• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.300-302
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• 2021

Usage of a face mask has become mandatory in many countries after the COVID-19. This paper described to develop a IoT based smart mask system for monitoring face mask. The system developed in this paper has two main units, a sensor module, and a smartphone application. The sensor module consists of four components: temperature and humidity sensor, a heart rate sensor, and a BLE chip. This components work as a unit to collect data and stream them through an I2C port over BLE to a connected mobile device. The smartphone application is an Android application developed for smart phones. It enables the Android device to communicate with the sensor to receive sensor data, process, store and display results.

• Journal of Korea Multimedia Society
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• v.25 no.4
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• pp.610-619
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• 2022

Recently, the market for masks has been growing due to air pollution, sun protection, pollen allergies and other reasons. In addition, the demand for masks has increased dramatically due to the new coronavirus from 2020, and masks are still one of the necessities of life. Although the reliance on masks is increasing, there are many inconveniences associated with wearing masks for long periods of time. At the same time, technology is developing rapidly, and the demand for smart wearable devices is increasing. Therefore, at the moment when the fourth industrial revolution is underway, combining people's common necessities with IoT technology to bring new convenient experiences to people is an important direction for future technology development and product development. In this study, smart masks were designed and implemented using IoT(Internet of Things) technology. The mask uses a microcomputer Adafruit circuit playground express, using the microcomputer's LED, optical sensors, can be in the dark place light, and through the temperature sensor real-time grasp of body temperature changes. If the body temperature rises above normal, the LED will turn "on" and activate the voice sensor to warn yourself and others around you.

• Korean Journal of Artificial Intelligence
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• v.9 no.2
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• pp.7-14
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• 2021

Purpose: To solve urban problems, empirical research is being actively conducted to implement a smart city based on various ICT technologies, and digital twin technology is needed to effectively implement a smart city. A digital twin is essential for the realization of a smart city. A digital twin is a virtual environment that intuitively visualizes multidimensional data in the real world based on 3D. Digital twin is implemented on the premise of the convergence of GIS and BIM, and in particular, a lot of time is invested in data pre-processing and labeling in the data construction process. In digital twin, data quality is prioritized for consistency with reality, but there is a limit to data inspection with the naked eye. Therefore, in order to improve the required time and quality of digital twin construction, it was attempted to detect a building using Mask R-CNN, a deep learning-based masking algorithm for aerial images. If the results of this study are advanced and used to build digital twin data, it is thought that a high-quality smart city can be realized.

• IEIE Transactions on Smart Processing and Computing
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• v.2 no.4
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• pp.197-202
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• 2013

Large gains in speech intelligibility can be obtained using the SNR-based binary mask approach. This approach retains the time-frequency (T-F) units of the mixture signal, where the target signal is stronger than the interference noise (masker) (e.g., SNR > 0 dB), and removes the T-F units, where the interfering noise is dominant. This paper introduces two alternative binary masks based on the distortion constraints to improve the speech intelligibility. The distortion constraints are induced by a gain function for estimating the short-time spectral amplitude. One binary mask is designed to retain the speech underestimated (T-F) units while removing the speech overestimated (T-F)units. The other binary mask is designed to retain the noise overestimated (T-F) units while removing noise underestimated (T-F) units. Listening tests with oracle binary masks were conducted to assess the potential of the two binary masks in improving the intelligibility. The results suggested that the two binary masks based on distortion constraints can provide large gains in intelligibility when applied to noise-corrupted speech.

• Journal of Internet of Things and Convergence
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• v.8 no.6
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• pp.27-33
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• 2022

Sleep is an essential factor for living a healthy life, but most modern people complain of poor sleep. For these people, as the need for a means to simply evaluate and manage the quality of sleep increases, devices that can check the sleep state at home without monitoring by an examiner are being developed. The smart sleep mask, which is the subject of this usability test, provides bio-signal monitoring while sleeping so that you can conveniently measure and manage your sleep state for yourself. The purpose of this study is to evaluate the usability and safety of the smart sleep mask, to find and prevent potential factors related to errors in use that may occur, and to develop the comfort and safety of this product. As a result of the formative evaluation of the sleep mask prototype, it was reported that it was difficult to turn on the power and check the results, and that the sleep mask was not comfortable to wear. Different opinions were presented on the size and weight of the sleeping mask by people in different age groups.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.787-789
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• 2014

Image processing is presently used in various areas such as smart phone, smart TV, and portable PC. Likewise, edge detection plays an important role in most of the applications. As such, studies for the detection of edge are continually underway. Roberts, Laplacian and LoG(lapacian of Gaussian) are the representative edge detection methods, but these methods do not offer optimal edge detection characteristic in case of the image that is damaged by Salt & Pepper noises. As such, this study presented algorithm with superior edge detection characteristic by utilizing the elements of local mask in Salt & Pepper noise environment.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.07a
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• pp.199-200
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• 2017

본 논문에서는 최근 황사 및 미세 먼지 등으로 늘어나는 환경적 오염으로부터 어린이들이 올바른 마스크 사용을 할 수 있도록 스마트 기능이 포함된 마스크를 제안하는 것이다. 제 4차 산업혁명으로 인하여 사물인터넷이나 스마트 제품은 날로 급증하고 있는 추세이다. 따라서, 어린이들이 많이 사용하는 마스크 제품에 스마트한 기능을 넣고자 한다. 스마트 밴드를 통해 미세먼제 오염도를 측정할 수 있고, 호흡 상태를 파악하고 분비물의 상태를 분석할 수가 있다. 따라서 의료기관을 방문하기 전까지 어린이들의 건강상태를 보다 즉각적으로 파악할 수가 있다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.10
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• pp.1262-1270
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• 2020

Recently, the smart video surveillance research, which has been receiving increasing attention, has mainly focused on the intruder detection and tracking, and abandoned object detection. On the other hand, research on real-time detection of stolen objects is relatively insufficient compared to its importance. Considering various smart surveillance video application environments, this paper presents two different types of stolen object detection algorithms. We first propose an algorithm that detects theft of statically and dynamically registered surveillance objects using a dual background subtraction model. In addition, we propose another algorithm that detects theft of general surveillance objects by applying the dual background subtraction model and Mask R-CNN-based object segmentation technology. The former algorithm can provide economical theft detection service for pre-registered surveillance objects in low computational power environments, and the latter algorithm can be applied to the theft detection of a wider range of general surveillance objects in environments capable of providing sufficient computational power.

• International journal of advanced smart convergence
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• v.8 no.3
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• pp.131-137
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• 2019

This study proposes a method of learning and recognizing the characteristics that are the classification criteria of Hangul using Mask R-CNN, one of the deep learning techniques, to recognize and classify atypical Hangul characters. The atypical characters on the Hangul signboard have a lot of deformed and colorful shapes beyond the general characters. Therefore, in order to recognize the Hangul signboard character, it is necessary to learn a separate atypical Hangul character rather than the existing formulaic one. We selected the Hangul character '닭' as sample data and constructed 5,383 Hangul image data sets and used them for learning and verifying the deep learning model. The accuracy of the results of analyzing the performance of the learning model using the test set constructed to verify the reliability of the learning model was about 92.65% (the area detection rate). Therefore we confirmed that the proposed method is very useful for Hangul signboard character recognition, and we plan to extend it to various Hangul data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.900-902
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• 2015

In the modern society, according to the advancement in digital image processing technology, edge detection is being utilized in various application sectors such as smart device and medical, etc. In existing edge detection methods, there are Sobel, Prewitt, Roberts and Laplacian, etc, which uses the mask. These previous methods are easy to implement but shows somewhat insufficient results. Therefore, in order to compensate the problems of existing methods, in this paper, an algorithm that detects the edge using the local mask and morphological operation was proposed and the detection performance was compared against the previous methods.