• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.10
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• pp.2195-2202
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• 2011

Recently, navigation system is used to inform users of vehicle location and driving direction, moving distance and so on. This navigation uses GPS sensor for current location determination. The GPS sensor will determinate current coordinates by using triangulation algorithm. This characteristic bring about that the GPS signal is not available in the shadow region such as tunnel and urban canyon. Moreover, Even though the signal is available, inherent positional error rate of the GPS often results in the dislocation of vehicle. To solve, these problems, a new positioning system is proposed in the paper. The System utilizes geomagnetic sensors of smartphone, speed information of CAN of vehicle though bluetooth and WiFi APs for GPS shadow area. The experimental test shadows that the proposed system using multiple data is able to determine the position of vehicle in GPS shadow areas.

• Journal of Advanced Navigation Technology
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• v.23 no.5
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• pp.473-480
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• 2019

The smart home is a technology that can monitor and control by connecting everything to a communication network in various fields such as home appliances, energy consumers, and security devices. The Smart home is developing not only automatic control but also learning situation and user's taste and providing the result accordingly. This paper proposes a model that can provide a comfortable indoor environment control service for the user's characteristics by detecting the user's behavior as well as the automatic remote control service. The whole system consists of ESP 8266 with sensor and Wi-Fi, Firebase as a real-time database, and a smartphone application. This model is divided into functions such as learning mode when the home appliance is operated, learning control through learning results, and automatic ventilation using indoor and outdoor sensor values. The study used moving averages for temperature and humidity in the control of home appliances such as air conditioners, humidifiers and air purifiers. This system can provide higher quality service by analyzing and predicting user's characteristics through various machine learning and deep learning.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.1
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• pp.11-19
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• 2012

Due to existing infrastructure to collect traffic information was constructed to expressway and national highway, we cannot precisely know traffic situation for their surrounding area. Therefore, it is difficult to provide reliable traffic information to users using navigation and smartphone. In this research, we collected aerial images by using unmanned airship capable of wide-area monitoring and proposed a method extracting vehicle speed from the collected data. And, we performed experiments to verify the accuracy of extracted vehicle speed. Our method proposed in this research can be used to extract a new approach of traffic information according to increased demand of traffic monitoring. We expect that our method will become a new research trend in traffic information application.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.475-484
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• 2021

The Android OS has quickly established itself with the smartphone market and is being applied in a variety of ways such as navigation and refrigerator panels. Existing terminals can implement services that require high precision while using RTOS that requires accurate execution time, but Android OS has a disadvantage in that it cannot provide high-precision real-time performance. In this paper, we propose a real-time communication method that operates in the Android OS. Real-time communication reduces the load using the UDP protocol, and configures the real-time operating system time tick through a high-precision timer in the kernel area. An Android application level library was created to implement real-time communication and compared with the existing Android library for real-time performance verification.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.652-653
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• 2015

This study investigates the effect of real-time traffic information on the traffic flows in Korea. Recently, the development of smartphones has made it easier to use the route guidance service based on real-time traffic information. By the Big Data analysis in the study, it was found that the number of postings on the web community sites increased sharply in 2010 and 2011 when the smartphones spread widely. In the analysis of the traffic speeds by time, the average traffic speeds for morning and evening rush hours on weekdays from 2009 to 2014 of the 142 sections in the 6 national highways in Gyeonggi-do, Korea were used. From the results of the analysis, it was found that the percentage of the number of sections with the improved traffic flows increased greatly in 2012 compared to 2011. The findings of the study indicate the effect of the real-time traffic information on improving traffic flows.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.77-84
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• 2022

In this paper, we propose a system for monitoring air pollutants such as fine dust using an unmanned aerial vehicle capable of autonomous navigation. The existing air quality management system used a method of collecting information through a fixed sensor box or through a measurement sensor of a drone using a control device. This has disadvantages in that additional procedures for data collection and transmission must be performed in a limited space and for monitoring. In this paper, to overcome this problem, a GPS module for location information and a PMS7003 module for fine dust measurement are embedded in an unmanned aerial vehicle capable of autonomous navigation through flight information designation, and the collected information is stored in the SD module, and after the flight is completed, press the transmit button. It configures a system of one-stop structure that is stored in a remote database through a smartphone app connected via Bluetooth. In addition, an HTML5-based web monitoring page for real-time monitoring is configured and provided to interested users. The results of this study can be utilized in an environmental monitoring system through an unmanned aerial vehicle, and in the future, various pollutants measuring sensors such as sulfur dioxide and carbon dioxide will be added to develop it into a total environmental control system.

• Journal of Advanced Navigation Technology
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• v.18 no.6
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• pp.619-624
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• 2014

Nowadays there are various smart devices and development with the development of smart phones and that can be attached to the human body wearable computing device has been in the spotlight. In this paper, we proceeded developing wearable devices in watch type which can detect user's movement and developing a system which connects the wearable devices to smart TVs, or smart phones so that users can save and manage their physical information in those devices. Health care wearable devices already existing save information by connecting their systems to smart phones. And, smart TV health applications usually include motion detecting systems using cameras. However, there is a limit when connecting smart phone systems to different devices from various companies. Also, in case of smart TV, because some devices may not have cameras, there can be a limit for users who wants to connect their devices to smart TVs. Wearable device and user information collected by using the smart phone and when it is possible to exercise and manage anywhere. This information can also be confirmed by the smart TV applications. By using this system will be able to take advantage of the study of the behavior of the future work of the user more accurately be measured in recognition technology and other devices.

• Journal of Advanced Navigation Technology
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• v.26 no.3
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• pp.172-178
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• 2022

In this paper, water meter AMR(automatic meter reading), one of the core technologies of smart water grid, using LoRa IoT network is studied. The main content of the research is to develop the network system and show the test results that one PC server receives the readings of water meters from multiple households through LoRa communication and stores them in the database, and at the same time sends the data to the web server database through internet. The system also allows users to monitor the meter readings using their smartphones. The hardware and firmware of the main board of the digital water meter are developed. For a PC server program, MDMS(meter data management system) is developed using Visual C#. The app program running on the user's smartphone is also developed using Android Studio. By connecting each developed parts, the total network system is mounted on a flow test bench in the laboratory and tested. For the fields test, 5 places around the university are selected and the transmission distances are tested. The test result show that the developed system can be applied into the real field. The developed system can be expanded to various social safety nets such as monitoring the living alone or elderly with dementia.

• Journal of the Korea Convergence Society
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• v.9 no.1
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• pp.199-204
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• 2018

Smart phones that have lost their existing physical home buttons are being released at the same time, and the flow of users is also changing. The flow is highly subjective and can vary depending on the individual's tendencies. Therefore, this study investigated the change of the flow of smart phone users by Q methodology which is a method of subjectivity research. As a result, the proficiency level of how to turn on the power to start the screen showed a tendency to decrease the flow, and the playability, which is a result of curiosity about the new thing, The results were very positive in the continuity of navigation due to the use of software buttons instead of buttons. Therefore, it can be seen that the change in the hardware smartphone has a positive effect on the flow.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.599-607
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• 2021

Street-view images, which are omnidirectional scenes centered on a specific location on the road, can provide various obstacle information for the pedestrians. Pedestrian network data for the navigation services should reflect the up-to-date obstacle information to ensure the mobility of pedestrians, including people with disabilities. In this study, the object detection model was trained for the bollard as a major obstacle in Seoul using street-view images and a deep learning algorithm. Also, a process for updating information about the presence and number of bollards as obstacle properties for the crosswalk node through spatial matching between the detected bollards and the pedestrian nodes was proposed. The missing crosswalk information can also be updated concurrently by the proposed process. The proposed approach is appropriate for crowdsourcing data as the model trained using the street-view images can be applied to photos taken with a smartphone while walking. Through additional training with various obstacles captured in the street-view images, it is expected to enable efficient information update about obstacles on the road.