• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.725-728
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• 2020

Light Field Rendering 을 이용하여 성능이 떨어지는 Low resolution 카메라 장비로 얻는 영상의 한계를 극복하고, Image Processing 기술로 직접 조정해야 해결할 수 있는 수차 및 성능 문제 해결한다. 저가형 장비, 렌즈를 사용하여도 컴퓨터기반 처리를 이용하여 물리적인 한계를 극복한 간이 광학현미경을 만들고자 함. 3D print 를 이용한 뼈대구조를 만들고, 저렴한 raspberry pi 임베디드 플랫폼을 이용하여 설계도만 있다면, 누구나 쉽게 만들 수 있기에 많은 사람들이 이 분야에 더 쉽게 다가설 수 있게 한다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.3
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• pp.401-410
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• 2023

In this paper, we propose optimization methods for implementing SPARKLE, one of the NIST LWC finalists, on a 64-bit ARMv8 processor. The proposed methods consist of two approaches: an implementation using ARM A64 instructions and another using NEON ASIMD instructions. The A64-based implementation is optimized by performing register scheduling to efficiently utilize the available registers on the ARMv8 architecture. By utilizing the optimized A64-based implementation, we can achieve speeds that are 1.69 to 1.81 times faster than the C reference implementation on a Raspberry Pi 4B. The ASIMD-based implementation, on the other hand, optimizes data by parallelizing the ARX-boxes to perform more than three of them concurrently through a single vector instruction. While the general speed of the optimized ASIMD-based implementation is lower than that of the A64-based implementation, it only slows down by 1.2 times compared to the 2.1 times slowdown observed in the A64-based implementation as the block size increases from SPARKLE256 to SPARKLE512. This is an advantage of the ASIMD-based implementation. Therefore, the ASIMD-based implementation is more efficient for SPARKLE variant block cipher or permutation designs with larger block sizes than the original SPARKLE, making it a useful resource.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.117-124
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• 2017

A Smart Grid is a system that can efficiently use energy by exchanging real-time information in both directions between a consumer and a power supplier using ICT technology on an existing power network. DR(Demand response) is an arrangement in which electricity users can sell the electricity they save to the electricity market when the price of electricity is high or the power system is crisis. In this study, we developed a power meter data transmission device and power IT system that measure the demand information in real-time using a smart meter and transmit it to a cloud server. The power meter data transmission device developed in this study uses alight sensor connected to a Raspberry Pi 3 to measure the number of blinking lamps on the KEPCO meter per unit of power, in order to provide reliable data without any measurement errors with respect to the KEPCO power data. The power measurement data transmission device uses the standard communication protocol, OpenADR 2.0b. The measured data is transmitted to the power IT system, which consists of the VEN, VTN, and calculation program, via the LTE WiFi communication network and stored in its MySQL DB. The developed power measurement data transmission device issues a power supply instruction and performs a peak reduction DR when a power system crisis occurs. The developed power meter data transmission device has the advantage of allowing the user to adjust it every 1 minute, where as the existing smart metering time is fixed at once every 15 minutes.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.183-184
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• 2021

기존의 스타일러는 옷 건조, 살균 기능을 가지고 있으나, 비용이 비싸며 공간을 차지하는 단점을 가지고 있다. 알림 기능을 가지는 스마트 옷장은 옷장위에 설치된 라즈베리파이 디스플레이에 간단한 날씨정보를 출력하여 그 날의 날씨정보를 시간소비 없이 간편하게 습득할 수 있으며, 한줄 뉴스를 통하여 그 날의 소식을 간편하게 알 수 있다. 또한 옷장 내부에 설치된 아두이노가 온습도 센서와 미세먼지 센서를 통제하여 옷장 내부의 온도, 습도, 미세먼지 농도를 디스플레이를 통해 알 수 있으며, 습도가 높거나, 미세먼지 농도가 높을 경우에 옷장 내부에 부착된 쿨링팬이 자동으로 작동하여 옷장 내부를 환기시킴으로써 습도를 낮추고 먼지, 냄새 등을 제거해주는 효과가 있다. 그리고 습도나 미세먼지 수치가 낮아지면 자동으로 쿨링팬의 작동은 멈춰진다. 또한 미세먼지, 온습도 값에 따라 3색 LED가 색이 변화한다. 이런 스마트옷장으로 바쁜 현대 사회에서 사용자들의 시간을 절약해주고 옷의 관리해줌으로써 편리함을 제공한다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.8
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• pp.1-8
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• 2020

Air ducts installed for ventilation inside buildings accumulate contaminants during their service life. Robots are installed to clean the air duct at low cost, but they are still not fully automated and depend on manpower. In this study, an intersection detection algorithm for autonomous driving was applied to an air duct cleaning robot. Autonomous driving of the robot was achieved by calculating the distance and angle between the extracted point and the center point through the intersection detection algorithm from the camera image mounted on the robot. The training data consisted of CAD images of the duct interior as well as the cross-point coordinates and angles between the two boundary lines. The deep learning-based CNN model was applied as a detection algorithm. For training, the cross-point coordinates were obtained from CAD images. The accuracy was determined based on the differences in the actual and predicted areas and distances. A cleaning robot prototype was designed, consisting of a frame, a Raspberry Pi computer, a control unit and a drive unit. The algorithm was validated by video imagery of the robot in operation. The algorithm can be applied to vehicles operating in similar environments.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.6
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• pp.1019-1024
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• 2019

In this paper, we plan to design and manufacture a new sleeping child check system using image and PIR sensors. Therefore, it plans to implement a system that can prevent in-vehicle accidents that can occur due to presence of human and certain temperature inside the vehicle by collecting data from PIR sensors and temperature sensors with the main control device based on Arduino. In addition, the values of sensors can be linked with Bluetooth communication or Wi-Fi communication to send information to the mobile phone, and the sensor values can be printed by texting on the screen. It also plans to use raspberry pie and camera modules to build a display and smartphone streaming service inside the vehicle. Through this, the objective of this study is to prevent safety accidents in school vehicles by making experiments and research in this paper recognize 100% inside the vehicle with the quantitative goal of PIR sensors.

• ETRI Journal
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• v.40 no.3
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• pp.396-409
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• 2018

Elliptic curve cryptography (ECC) can achieve relatively good security with a smaller key length, making it suitable for Internet of Things (IoT) devices. DNA-based encryption has also been proven to have good security. To develop a more secure and stable cryptography technique, we propose a new hybrid DNA-encoded ECC scheme that provides multilevel security. The DNA sequence is selected, and using a sorting algorithm, a unique set of nucleotide groups is assigned. These are directly converted to binary sequence and then encrypted using the ECC; thus giving double-fold security. Using several examples, this paper shows how this complete method can be realized on IoT devices. To verify the performance, we implement the complete system on the embedded platform of a Raspberry Pi 3 board, and utilize an active sensor data input to calculate the time and energy required for different data vector sizes. Connectivity and resilience analysis prove that DNA-mapped ECC can provide better security compared to ECC alone. The proposed method shows good potential for upcoming IoT technologies that require a smaller but effective security system.

• Atmosphere
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• v.28 no.3
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• pp.317-324
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• 2018

In this study, we review the ground-based whole-sky camera (WSC), which is developed to continuously capture day and night cloud images using the illumination data from a precision Lightmeter with a high temporal resolution. The WSC is combined with a precision Lightmeter developed in IYA (International Year of Astronomy) for analysis of an artificial light pollution at night and a DSLR camera equipped with a fish-eye lens widely applied in observational astronomy. The WSC is designed to adjust the shutter speed and ISO of the equipped camera according to illumination data in order to stably capture cloud images. And Raspberry Pi is applied to control automatically the related process of taking cloud and sky images every minute under various conditions depending on illumination data from Lightmeter for 24 hours. In addition, it is utilized to post-process and store the cloud images and to upload the data to web page in real time. Finally, we check the technical possibility of the method to observe the cloud distribution (cover, type, height) quantitatively and objectively by the optical system, through analysis of the captured cloud images from the developed device.

• Journal of IKEEE
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• v.21 no.3
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• pp.227-233
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• 2017

Python language is widely used because of its ease of learning and its wide application range. Arduino, on the other hand, is also widely utilized hardware for physical computing and internet of things(IoT). However, Arduino is controlled by $C{^+^+}$ language, which makes it difficult for non-experts to enter swiftly. This paper proposes an errorless protocol that can simultaneously control multiple Arduino devices in a master device using python language with I2C communication. Using the protocol proposed in this paper, we can take advantage of the python language to control multiple Arduinos.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.37-40
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• 2021

This paper presents a design of a speech to sign language converter for deaf and hard of hearing people. The device is low-cost, low-power consumption, and it can be able to work entirely offline. The speech recognition is implemented using an open-source API, Pocketsphinx library. In this work, we proposed a context-oriented language model, which measures the similarity between the recognized speech and the predefined speech to decide the output. The output speech is selected from the recommended speech stored in the database, which is the best match to the recognized speech. The proposed context-oriented language model can improve the speech recognition rate by 21% for working entirely offline. A decision module based on determining the similarity between the two texts using Levenshtein distance decides the output sign language. The output sign language corresponding to the recognized speech is generated as a set of sequential images. The speech to sign language converter is deployed on a Raspberry Pi Zero board for low-cost deaf assistive devices.