SafeMine Quantum Network-Inspired LabVIEW-Driven Real-Time Health Monitoring for Advanced Mining Safety

Abstract

Mining coal is among the world's most dangerous jobs. They had unanticipated emergencies on a regular basis. Mining workers faces the risks of cave-ins, explosions, gas leaks, and other accidents. Ensuring the safety of mining workers remains a significant concern. To overcome these situations, our project aims to design a monitoring system for analysing the health conditions of the mining workers in the LabVIEW environment. The proposed system provides the health conditions of the workers and give alert signals to the control center about the risk. The different types of sensors are used like heart rate sensor for measuring pulses of the workers, Gas Sensor for measuring toxic gases around the surroundings of workers and temperature sensors. The sensors data are received by microcontroller hardware and then integrated with LabVIEW environment to monitor the health conditions of workers. The proposed method allows the control unit to monitor the mining workers health conditions at any time using the consumer id. Also, if any abnormalities in workers' health is found ie., sudden change in heartbeat, heart panic, oxygen level and temperature, alerts message given to control unit. This is the proposed method used for monitoring the health conditions of the mining workers. By leveraging quantum networking inspired algorithms, we seek to optimize data processing efficiency, ultimately contributing to a safer working environment for mining workers.