Abstract
Structural collapses are widespread, owing to a surge in climatic changes, earthquakes, and terrorism. Therefore, there are some technological rescue methods in practice that involve sensors, radars, cameras, microphones, and robots. However, deployment of these techniques faces at least one issue amongst cost, availability, and technical expertise, which limits their application in developing countries. So, there is a dire need for a low-cost and easy deployable rescue method. Recently, we witnessed an increasing trend of using Wi-Fi radios as sensing modality for various applications, including breathing detection and localization, thus leading to device-free communication. Based on this, we may envisage having a Wi-Fi rescue solution. However, Wi-Fi signals cannot easily penetrate through collapsed structures due to the multilayered obstacle scenario. So, in this study, we focus our research on the proper information analysis and abstraction of debris and also present the possible methodology to have better coverage for Wi-Fi signals using Wi-Fi radar edge. We define two objectives of this work; 1) debris information analysis and 2) the Wi-Fi signal propagation mechanism, respectively. We achieve our first goal by conducting site surveys of earthquake-hit areas that enable us to analyze the causes and types of structural collapses followed by debris concept selection model. We employ a bijective soft set approach to accurately select the debris based on the complexity and nature of structural engineering followed. Moreover, we use the Wi-Fi Halow radar edge for wireless signal propagation and perform extensive simulations at low power. Finally, we compare both methods and discuss prospects.
Highlights
Post-disaster rescue from collapsed structures using ubiquitous methods is getting more attention from the research community owing to the surge in climate changes, earthquakes, war, and terrorism [1]
In this paper, we study the nature of debris and its proper modeling to address the weak Wi-Fi signal strength through a low-powered Wi-Fi radar approach
We present debris selection mechanism by employing bijective soft set theory [35], as it can provide us the best concept of construction materials that can be subject to Wi-Fi radar signal method for coverage computation
Summary
Post-disaster rescue from collapsed structures using ubiquitous methods is getting more attention from the research community owing to the surge in climate changes, earthquakes, war, and terrorism [1]. UAV’s, Biobots, and radar-based solutions like FINDER are not available in developing countries due to cost, and unavailability within 72 hours, which is a major challenge None of these except FINDER’’2 proved to be much successful in practical scenarios. There are applications using Wi-Fi signals for indoor localization yet those are not effective for collapsed structures owing to complex multilayered debris Howsoever, this does provide us room to investigate more on the strength of Wi-Fi signals in debris scenarios because successful breathing detection can lead to device-free rescue solutions that would be cost-effective and available round the globe. We employ a bijective soft set theory method to transform debris and building assessment models into proper debris information analysis mechanism This method is based on the selection of pivotal attributes that define the nature of collapsed buildings.
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