• 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.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.1
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• pp.69-76
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• 2017

Bluetooth Low Energy (BLE), also known as Bluetooth Smart, has ultra-low power consumption; in fact, BLE-enabled devices can run on a single coin cell battery for several years. In addition, BLE can estimate the approximate distance between two devices using the Received Signal Strength Indication (RSSI) feature, enabling relatively precise navigation in indoor and small outdoor areas where GPS is not an option. In this paper, an experimental setup is presented in which BLE is used for navigation within a small outdoor area. BLE-based beacons are installed in fixed positions, which periodically transmit a universally unique identifier (UUID). A smart device receives the UUID and sends it to a database server using cellular or Wi-Fi technology. The server returns fixed position information corresponding to the received UUID codes, and the smart device uses that information to compute its current position based on relative signal strengths, and display it on a map. These results demonstrate the successful application of BLE technology for navigation in small outdoor areas. This system can be implemented for indoor navigation as well.

• Journal of Korea Society of Industrial Information Systems
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• v.24 no.6
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• pp.43-53
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• 2019

In recent years, there have been many cases of damage to indoor air hazardous materials, and major damage due to the lack of quick action. In this regard, the system is intended to establish for sending push messages to the user's mobile when the concentration of hazardous substances is exceeded. This system extracts data with IoT system such as Arduino and Raspberry Pi and then constructs database through MongoDB and MySQL in cloud computing system. The database is imported through the application server using NodeJS and sent to the application for visualization. Also, when receiving signals about a dangerous situation in IoT system, push message is sent using Google FCM library. Mobile application is developed using Android Web view, and page to enter Web view is developed using HTML5 (HTML, Javascript CSS). The application of this system enables real-time monitoring of indoor air-dangerous substances. In addition, real-time information on indoor/outdoor detection location and concentration can be sent to the user's mobile in case of a risk situation, which can be expected to help the user respond quickly.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.10
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• pp.2177-2184
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• 2012

A different and effective method for indoor positioning system is needed and increased it's importance compare to the outdoor GPS based method. The FingerPrint positioning method is known as a superior method in indoor positioning system that maintains signal strength patterns for RPs(Reference Points) in database and compare the DB with the measured real-time signals on the mobile device. FingerPrint positioning method is necessary to establish an accurate database, but errors can occur by several factors. In this paper, we analyze the signal patterns of each terminal in accordance with connection state of access point and trace that the error in accordance with connection state of access point can be an important error in FingerPrint DB configuration through an experimental case study.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.11
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• pp.1706-1712
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• 2022

Recently, the safety of chemical substances has gained attention due to incidents occurring in petrochemical industrial complexes, such as gas leaks and fires. In particular, industrial complexes in Ulsan and Yeosu (South Korea) are valuable as they significantly contribute to the petrochemical industry, but accidents may occur due to chemical leakage. Therefore, in this study, sensor nodes are configured at an interval of 20 [m] based on outdoor facilities standards to respond to chemical accidents, and exposure consideration of 8 h (TWA) and 15 min (STEL) are proposed in TLVs. The proposed system pre-processes data collected in multi-hop communication at a cycle of 0.6-0.75 [s] using Python and stores it in the MySQL database through SQL and a real-time remote monitoring system that updates the stored data once every 5 s is implemented by linking MySQL and Grafana.

• Journal of the Korean Society of Costume
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• v.58 no.4
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• pp.26-34
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• 2008

The purpose of this study was to create a database of information on the mechanical properties of two different waterproof and breathable shell fabric groups(high density woven and PTFE laminate) used for outdoor apparel and to compare and correlate data of their mechanical properties and hand values. The results of this study were as follows; There were no statistically significant differences between two fabric groups in extension, bending and shearing properties. There were statistically significant differences between two fabric groups in MMD, SMD, LC and we values. High density woven fabrics had smoother surface than PTFE laminated fabrics. PTFE laminated fabrics can be compressed easily more than high density woven fabrics but their recovery after compression was not better than high density woven fabrics. There were statistically significant differences between two fabric groups in NUMERI, FUKURAMI. There was statistically significant difference between two fabric groups in total hand value. Total hand value and mean deviation of MIU had a very high and statistically significant negative correlation coefficient.

• Fashion & Textile Research Journal
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• v.16 no.1
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• pp.1-12
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• 2014

Leggings are recognized as unique fashion items that meet the needs of customers to express individuality due to their protective and thermal functions. They are highly practical fashion items that show a casual, street and sportive style with a noted influence on outdoor leisure fields. This study analyzes the sociocultural background for the spread of leggings as well as their design characteristics, coordination characteristics and authentic characteristics. The formative characteristics of modern legging designs are as follows. First, the shapes of modern leggings are ankle-length, calflength, above-knee, knee-length, stirrup and top of the foot-length. Leggings are transformed in many ways: length-expansion, side-slit, unbalanced length, variations of straps, cut-out, trimmings, pattern transformation and complex form. Second, modern leggings contain achromatic colors in modern and sensual image, vivid colors in sportive image and metallic colors futuristic and technical image. Third, leggings patterns value originality, uniqueness and rarity as shown by printed geometric patterns, hand crafted geometric and natural patterns, and abstract patterns expressed through various materials and themes. Fourth, modern leggings' textures are categorized into erotic, simply-functional, seasonless, glossy, and metallic. Functional and fashionable leggings reflect the psychological needs of modern society. This study suggests a direction for the development of legging designs and provides a theoretical database for higher value-added leggings business.

• The Journal of Korea Robotics Society
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• v.8 no.4
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• pp.283-291
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• 2013

Methods for measuring or estimating of ground shape by a laser range finder and a vision sensor(exteroceptive sensors) have critical weakness in terms that these methods need prior database built to distinguish acquired data as unique surface condition for driving. Also, ground information by exteroceptive sensors does not reflect the deflection of ground surface caused by the movement of UGVs. Thereby, UGVs have some difficulties regarding to finding optimal driving conditions for maximum maneuverability. Therefore, this paper proposes a method of recognizing exact and precise ground shape using Inertial Measurement Unit(IMU) as a proprioceptive sensor. In this paper, firstly this method recognizes attitude of a robot in real-time using IMU and compensates attitude data of a robot with angle errors through analysis of vehicle dynamics. This method is verified by outdoor driving experiments of a real mobile robot.

• KIISE Transactions on Computing Practices
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• v.24 no.3
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• pp.151-156
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• 2018

In this paper, a method to classify objects in outdoor CCTV images using Convolutional Neural Network(CNN) and background subtraction is proposed. Object candidates are extracted using background subtraction and they are classified with CNN to detect objects in the image. At the end, computation complexity is highly reduced in comparison to other object detection algorithms. A database is constructed by filming alleys and playgrounds, places where crime occurs mainly. In experiments, different image sizes and experimental settings are tested to construct a best classifier detecting person. And the final classification accuracy became 80% for same camera data and 67.5% for a different camera.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.3
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• pp.151-156
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• 2020

A technology for calculating the position of a device is very important for users who receive positioning services, regardless of various indoor/outdoor or with/without any positioning infrastructure existence environments. One of the positioning resources widely used at present, LTE, is a typical infrastructure that can overcome the space limitation, however its positioning method based on the position of the LTE base station has low accuracy. A method of constructing a radio wave map of an LTE signal has been proposed as a method for overcoming the accuracy, but it takes a lot of time and cost to perform high-density collection in a wide area. In this paper, we describe a method of creating a high-density DB for the entire region by using vehicle-based partial collection data. To create a positioning database, we applied the idea of Generative Adversarial Network (GAN), which has recently been in the spotlight in the field of deep learning, and learned the collected data. Then, a virtually generated map which having the smallest error from the actual data is selected as the optimum DB. We verified the effectiveness of the positioning DB generation algorithm using the positioning data obtained from un-collected area.