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Delay-Sensitive Multi-Sensor Routing Scheduling Method for Underground IoT in Mines.

Yinghui Zhang¹, Mingli Liu², Aiping Tan³

¹School of Computing and Software, Chengdu Neusoft University, Chengdu 611844, China.

Sensors (Basel, Switzerland)

|January 25, 2025

Summary

This summary is machine-generated.

This study introduces a new routing method for Internet of Things (IoT) sensors in underground mines. It addresses real-time data challenges in complex tunnel environments, improving safety and response times.

Keywords:

Internet of Things delay-sensitive multi-hop routing scheduling real-time schedule underground mine

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Area of Science:

Engineering
Computer Science
Mining Engineering

Background:

Underground construction safety is critical for mining and tunneling operations.
Internet of Things (IoT) sensors are vital for monitoring but face deployment challenges due to power and layout complexities.
Real-time data transmission and response are significant hurdles in underground environments.

Purpose of the Study:

To propose a delay-sensitive routing scheduling method for multi-sensor, multi-base-station IoT networks in underground mining.
To address the NP-hard nature of real-time routing in complex, mixed network topologies.
To enhance the efficiency and reliability of data transmission for underground safety.

Main Methods:

Formulation of a mixed wireless and wired network topology reflecting irregular tunnel distributions.
Development of routing scheduling algorithms based on greedy and heuristic strategies.
Implementation of an experimental platform for performance evaluation.

Main Results:

The proposed routing scheduling problem is proven to be NP-hard.
Greedy and heuristic algorithms were designed to solve the routing problem.
Experimental analysis demonstrated the performance of the developed algorithms.

Conclusions:

The developed delay-sensitive routing scheduling method effectively addresses real-time data challenges in underground IoT deployments.
The proposed algorithms offer a viable solution for optimizing data transmission in complex mining environments.
This research contributes to improving the safety and operational efficiency of underground construction through advanced IoT networking.