Title: A topology network optimisation of underground mine escape paths based on real-time personnel localisation data

Authors: Mingjiang Wu

Addresses: China Coal Huajin Group Co., Ltd., Taiyuan 030024, China

Abstract: Static escape paths often fail to adapt to dynamic underground hazards, including fires and collapses. To address this limitation, we propose a topology-driven optimisation framework leveraging real-time personnel tracking. Ultra-wideband positioning data from the subterranean tunnel dataset enable the construction of a spatiotemporal graph network with dynamic risk perception. Our multi-objective cost function integrates path length, personnel density derived from adaptive Gaussian kernel estimation, and hazard gradients simulated via Navier-Stokes equations for fire and predicted through long short-term memory networks for collapses. The dynamic topology optimisation algorithm achieves sub-second path re-planning. Validation using a 500 m × 300 m × 150 m mine point cloud model under compound disasters demonstrates key advantages: an average escape time reduction to 8.7 ± 1.2 minutes, surpassing risk-aware ant colony optimisation by 15.5%; a 96.3% success rate with a maximum path risk of below 0.52.

Keywords: underground escape routes; topology network optimisation; personnel location data; dynamic risk perception; mine safety.

DOI: 10.1504/IJSN.2026.153820

International Journal of Security and Networks, 2026 Vol.21 No.2, pp.96 - 106

Received: 27 Aug 2025
Accepted: 29 Aug 2025
Published online: 27 May 2026 *

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