Detailed Research

IoT, Cloud, Bigdata and Mobile (ICBM)


2022. 12

Junyong Kim, Geunbeom Kim, Jisu Jeong, Jongwook Si, and Sungyoung Kim

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The existing control panel causes inconvenience to pedestrians and increases the frequency of safety accidents. To overcome this, the problem can be solved by burying the existing control panel underground. However, the control panel buried underground has a disadvantage in that it is difficult to maintenance and manage. Therefore in the further research propose an application that provides each location for the underground control panel and enables internal monitoring and management.

Development of Smart Alarm IoT Systemin Raspberry Pi Environment

2022. 12

Ceumbeom Kim, Jongwook Si, Seungjae Son, Jeyong Song, and Sungyoung Kim

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In this paper, we propose a smart alarm technology that enables interaction between Raspberry Pi and mobile phones using IoT and database technologies. It provides a function to set alarms through Raspberry Pi, mobile phones, and APIs, and provides weather services to users using Raspberry Pi's modules. In this case, user alarm setting information may be collected in a database together with a communication function through a server.

Development of Data Analysis System for Determining Product Quaility of Injection Molding Machine Results

2022. 12

Jisu Jeong, Minsu Jeong, Jongwook Si, and Sungyoung Kim

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In this paper, we propose a system capable of determining good and defect of the Injection Molding Machine results using machine learning and visualization techniques through data analysis. Data analysis and visualization techniques are used to visually provide the user with factors affecting the poor results of the Injection Molding Machine, and the optimal value of each factor can be found to reduce the production of the defective results.

Development of an Infrared Imaging-Based Illegal Camera Detection Sensor Module in Android Environments

2022. 03

Moonnyeon Kim, Hyungman Lee, Sungmin Hong and Sungyoung Kim

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This study is for detecting hidden cameras effectively such that they could not be easily detected by human eyes. An image sensor-based module with 940 nm wavelength infrared detection technology was developed, and an image processing algorithm was developed to selectively detect illegal cameras. Based on the Android smartphone environment, image processing technology was applied to an image acquired from an infrared camera, and a detection sensor module that is less sensitive to ambient brightness noise was studied.

Hidden Camera Detection Based on Infrared Camera

2021. 11

Moonnyeon Kim, Gyuree Kim, Hyungman Lee, Sungmin Hong and Sungyoung Kim

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Existing studies have mainly detected a hidden camera by analyzing a specific frequency signal from the hidden camera, but these methods have the disadvantage of requiring equipment for measuring the frequency.This paper proposes new method to detect hidden cameras by applying image processing to infrared camera images that are less affected by lighting to detect various types of mass-produced hidden camera products.

Hidden Camera Detection Based on Infrared Images in Android Environment

2021. 06

Moonnyeon Kim, Gyuree Kim and Sungyoung Kim

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In this paper, we present a technique to effectively detect hidden cameras so that they cannot be easily found with human eyes. Based on the Android smartphone environment, we apply image processing technology to images acquired from infrared cameras. The technology proposed in this study is expected to contribute to crime prevention in the future by enabling effective detection by an infrared camera that is minimally affected by the ambient brightness.