• Smart Structures and Systems
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• v.31 no.2
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• pp.141-154
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• 2023

After an earthquake, information regarding potential damage to buildings close to the epicenter is very important during the initial emergency response. This study proposes the use of crowdsourced measured acceleration response data collected from smartphones located within buildings to perform system identification of building structures during earthquake excitations, and the feasibility of the proposed approach is studied. The principal advantage of using crowdsourced smartphone data is the potential to determine the condition of millions of buildings without incurring hardware, installation, and long-term maintenance costs. This study's goal is to assess the feasibility of identifying the lowest fundamental natural frequencies of buildings without knowing the orientations and precise locations of the crowds' smartphones in advance. Both input-output and output-only identification methods are used to identify the lowest fundamental natural frequencies of numerical finite element models of a real building structure. The effects of time synchronization and the orientation alignment between nearby smartphones on the identification results are discussed, and the proposed approach's performance is verified using large-scale shake table tests of a scaled steel building. The presented results illustrate the potential of using crowdsourced smartphone data with the proposed approach to identify the lowest fundamental natural frequencies of building structures, information that should be valuable in making emergency response decisions.

• Tunnel and Underground Space
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• v.28 no.6
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• pp.547-554
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• 2018

Using crowdsourced sensor data collection technique, it is possible to collect high-density ground vibration data which is difficult to obtain by conventional methods. In this study, we have developed a crowdsourced ground vibration data collection system using MEMS sensors mounted on small electronic devices including smartphones, and implemented client and server based on the proposed infrastructure system design. The system is designed to gather vibration data quickly through Android-based smartphones or fixed devices based on Android Things, minimizing the usage of resource like power usage and data transmission traffic of the hardware.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.577-587
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• 2023

The utilization of crowdsourced spatial data has been actively researched; however, issues stemming from the uncertainty of data quality have been raised. In particular, when low-quality data is mixed into drone imagery datasets, it can degrade the quality of spatial information output. In order to address these problems, the study presents a methodology for automatically validating the geometric quality of crowdsourced imagery. Key quality factors such as spatial resolution, resolution variation, matching point reprojection error, and bundle adjustment results are utilized. To classify imagery suitable for spatial information generation, training and validation datasets are constructed, and machine learning is conducted using a radial basis function (RBF)-based support vector machine (SVM) model. The trained SVM model achieved a classification accuracy of 99.1%. To evaluate the effectiveness of the quality validation model, imagery sets before and after applying the model to drone imagery not used in training and validation are compared by generating orthoimages. The results confirm that the application of the quality validation model reduces various distortions that can be included in orthoimages and enhances object identifiability. The proposed quality validation methodology is expected to increase the utility of crowdsourced data in spatial information generation by automatically selecting high-quality data from the multitude of crowdsourced data with varying qualities.

• Journal of Korea Multimedia Society
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• v.20 no.4
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• pp.704-712
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• 2017

Various researches on content sensibility with the development of digital contents are under way. Emotional research on fonts is also underway in various fields. There is a requirement to use the content expressions in the same way as the content, and to use the font emotion and the textual sensibility of the text in harmony. But it is impossible to select a proper font emotion in Korea because each of more than 6,000 fonts has a certain emotion. In this paper, we analysed emotional classification attributes and constructed the Hangul font recommendation system. Also we verified the credibility and validity of the attributes themselves in order to apply to Korea Hangul fonts. After then, we tested whether general users can find a proper font in a commercial font set through this emotional recommendation system. As a result, when users want to express their emotions in sentences more visually, they can get a recommendation of a Hangul font having a desired emotion by utilizing font-based emotion attribute values collected through the crowdsourced method.

• Journal of Information Technology Applications and Management
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• v.21 no.3
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• pp.19-33
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• 2014

Crowdsourcing is a popular tool for firms to harness external knowledge and resources. One variation of crowdsourcing entails the use of corporate channels in social network services (SNS) such as Twitter to hold public idea competitions. This study examined the role of feedback interaction between participants of idea competitions. More specifically, the study examined the impact of incentives to provide feedback on other participants' ideas. We found that idea competitions where explicit incentives were introduced to elicit crowdsourced feedback in the form of qualitative comments resulted in improved idea generation performance-with more ideas generated overall, and more ideas generated through participant collaborations, through increased comment-posting activities. Based on the findings, implications for theory and practice are discussed.

• Journal of Korea Multimedia Society
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• v.20 no.5
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• pp.827-834
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• 2017

Android's inter-application access enriches its application ecosystem. However, it exposes security vulnerabilities where end-user data can be exploited by attackers. While existing techniques have focused on minimizing the risks of inter-application access, they either suffer from inaccurate risk detection or are primarily available to expert users. This paper introduces a novel technique that automatically analyzes potential risks between a set of applications, aids end-users to effectively assess the identified risks by crowdsourcing assessments, and generates an access control policy which prevents unsafe inter-application access at runtime. Our evaluation demonstrated that our technique identifies potential risks between real-world applications with perfect accuracy, supports a scalable analysis on a large number of applications, and successfully aids end-users' risk assessments.

• Journal of information and communication convergence engineering
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• v.17 no.2
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• pp.142-148
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• 2019

Relatively few countries provide separate bicycle lanes for cyclists. Hence, tools for suggesting cycling routes are essential for a safe and pleasant cycling experience. This study aims to develop a mobile application to build cycling routes based on user preferences, specifically location, search radius, ride distance, and number of optimal routes. Our application calls the Strava API to retrieve Strava cycling segments crowdsourced from the cycling community. Then, it creates a graph consisting of the start and end points of these segments. Beginning from a user-specified location, the depth-first search algorithm (DFS) is applied to find routes that conform to the user's preferences. Next, a set of optimal routes is obtained by computing a trade-off ratio for every discovered route. This ratio is calculated from the lengths of all segments and the lengths of all connecting paths. The connected routes can be displayed on a map on an Android device or exported as a GPX file to a bike computer. Future work must be performed to improve the design of the user interface and user experience.

• Architectural research
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• v.20 no.4
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• pp.109-120
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• 2018

In the context of ever-faster urbanization, cities are becoming increasingly complex, and data collection to understand such complex relationships is becoming a very important factor. This paper focuses on the lighter weight of the method of collecting urban data, and studied how to use such complementary data collection using crowdsourcing. Especially, the method of converting mobile acceleration sensor information to urban trip information by combining with locational information was experimented. Using the parameters for transportation type classification obtained from the research, information was obtained and verified in Singapore and Zurich. The result of this study is thought to be a good example of how to combine raw data into meaningful behavior information.

• Journal of KIBIM
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• v.13 no.1
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• pp.33-40
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• 2023

In architectural design studios, students' needs are evaluated from a diverse and objective point of view. And the evaluation process and results are to use a design evaluation method that everyone can recognize. Therefore, in this study, we propose Crowdsourcing, in which a large number of participants participate in the evaluation to solve fundamental problems. However, the field of architecture is an area in which expertise such as evacuation, firefighting, rescue, and regulations is essential. Therefore, we expanded the concept by participation of a large number of architects, not the general public. And It presented a new word, Prowdsourcing. Prowdsourcing is a group of architects working on-line as an evaluator. It is a method that can have objectivity and expertise of evaluation at the same time. Therefore, prowdsourcing will provide students with a variety of objective assessments, which will be a recognized design evaluation method by everyone.

• Journal of Information Science Theory and Practice
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• v.5 no.2
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• pp.6-16
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• 2017

Populating information-rich online environments through crowdsourcing is increasingly becoming popular. One approach to motivate participation is via games. That is, a crowdsourcing game offers entertainment while generating useful outputs as byproducts of gameplay. A gap in current research is that actual usage patterns of crowdsourcing games have not been investigated thoroughly. We thus compare content creation patterns in a game for crowdsourcing mobile content against a non-game version. Our analysis of 3,323 contributions in both apps reveal 10 categories including those that conform to the traditional notion of mobile content created to describe locations of interest, and those that are social in nature. We contend that both types of content are potentially useful as they meet different needs. Further, the distribution of categories varied across the apps suggests that games shape behavior differently from non-game-based approaches to crowdsourcing.