• International Journal of Advanced Culture Technology
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• v.5 no.2
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• pp.54-62
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• 2017

Currently, falling to industrial field workers is causing serious injuries. Therefore, many researchers are actively studying the fall by using acceleration sensor, gyro sensor, pressure sensor and image information.Also, as the spread of smartphones becomes common, techniques for determining the fall by using an acceleration sensor built in a smartphone are being studied. The proposed method has complexity due to fusion of various sensor data and it is still insufficient to develop practical application. Therefore, in this paper, we use acceleration sensor module built in smartphone to collect acceleration data, propose a simple falling algorithm based on accelerometer sensor data after normalization and preprocessing, and implement an Android based app.

• Journal of the Korea Safety Management & Science
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• v.20 no.2
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• pp.37-44
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• 2018

The Location Based Service is growing rapidly nowadays due to the universalization of the use for smartphone, and therefore the location determination technology has been placed in a very important position. This study suggests an algorithm that can provide the estimate of users' location by using smartphone sensors. And in doing so we will propose a methodology for the creation and update of indoor map through the more accurate position estimation using smartphone sensors such as acceleration sensor, gyroscope sensor, geomagnetic sensor and rotation sensor.

• International journal of advanced smart convergence
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• v.10 no.3
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• pp.10-16
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• 2021

In this paper, we devise a Shapley-value-based covert channel in smartphones. More specifically, unlike ordinary use of Shapley value in cooperative game, we make use of a series of Shapley values, which are computed from sensor data collected from smartphones, in order to create a covert channel between encoding smartphone and decoding smartphone. To the best of our knowledge, we are the first to contrive covert channel based on Shapley values. We evaluate the encoding process of our proposed covert channel through simulation and present our evaluation results.

• Journal of Korea Multimedia Society
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• v.20 no.8
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• pp.1200-1207
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• 2017

Sensors in a smartphone can be used to measure various physical quantities. In this paper, we propose an object localization scheme in a three dimenstional using a smart phone. The proposed scheme estimates the location of an object by observing it from several different points. The direction to the target object and the locations of the observation points are collected at each observation point using the location sensor and the orientation sensor in the smartphone. Based on these observations, the proposed scheme derives three dimensional line of sight vectors and estimates the location of the target object that minimizes the estimation error. We implemented the proposed scheme on an Android smartphone and tested its performance by estimating the height of a building and characteristics of the proposed approach.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.2
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• pp.27-32
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• 2016

Several sensor devices have been developed for monitoring individual's health and status information and services which visualize customized information by associating applications running on smartphones with sensor devices also have been emerged. Though these applications provide similar information to a user, each sensor device has its own application caused by non-standardized packet formats. In this paper, we propose a sensor device identification for dynamic interworking between a smartphone and personal sensor devices. In the proposed scheme, we can use the same application which plays role of a client on the smartphone as changing sensor devices because server stores packet information of sensor devices.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.1
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• pp.48-56
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• 2015

In the paper, a smartphone-controlled personal mobility system(PMS) based on a compass sensor is developed. The use of a magnetic compass sensor makes the PMS move according to the heading direction of a smartphone controlled by a rider. The proposed smartphone-controlled PMS allows more intuitive interface than PMS controlled by pushing a button. As well, the magnetic compass sensor makes a role in compensating for the mechanical characteristics of motors mounted on the PMS. For adequate control of the robot, two methods: absolute and relative direction methods based on the magnetic compass sensor and wireless communication are presented. Experimental results show that the PMS is conveniently and effectively controlled by the proposed two methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.5805-5825
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• 2019

Smartphones are important platforms because of their sophisticated computation, communication, and sensing capabilities, which enable a variety of applications in the Internet of Things (IoT) systems. Moreover, advancements in hardware have enabled sensors on smartphones such as environmental and chemical sensors that make sensor data collection readily accessible for a wide range of applications. However, dynamic, opportunistic, and heterogeneous mobility patterns of smartphone users that vary throughout the day, which greatly affects the efficacy of sensor data collection. Therefore, it is necessary to consider phone users mobility patterns to design data collection schedules that can reduce the loss of sensor data. In this paper, we propose a mobility-based weighted adaptive opportunistic scheduling framework that can adaptively adjust to the dynamic, opportunistic, and heterogeneous mobility patterns of smartphone users and provide prioritized scheduling based on various application scenarios, such as velocity, region of interest, and sensor type. The performance of the proposed framework is compared with other scheduling frameworks in various heterogeneous smartphone user mobility scenarios. Simulation results show that the proposed scheduling improves the transmission rate by 8 percent and can also improve the collection of higher-priority sensor data compared with other scheduling approaches.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.6
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• pp.1477-1484
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• 2015

With the growth of financial industry with smartphone, interest on user authentication using smartphone has been arisen in these days. There are various type of biometric user authentication techniques, but gait recognition using accelerometer sensor in smartphone does not seem to develop remarkably. This paper suggests the method of user authentication using accelerometer sensor embedded in smartphone. Specifically, calibrate the sensor data from smartphone with 3D-transformation, extract features from transformed data and do principle component analysis, and learn model with using gaussian mixture model. Next, authenticate user data with confidence interval of GMM model. As result, proposed method is capable of user authentication with accelerometer sensor on smartphone as a high degree of accuracy(about 96%) even in the situation that environment control and limitation are minimum on the research.

• Journal of Korea Multimedia Society
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• v.17 no.12
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• pp.1437-1445
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• 2014

A smartphone has very limited input methods regardless of its various functions. In this respect, it is one alternative that sensor motion recognition can make intuitive and various user interface. In this paper, we recognize user's motion using acceleration sensor, magnetic field sensor, and gyro sensor in smartphone. We try to reduce sensing error by gradient descent algorithm because in single sensor it is hard to obtain correct data. And we apply vector quantization by conversion of rotation displacement to spherical coordinate system for elevated recognition rate and recognition of small motion. After vector quantization process, we recognize motion using HMM(Hidden Markov Model).

• Journal of the Korean Society of Safety
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• v.30 no.6
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• pp.117-121
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• 2015

$O_2$-deficiency related accidents occur every year and the most effective way to prevent them is to measure $O_2$ concentration in air with a properly-calibrated $O_2$ monitoring device before entering low-$O_2$ areas. An electro-chemical sensor, Texas Instrument gas platform, and iPhone are used to construct a smartphone-based $O_2$ monitoring device. The smartphone based $O_2$ measuring approach offers advantages of small size, accessibility, internet-connectivity, and programmability in comparison to conventional $O_2$ measuring devices. Multiple gas sensors can be conveniently interfaced to single smartphone, allowing for creating a network of gas sensors distributed across workplaces and remote monitoring via existing mobile communication network. To check proper function of the $O_2$ monitoring device the sensor was exposed to shallow and deep human breaths. The readings decreased immediately after being exposed to exhalation and recovered during inhalation to a calibrated level of 20.9%. When readings decreased below a preset warning value of 19.5%, a low $O_2$ warning was successfully activated on the smartphone.