• Journal of Drive and Control
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• v.20 no.1
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• pp.8-15
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• 2023

With the recent trend of intelligence and automation of construction work, a double-blade road cutter is being developed that automatically enables cutting along the cutting line marked on the road using a vision system. The road cutter can recognize the cutting line through the camera and correct the driving route in real-time, and it detects the load of the cutting blade in real-time to control the driving speed in case of overload to protect workers and cutting blades. In this study, a vision system mounted on a double-blade road cutter was developed. A cutting route recognition technology was developed to stably recognize cutting lines displayed on non-uniform road surfaces, and performance was verified in similar environments. In addition, a vision sensor protection module was developed to prevent foreign substances (dust, water, etc.) generated during cutting from being attached to the camera.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.505-507
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• 2021

Image recognition technology is a technology that recognizes an image object by using the generated feature descriptor and generates object feature points and feature descriptors that can compensate for the shape of the object to be recognized based on artificial intelligence technology, environmental changes around the object, and the deterioration of recognition ability by object rotation. The purpose of the present invention is to implement a power management framework required to increase profits and minimize damage to livestock farmers by preventing accidents that may occur due to the improvement of efficiency of the use of livestock house power and overloading of electricity by integrating and managing a power fire management device installed for analyzing a complex environment of power consumption and fire occurrence in a smart safety livestock house, and to develop and disseminate a safe and optimized intelligent smart safety livestock house.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.4
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• pp.611-616
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• 2018

RFID-based Smart cabinets can make a recognition error owing to the electromagnetic wave interference. This paper proposes and implements a smart cabinet system for inventory management using RFID, especially which can be applied to biological laboratories. We calculate the optimal value of partition distance for the higher recognition rate between RFID tags and the reader, and the optimal partition thickness for electromagnetic wave absorption to achieve the higher recognition rate, in which two kinds of the partitions have been tested, a pure steel partition with various thickness and a thin steel partition attached with electromagnetic waves absorber. The experimental results show that the most recommended partition structure for the smart cabinets is one with the partition distance of 30cm and the partition thickness of 1mm attached with the electromagnetic wave absorption tapes.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.191-197
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• 2015

In this paper, we propose the system which recognize the gaze using Random Forests in vehicular environment based on smart-phone. Proposed system is mainly composed of the following: face detection using Adaboost, face component estimation using Histograms, and gaze recognition based on Random Forests. We detect a driver based on the image information with a smart-phone camera, and the face component of driver is estimated. Next, we extract the feature vectors from the estimated face component and recognize gaze direction using Random Forest recognition algorithm. Also, we collected gaze database including a variety gaze direction in real environments for the experiment. In the experiment result, the face detection rate and the gaze recognition rate showed 82.02% and 84.77% average accuracies, respectively.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.10 no.4
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• pp.111-117
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• 2001

In this paper, we will propose the new method that estimates the sensing ability of smart sensor. A study is estimation method that evaluates the sensing ability about smart sensor respectively. According to acceleration(g) and displacement changing, we estimated the sensing ability of smart sensor using the SAI(Sensing Ability Index) method respectively. We made the smart sensors in our experiment. The types of smart sensor are three types(H1, H1, H3 smart sensor). The smart sensors were developed for recognition of materials. Experiments and analysis were executed to estimated the sensing abili-ty of smarty sensor. Dynamic characteristics of smart sensors(acceleration changing) were evaluated respectively through a new method(SAI) that uses the power spectrum density.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.124-133
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• 2021

Smart factory is a future factory that collects, analyzes, and monitors various data in real time by attaching sensors to equipment in the factory. In a smart factory, it is very important to inquire and generate the status and history of equipment in real time, and the emergence of various smart devices enables this to be performed more efficiently. This paper proposes a multi device-based system that can create, search, and delete equipment status and history in real time. The proposed system uses the Android system and the smart glass system at the same time in consideration of the special environment of the factory. The smart glass system uses a QR code for equipment recognition and provides a more efficient work environment by using a voice recognition function. We designed a system structure for real time equipment monitoring based on multi devices, and we show practicality by implementing and Android system, a smart glass system, and a web application server.

• International Journal of Contents
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• v.11 no.1
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• pp.1-6
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• 2015

The development of information and technology has brought plenty of changes to the educational environment. The prevalence of smart phones is particularly playing a huge role in shaping learning methods. Smart phones provide the opportunity to scan QR codes, which can greatly ease access to information. Due to a high recognition speed, recognition rate, and restoration rate, they can be useful tools for English teachers to use in their class. In this study, we suggest using QR codes for writing and picture descriptions. Based on this study, more research should invest in Technology Embedded English teaching models to create better English classes for students.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.171-176
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• 2020

This paper presents an implementation of a gesture recognition platform that can be used in a factory workplaces. The platform consists of signages that display worker's job orders and a control center that is used to manage work orders for factory workers. Each worker does not need to bring work order documents and can browse the assigned work orders on the signage at his/her workplace. The contents of signage can be controlled by worker's hand and arm gestures. Gestures are extracted from body movement tracked by 3D depth camera and converted to the commandsthat control displayed content of the signage. Using the control center, the factory manager can assign tasks to each worker, upload work order documents to the system, and see each worker's progress. The implementation has been applied experimentally to a machining factory workplace. This flatform provides convenience for factory workers when they are working at workplaces, improves security of techincal documents, but can also be used to build smart factories.

• Journal of the Korean Society of Industry Convergence
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• v.18 no.4
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• pp.241-249
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• 2015

The purpose of this research is to develop the pattern recognition algorithm based on smart camera for inspection automation, and including external surface state of molding parts or optical parts. By performance verification, this development can be applied to establish for existing reflex data because inputting surface badness degree of scratch's standard specification condition directly. And it is pdssible to distinguish from schedule error of badness product and normalcy product within schedule extent after calculating the error comparing actuality measurement reflex data and standard reflex data mutually. The proposed technology cab be applied to test for masearing of the smallest 10 pixel unit. It is illustrated the relibility pf proposed technology by an experiment.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.818-821
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• 2020

The artificial intelligence software market is developing in various fields world widely. In particular, there is a wide variety of applications for image recognition technology using deep learning. This study intends to apply image recognition technology to the 'Home Gardening' market growing rapidly due to COVID-19, and aims to build a small-scale smart farm in the house using artificial intelligence and IoT technology for convenient crop cultivation for busy people living in cities. This intelligent farm system includes an automatic image recognition function and recommendation function based on temperature and humidity sensor-based indoor environment analysis.