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Related Experiment Video

Updated: Dec 24, 2025

Using a Real-Time Locating System to Measure Walking Activity Associated with Wandering Behaviors Among Institutionalized Older Adults

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A Rescue-Assistance Navigation Method by Using the Underground Location of WSN after Disasters.

Shuo Li¹, Tiancheng Guo¹, Ran Mo²

¹School of Electrical and Information Engineering, Changsha University of Science & Technology, Changsha 410114, China.

Sensors (Basel, Switzerland)

|April 16, 2020

Summary

This study proposes a new method for developing escape guidance paths in underground disasters using wireless sensor networks. It improves survivor navigation accuracy and effectiveness in challenging, sparse anchor node environments.

Keywords:

anisotropic wireless sensor networks disaster guidance path indoor localization sparse anchor localization wireless sensor networks

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Area of Science:

Electrical Engineering
Computer Science
Geotechnical Engineering

Background:

Underground disasters pose significant rescue challenges, requiring rapid survivor guidance.
Existing methods struggle with accurate positioning and pathfinding in anisotropic wireless sensor networks with sparse anchor nodes.

Purpose of the Study:

To develop an effective escape guidance path method for underground disaster scenarios.
To address the limitations of anisotropic networks with sparse anchor nodes for precise localization and navigation.

Main Methods:

A hybrid channel model was developed to characterize underground wireless communication, including ray waveguide, shadowing, tunnel size, and obstacle penetration.
A trustable anchor node selection algorithm with node movement detection was proposed for high-precision localization.
A modified minimum spanning tree algorithm was used to determine the optimal guidance path based on node location and obstacles.

Main Results:

The proposed method demonstrated improved localization accuracy in anisotropic networks.
Simulations verified the effectiveness of the developed guidance paths.
The method showed good scalability for underground rescue applications.

Conclusions:

The developed escape guidance path method enhances survivor navigation in underground disasters.
The hybrid channel model and anchor node selection algorithm improve positioning accuracy.
The modified minimum spanning tree algorithm effectively generates optimal escape routes.