An Industry 4.0 geolocation system for last mile ground disasters survivor detection: Tests and results

A.J. Soto-Vergel, D. Ramirez-Rios, J.C. Velez and R. Amaya-Mier

Socio-Economic Planning Sciences, 2025, vol. 101, issue C

Abstract: This research introduces a novel geolocation system for survivor detection after disasters, based on the Ground Disaster Information Management System (GDIMS) guidelines. Our geolocation system is a rapid deployment, low-power, and wide-area network solution that uses tiny machine-learning-based voice activity detection to obtain timely information in challenging disaster-struck environments. The system is designed to signal survivor existence on an interactive map and further guide search and rescue efforts during the aftermath of a disaster. The impact and relevance of this technology lie in its ability to continuously monitor disasters despite disruptions from remote, steep, and/or debris disaster surroundings, nontrivial locations of possible victims, and failed transportation and communication infrastructure. This research draws from lessons learned from past events, such as the 2017 and 2010 landslides in Mocoa and Gramalote, Colombia. Results from numerical tests conducted in Gramalote, Colombia, show the technological maturity of the system and its capabilities for possible real-world implementation.

Keywords: Geolocation system; Ground disaster; LPWAN; LoRaWAN; Tiny machine learning; Survivor detection (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0038012125001193
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:soceps:v:101:y:2025:i:c:s0038012125001193

DOI: 10.1016/j.seps.2025.102270

Access Statistics for this article

Socio-Economic Planning Sciences is currently edited by Barnett R. Parker

More articles in Socio-Economic Planning Sciences from Elsevier
Bibliographic data for series maintained by Catherine Liu ().