• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.3
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• pp.667-673
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• 2015

A laser diode(LD) has been studied in many fields what medical, industrial processing, sensor, advertising equipment, printing equipment. And the LD is being used in industry. However, LD will require precision handling. Therefore, the actual use of LD is limited to areas of specialization. In this study, attend to the characteristics of the LD what weak to electrostatic and physical impact, current and heat. And will make a sample module that use comfortably a various wavelength LD. Furthermore, Furthermore, through the printing CTP(Computer to Plate) equipment used the 128-channel LD-Driver, compares it with a 64-channel CTP device about the print speed and resolution. And will solved the problem of delay between the dot and the dot. Finally, consider the potential of the 256-channel LD-Driver.

• Journal of Multimedia Information System
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• v.4 no.4
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• pp.163-170
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• 2017

Internet of things (IoT) is a new paradigm for collecting, processing and analyzing various contents in order to detect anomalies and to monitor particular patterns in a specific environment. The collected data can be used to discover new patterns and to offer new insights. IoT-enabled data mashup is a new technology to combine various types of information from multiple sources into a single web service. Mashup services create a new horizon for different applications. Environmental monitoring is a serious tool for the state and private organizations, which are located in regions with environmental hazards and seek to gain insights to detect hazards and locate them clearly. These organizations may utilize IoT - enabled data mashup service to merge different types of datasets from different IoT sensor networks in order to leverage their data analytics performance and the accuracy of the predictions. This paper presents an IoT - enabled data mashup service, where the multimedia data is collected from the various IoT platforms, then fed into an environmental cognition service which executes different image processing techniques such as noise removal, segmentation, and feature extraction, in order to detect interesting patterns in hazardous areas. The noise present in the captured images is eliminated with the help of a noise removal and background subtraction processes. Markov based approach was utilized to segment the possible regions of interest. The viable features within each region were extracted using a multiresolution wavelet transform, then fed into a discriminative classifier to extract various patterns. Experimental results have shown an accurate detection performance and adequate processing time for the proposed approach. We also provide a data mashup scenario for an IoT-enabled environmental hazard detection service and experimentation results.

• Journal of Advanced Navigation Technology
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• v.22 no.1
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• pp.43-47
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• 2018

In recent years, bicycle craze has been blowing in Korea, and bicycle has become a means of transportation near. In addition, there is a lot of interest in the Internet of things, and recently there is a lot of interest in the Internet of things. However, despite the development of the bicycle market, the bicycle cradle does not have such a development, and it still has a drawback in that it requires a separate lock for the lock. In this regard, I would like to find some problems and solve them. In this paper, we have implemented a system that can control the location and use of the bicycle cradle in real time by communicating with the app and Arduino so that it can help the collection and retrieval of the bicycle which is the problem of the current bicycle cradle. n addition, we propose a method to establish a shared economic system based on Internet of things by providing shared services with acquaintances and others, and to improve user convenience by providing real - time services.

• Journal of Internet of Things and Convergence
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• v.2 no.3
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• pp.37-41
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• 2016

In this thesis, we sought to build a home and business environment based on the rapid prototyping technology and network technologies that enabled rapid access to high-speed technologies and technologies. Using the analytic algorithm for image processing techniques, using the analytic algorithm for analyzing and tracking objects in the OpenCV library, trace objects and track objects and control various sensors. It also wants to implement a platform enabling various sensors to collect and record various services by controlling and connecting various sensors through the master Single board and the slave single.

• Journal of Internet of Things and Convergence
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• v.5 no.2
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• pp.73-79
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• 2019

Research is underway on services and systems that provide real-time alerts for suffocating gases and potentially explosive materials, but currently smart bend type services are lacking. This study supports real-time identification of explosion hazards due to static electricity in the workplace and immediate elimination of accident occurrence factors, real-time monitoring of worker status and workplace hazards (oxygen, hazardous chemical concentration), and immediate warning and data in case of danger. We propose a method of establishing an accident prevention system through analysis. In this way, various accidents that may occur in industrial sites are monitored using IoT-based intelligent sensor nodes, wireless network technology, data processing middleware, and integrated control system, and real-time risk information at the industrial sites is prevented and accidents are prevented. By supporting a safe working environment, the company can significantly reduce costs compared to post-procurement costs.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.12
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• pp.2347-2356
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• 2017

Raspberry Pi has been widely used for a hardware platform to develop the Internet of Things (IoT) applications. The basic task of diverse IoT devices is to obtain their status or environmental information by using various sensors and to send them to a gateway or a remote server. For the purpose, one of application layer protocols for IoT, MQTT is widely used. IoT devices are often powered by batteries and they are required to operate for a long time without replacing or recharging their batteries. Thus, energy efficiency is one of the most critical problems for obtaining and sending sensor data. To develop energy-efficient IoT applications, the information about power consumption characteristics of the applications is necessary. However, there has been little study to analyze power consumption of IoT communication on IoT devices. This paper presents a study to measure and analyze the power consumption of sending/receiving data under various conditions via the MQTT protocol on Raspberry Pi.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.5
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• pp.120-124
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• 2017

The temporal super resolution is a method for increasing the frame rate. Electro-optical sensors are used in various surveillance and reconnaissance weapons systems, and the spatial resolution and temporal resolution of the required electro-optical sensors vary according to the performance requirement of each weapon system. Because most image sensors capture images at 30~60 frames/second, it is necessary to increase the frame rate when the target moves and changes rapidly. This paper proposes a method to increase the frame rate using color channel extrapolation. Using a DMD, one frame of a general camera was adjusted to have different consecutive exposure times for each channel, and the captured image was converted to a single channel image with an increased frame rate. Using the optical flow method, a virtual channel image was generated for each channel, and a single channel image with an increased frame rate was converted to a color channel image. The performance of the proposed temporal super resolution method was confirmed by the simulation.

• Proceedings of the KSRS Conference
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• v.2
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• pp.590-593
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• 2006

Timber inventory management includes to measure and update forest attributes, which is crucial information for private companies and public organizations in property assessment and environment monitoring. Field measurement would be accurate, but time-consuming and inefficient. For the reason, remote sensing technology has been an alternative to field measurement from an economic perspective. Among several sensors, LiDAR and Radar interferometry are known for their efficiency for forest monitoring because they are less influenced by weather and light conditions, and provide reasonably accurate vertical/horizontal measurement for a large area in a short period. For example, Shuttle Radar Topography Mission (SRTM) and National Elevation Dataset (NED) in the U.S. can provide tree height information and DSM. On the other hand, LiDAR DSM (the first return) and DEM (the last return) can also present tree height estimation. With respect to project site of loblolly pine plantation in Louisiana in the U.S., the accuracy of SRTM C-Band approach estimating tree height was assessed by the LiDAR approaches. In addition, SRTM X-Band and NED were also compared with the results. Plantation year in inventory GIS, which is directly related to forest age, is high correlated with the difference between SRTM C-Band and NED. As a byproduct, several stands of age mismatch could be recognized using an outlier detection algorithm, and optical satellite image (ETM+) were used to verify the mismatch. The findings of this study were (1) the confirmation of usefulness of the SRTM DSM for forest monitoring and (2) Multi-sensors- Radar, LiDAR, ETM+, MODIS can be used for accuracy improvement of forest inventory GIS altogether.

• Proceedings of the KSRS Conference
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• v.1
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• pp.471-474
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• 2006

Several planktonic dinoflagellates, including Cochlodinium polykrikoides (p), are known to produce red tides responsible for massive fish kills and serious economic loss in turbid Northwest Pacific (Korean and neighboring) coastal waters during summer and fall seasons. In order to mitigate the impacts of these red tides, it is therefore very essential to detect, monitor and forecast their development and movement using currently available remote sensing technology because traditional ship-based field sampling and analysis are very limited in both space and temporal frequency. Satellite ocean color sensors, such as Sea-viewing Wide Field-of-view Sensor (SeaWiFS), are ideal instruments for detecting and monitoring these blooms because they provide relatively high frequency synoptic information over large areas. Thus, the present study attempts to evaluate the red tide index methods (previously developed by Ahn and Shanmugam et al., 2006) to identify potential areas of red tides from SeaWiFS imagery in Korean and neighboring waters. Findings revealed that the standard spectral ratio algorithms (OC4 and LCA) applied to SeaWiFS imagery yielded large errors in Chl retrievals for coastal areas, besides providing false information about the encountered red tides in the focused waters. On the contrary, the RI coupled with the standard spectral ratios yielded comprehensive information about various ranges of algal blooms, while RCA Chl showing a good agreement with in-situ data led to enhanced understanding of the spatial and temporal variability of the recent red tide occurrences in high scattering and absorbing waters off the Korean and Chinese coasts. The results suggest that the red tide index methods for the early detection of red tides blooms can provide state managers with accurate identification of the extent and location of blooms as a management tool.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2568-2574
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• 2005

Control architecture of the action based robot engineering can be divided into two types of deliberate type - and reactive type- controller. Typical deliberate type, slow in reaction speed, is well suited for the realization of the higher intelligence with its capability to forecast on the basis of environmental model according to time flow, while reactive type is suitable for the lower intelligence as it fits to the realization of speedy reactive action by inputting the sensor without a complete environmental model. Looking at the environments in the application areas in which robots are actually used, we can see that they have been mostly covered by the uncertain and unknown dynamic changes depending on time and place, the previously known knowledge being existed though. It may cause, therefore, any deterioration of the robot performance as well as further happen such cases as the robots can not carry out their desired performances, when any one of these two types is solely engaged. Accordingly this paper aims at suggesting Goal-oriented Geometric Model(GGM) Based Intelligent System Architecture which leads the actions of the robots to perform their jobs under variously changing environment and applying the suggested system structure to the navigation issues of the robots. When the robots do perform navigation in human life changing in a various manner with time, they can appropriately respond to the changing environment by doing the action with the recognition of the state. Extending this concept to cover the highest hierarchy without sticking only to the actions of the robots can lead us to apply to the algorithm to perform various small jobs required for the carrying-out of a large main job.