Citation

Rajeswari R, Surendra B, Dhilipkumar D, Krishnan SG. Int. J. Eng. Technol. Manage. Sci. 2022; 6(5): 80-87.

Copyright

(Copyright © 2022, International Journal of Engineering Technology and Management Sciences)

DOI

10.46647/ijetms.2022.v06i05.011

PMID

unavailable

Abstract

People who work in mining locations put their lives on the line for valuable resources; landslides and the emission of hazardous gases are the leading causes of worker fatality. In general, underground mining is far more perilous than surface mining. The landslide occurs in a matter of seconds, and although warning surface mine employees is simple, informing underground mining personnel is complicated and has a low likelihood of escape. The proposed solution for our project is to use deep learning technology to monitor and anticipate landslides. It does an amount analysis of the mining zone, which is backed by IoT sensors that monitor the landslide. A trained model is developed and fed into the computer system. By predictive analysis, the system issues an alarm

Language: en