critical need for efficient post-earthquake rescue operations to save trapped individuals, though it appears incremental as it applies existing ML methods to a new domain.
The paper tackles the problem of detecting human presence in earthquake rubble using ambient sounds, achieving 97.45% accuracy, and provides real-time environmental data to aid rescue efforts.
The earthquake rubble analyzer uses machine learning to detect human presence via ambient sounds, achieving 97.45% accuracy. It also provides real-time environmental data, aiding in assessing survival prospects for trapped individuals, crucial for post-earthquake rescue efforts