With the increasing efforts to utilize information and communication technologies (ICT) in disaster management, the massive amount of heterogeneous data that is generated through ubiquitous sensors paves the way for fast and informed decisions in the case of disasters. Utilization of the big “sensed” data leads to an effective and efficient management of disaster situations so as to prevent human and economic losses. The advancement of built-in sensing technologies in smart mobile devices enables crowdsourcing of sensed data, which is known as mobile crowdsensing (MCS). This systematic literature review investigates the use of mobile crowdsensing in disaster management on the basis of the built-in sensor types in smart mobile devices, disaster management categories, and the disaster management cycle phases (i.e., mitigation, preparedness, response, and recovery activities). Additionally, this work seeks to unveil the frameworks or models that can potentially guide disaster management authorities towards integrating crowd-sensed data with their existing decision-support systems. The vast majority of the existing studies are conceptual as they highlight a challenge in experimental testing of the disaster management solutions in real-life settings, and there is little emphasis on the use cases of crowdsensing through smartphone sensors in disaster incidents. In light of a thorough review, we provide and discuss future directions and open issues for mobile crowdsensing-aided disaster management.

/pdf/use-of-mobile-crowdsensing-in-disaster-management-a-3akfjstk.pdf

Use of Mobile Crowdsensing in Disaster Management: A Systematic Review, Challenges, and Open Issues

In this paper, an innovative strengthening system for masonry walls made of externally bonded Fabric-Reinforced Cementitious Matrix (FRCM) is presented. Due to the good mechanical properties and the compatibility with the architectural heritage, the FRCM is an adequate alternative to the use of Fiber-Reinforced Polymer (FRP) composites and other traditional techniques. The proposed system is applied to the strengthening of a classical architectural typology in cultural heritage architecture, which is the “in falso” masonry: a load-bearing wall built over a masonry vault, and hence without a direct load path to the ground. A research program, characterized by an experimental campaign, has been started in order to devise and verify an optimal strengthening system that assures for the masonry wall a structural behavior similar to a “wall beam”, so to prevent progressive collapses when the underlying masonry vault loses its carrier function. In particular, rather than the canonical application, consisting in widespread application to the whole surface of the masonry wall, an innovative intervention made of “Green Tape” of composites has been designed and verified by a specifically designed experimental set-up. The main objective of the research is to propose a reinforcement strategy not detrimental to unmovable artistic assets and tied to the safety and robustness of the architectural heritage.

/pdf/natural-frcm-and-heritage-buildings-experimental-approach-to-26uw6gb9.pdf

Natural FRCM and Heritage Buildings: Experimental Approach to Innovative Interventions on “Wall Beams”

The dynamic characteristics of existing wind turbine structures are usually monitored using contact sensors, which is not only expensive but also time-consuming and laborious to install. Recently, computer vision technology has developed rapidly, and monitoring methods based on cameras and UAVs (unmanned aerial vehicles) have been widely used. However, the high cost of UAVs and cameras make it difficult to widely use them. To address this problem, a target-free dynamic characteristic monitoring method for wind turbine structures using portable smartphone and optical flow method is proposed by combining optical flow method with robust corner feature extraction in ROI (region of interest). Firstly, the ROI region clipping technology is introduced after the structural vibration video shooting, and the threshold value is set in the ROI to obtain robust corner features. The sub-pixel displacement monitoring is realized by combining the optical flow method. Secondly, through three common smartphone shooting state to monitor the structural displacement, the method of high pass filtering combined with adaptive scaling factor is used to effectively eliminate the displacement drift caused by the two shooting states of standing and slightly walking, which can meet the requirements of structural dynamic characteristics monitoring. After that, the structural displacement is monitored by assembling the telephoto lens on the smartphone. The accuracy of displacement monitored by assembling the telephoto lens on the smartphone is investigated. Finally, the proposed monitoring method is verified by the shaking table test of the wind turbine structure. The results show that the optical flow method, combined with smartphones, can accurately identify the dynamic characteristics of the wind turbine structure, and the smartphone equipped with a telephoto lens is more conducive to achieving low-cost wind turbine structure dynamic characteristics monitoring. This research can provide a reference for evaluating the condition of wind turbine structures.

/pdf/dynamic-characteristic-monitoring-of-wind-turbine-structure-2e63epav.pdf

Dynamic Characteristic Monitoring of Wind Turbine Structure Using Smartphone and Optical Flow Method

Geocoding is a spatial analysis method that uses address information (e.g., street address, intersection, census tract, zip code, etc.) to determine geographical coordinates (latitude and longitude). In recent decades, geocoding has gone beyond its primary use for census and demographic information to novel applications in disaster risk reduction, even to earthquake early warning. Here I demonstrate the usefulness of geocoding techniques to earthquake early warning systems as applied to case studies that relied on survey response data and crowd-sourced video footage. These datasets were initially collected to understand the efficacy of tests conducted on ShakeAlert®, the earthquake early warning system for the West Coast of the United States, and how people behave during earthquakes, respectively. Geocoding these data can improve our overall technical understanding of the system, demonstrate whether individuals take protective actions such as ‘Drop, Cover, and Hold On’, and spotlight community demographics that the system is reaching or unintentionally missing. The combination of these social science datasets with geocoding information deepens our knowledge of these fundamentally human-centered systems, including how to improve the distribution of alerts for people and individuals with access and functional needs. In the future, this work may help verify U.S. Geological Survey ‘Did You Feel It?’ responses and seismic intensity, especially in regions with sparse seismic networks. 

Geocoding Applications for Social Science to Improve Earthquake Early Warning

FTBCS safety evacuation of frame-core tube buildings on construction sites (FTBCS) is one of the most challenging evacuation scenarios conceivable. This investigation proposes a practical calculation method and examines the parameters’ influence on safety evacuation in frame-core tube building construction sites. Firstly, the characteristics of constructors from 30 FTBCS in China are analyzed. After an investigation of 23,230 constructors, it was found that constructors have unique properties in gender ratio, age composition, and occupational age. Female constructors account for about 10%, and aged constructors account for 0.28%. Constructors within five years of occupational age account for about 26.39%. Evacuation speeds on different working faces including frames and core tubes are tested, and the decline coefficients of 0.80 and 0.70 are taken consideration into the evacuation model. Then, an exclusive evacuation time algorithm that is appropriate for FTBCS is proposed. Multiple parameters’ influence on safety evacuation is researched by numerical simulation. With a 5.0% growth of female gender ratio, aged constructors, and constructors within five years of occupational age, the average movement distance is increased by 10.32 m, 0.67 m, and 11.19 m, respectively. The age composition ratio and occupational age ratio mainly affect the evacuation process by evacuation speed and path programming, respectively, and the leading influencing factors are not distinct in their gender ratio effects. Optimization of construction layout can reduce the evacuation time from the horizontal direction plane effectively, and then relieve clustering and crowding on platforms.

/pdf/an-investigation-of-frame-core-tube-building-construction-1bucb0kt.pdf

An Investigation of Frame-Core Tube Building Construction Sites on Safety Evacuation

Structural health monitoring (SHM) is of great significance for post-earthquake damage assessment. Smartphone-based monitoring techniques provide the possibility to perform crowdsensing for all buildings in urban regions after an earthquake. However, this idea still faces many difficulties and is hard to realize. Fortunately, the development of game engines provides the opportunity for simulating this kind of experiment. The main objective of this study was to use Unity to simulate the whole process when a city is struck by an earthquake that consists of one main shock and one aftershock. During the emergency response, the citizens and the “city brain” in Unity, named Ground Eye, cooperate to finish the task of taking refuge and collecting data for regional damage assessment. Some basic assumptions were made first. Then the city model was established in Unity, and the behaviors of the citizens were directed by the behavior tree artificial intelligence (AI). OpenSees was utilized to determine the monitoring demand and simulate the monitoring results. A GUI was built to exhibit the data during the whole process. The results show that the evacuation and monitoring plan is feasible. The simulation framework presented in this paper can be used in other SHM application scenarios.

/pdf/simulation-of-smartphone-based-public-participation-in-2l2c0jrr.pdf

Simulation of Smartphone-Based Public Participation in Earthquake Structural Response Emergency Monitoring Using a Virtual Experiment and AI

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Zheng He

Author Tools

Chat about Author

Papers

Simulation of Smartphone-Based Public Participation in Earthquake Structural Response Emergency Monitoring Using a Virtual Experiment and AI