• Korean Journal of Remote Sensing
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• v.33 no.2
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• pp.231-242
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• 2017

Monitoring of facilities such as roads, dams and bridges is important for their long-term sustainable usage. It has usually suffered with safety and cost problems, which makes more frequent monitoring difficult. As an efficient and economicalsolution to these problems, one may consider the use of smartphone to capture the status of the facilities. To derive quantitative analysis results with the smartphone images for facility monitoring, one should first rectify the images in a way as automatic and economical as possible. In thisstudy, we propose such a rectification method, which rectifiessmartphone images acquired from arbitrary locations based on reference images.In the proposed method, we determine the camera extrinsic parameters of each smartphone images using the reference imagesrather than ground control points, and project the image to the target surface of the facility based on the determined camera parameters. The method were applied to test data acquired from a small dam toward water-area facility monitoring. The experimental results showed that the camera extrinsic parameters were determined with the accuracy of 5 cm and $0.28^{\circ}$ in the position and attitude. The accuracy of the distance measured from the rectified image was evaluated to 10 cm. With the rectified images, one can accurately determine the location and length of the target objects required for facility monitoring.

• Korean Journal of Remote Sensing
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• v.28 no.4
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• pp.467-475
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• 2012

Cloud computing services are known that they have many advantages from the point of view in economic saving, scalability, security, sharing and accessibility. So their applications are extending from simple office systems to the expert system for scientific computing. However, research or computing technology development in the geo-spatial fields including remote sensing applications are the beginning stage. In this work, the previously implemented smartphone app for image processing was first migrated to mobile cloud computing linked to Amazon web services. As well, parallel programming was applied for improving operation performance. Industrial needs and technology development cases in terms of mobile cloud computing services are being increased. Thus, a performance testing on a satellite image processing module was carried out as the main purpose of this study. Types of implementation or services for mobile cloud varies. As the result of this testing study in a given condition, the performance of cloud computing server was higher than that of the single server without cloud service. This work is a preliminary case study for the further linkage approach for mobile cloud and satellite image processing.

• Journal of Satellite, Information and Communications
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• v.11 no.3
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• pp.18-23
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• 2016

Internet of things (IoT) is revolutionizing in the patient-Centered medical monitoring and management by authorizing the Smartphone application and data analysis with medical centers. The network connectivity is basic requirement to collect the observed human beings' health information from Smartphone to monitor the health from IoT medical devices in personal healthcare. The IoT environment built in Smartphone is very effective and does not demand infrastructure. This paper presents the smart phone deployed personal IoT architecture for Non-Invasive ECG Capturing. The adaptable IoT medical device cum Gateway is used for personal healthcare with big data storage on cloud configuration. In this approach, the Smartphone camera based imaging technique used to extract the personal ECG waveform and forward it to the cloud based big data storage connectivity using IoT architecture. Elaborated algorithm allows for efficient ECG registration directly from face image captured from Smartphone or Tablet camera. The profound technique may have an exceptional value in monitoring personal healthcare after adequate enhancements are introduced.

• Information and Communications Magazine
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• v.30 no.10
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• pp.79-85
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• 2013

By interacting with external wireless sensors, smartphones can gather high-fidelity data on the surrounding environment to develop various environment-aware, personalized applications. In this work we introduce the sensor virtualization module (SVM), which virtualizes external sensors so that smartphone applications can easily utilize a large number of external sensing resources. Implemented on the Android platform, our SVM simplifies the management of external sensors by abstracting them as virtual sensors to provide the capability of resolving conflicting data requests from multiple applications and also allowing sensor data fusion for data from different sensors to create new customized sensors elements. We envision our SVM to open the possibilities of designing novel personalized smartphone applications.

• Advances in nano research
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• v.15 no.2
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• pp.155-163
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• 2023

Exercise is beneficial to the body in some ways. It is vital for people who have heart problems to perform exercise according to their condition. This paper describes how an Android platform can provide early warnings of fatigue during wushu exercise using Photoplethysmography (PPG) signals. Using the data from a micro-electro-mechanical system (MEMS) gyroscope to detect heart rate, this study contributes an algorithm to determine a user's fatigue during wushu exercise. It sends vibration messages to the user's smartphone device when the heart rate exceeds the limit or is too fast during exercise. The heart rate monitoring system in the app records heart rate data in real-time while exercising. A simple pulse sensor and Android app can be used to monitor heart rate. This plug-in sensor measures heart rate based on photoplethysmography (PPG) signals during exercise. Pulse sensors can be easily inserted into the fingertip of the user. An embedded microcontroller detects the heart rate by connecting a pulse sensor transmitted via Bluetooth to the smartphone. In order to measure the impact of physical activity on heart rate, Wushu System tests are conducted using various factors, such as age, exercise speed, and duration. During testing, the Android app was found to detect heart rate with an accuracy of 95.3% and to warn the user when their heart rate rises to an abnormal level.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.7
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• pp.1364-1370
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• 2017

This paper proposes a method that automatically sets profile schedule context-based mobile phone by collecting the user's external situation based on the GPS sensor and accelerometer built into the smartphone and interacting with the data in the user's schedule to minimize the user's handset handling. However, real-time data collection in mobile phones causes energy shortage in the device due to battery consumption. In other words, a service control method is explained in a way that can efficiently handle resource consumption because accessing a measurement device such as GPS and other sensors may increase power consumption of the portable device. Therefore, effective data sharing for context awareness to reduce weekly schedules and smartphone mode has improved energy efficiency in sensing for data collection. The user can use the context more effectively by providing environmental adaptability for various situations such as the end user's local context and smartphone force control.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.6
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• pp.243-248
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• 2013

With rapid growth and fast diffusion of smartphone technologies, many users are deeply concerned about the smart applications and many mobile applications converged with various related technologies are rapidly disseminated. Especially, the convergence technologies like mobile apps that can establish the wireless ad hoc network between smartphone and other peripherals and exchange data are appear and progressed continuously. In this paper, we design and implement the smart app using bluetooth based wireless ad hoc sensor network that can connect smartphone with sensors and exchange data for various smart applications. The proposed smart application in this paper collects data obtained from more than 2 multi-sensors in real time and fulfills the decision making function by storing data at the database and analysing it. The smart application designed and implemented in this paper is the healthcare application that can analyze and evaluate the patient's health condition with sensing data from multi-sensors in real time through bluetooth module.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.3
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• pp.615-625
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• 2012

To measure the athletic information of exercisers, the applications of smartphone are programmed based on the sensing data from GPS device. These applications provide exercisers for running or walking distance, exercising time, calorie consumption, average speed, and so on. Among them, the exercising distance should measure accurately because it directly affects the other athletic information for exercisers. However, the existing methods for measuring the exercising distance makes errors because they are worked on the simple sphere or ellipse earth models. Actually, the surface of real earth is composed of inclined ground like hills and valleys. In this paper, a new exercising distance measuring algorithm is proposed to compensate the errors of existing method. It considers the altitude of slopes in exercising routes. To evaluate exercising distance measuring algorithms, we implement the athletic life-guide system based on the smartphone platform. In experiments, the proposed method shows that it provides more accurate distance measurement.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.405-406
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• 2012

A sensor network is composed of a large number of sensor nodes which have sensing, computation and wireless communication capabilities. The sensor node sends such collected data, usually via radio transmitter, to a command center (sink) either directly or through a data concentration center (a gateway). These sensor networks can be used for various application areas such as health, military, home network, managing inventory, monitoring disaster areas and so on. Moreover, owing to the rapid growth of mobile technology, high-performance smartphones are widespread and in increasing cases are utilized as a terminal device. In this paper, we propose a home management system using smartphone and sensor networks.

• Journal of KIISE
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• v.43 no.7
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• pp.763-772
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• 2016

With the spread of smartphones containing multiple on-board sensors, the market for context aware applications have grown. However, due to the limited power capacity of a smartphone, users feel discontented QoS. Additionally, context aware applications require the utilization of many forms of context and sensing information. If context transition has occurred, types of needed sensors must be changed and each sensor modules need to turn on/off. In addition, excessive sensing has been found when the context decision is ambiguous. In this paper, we focus on power consumption associated with the context transition that occurs during indoor/outdoor detection, modeling the activities of the sensor associated with these contexts. And we suggest a freezing algorithm that reduces power consumption in context transition. We experiment with a commercial application that service is indoor/outdoor location tracking, measure power consumption in context transition with and without the utilization of the proposed method. We find that proposed method reduces power consumption about 20% during context transition.