Design Of Rubble Analyzer Probe Using ML For Earthquake

TL;DR

This paper presents a machine learning-based rubble analyzer probe that detects human presence through ambient sounds with high accuracy and provides real-time environmental data to assist earthquake rescue operations.

Contribution

It introduces a novel ML-powered rubble analyzer probe capable of detecting trapped individuals and environmental conditions during earthquakes.

Findings

Achieved 97.45% accuracy in human presence detection.

Provides real-time environmental data for rescue efforts.

Enhances post-earthquake rescue decision-making.

Abstract

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