• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.8
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• pp.327-342
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• 2017

In this paper, we introduce an integrated processing system of smart sensor data for IoT service which collects sensor data and efficiently processes it. Based on the technology of collecting sensor data to the development of the IoT field and sending it to the network · Based on the receiving technology, as various projects such as smart homes, autonomous running vehicles progress, the sensor data is processed and effectively An autonomous control system to utilize has been a problem. However, since the data type of the sensor for monitoring the autonomous control system varies according to the domain, a sensor data integration processing system applying the autonomous control system to various different domains is necessary. Therefore, in this paper, we introduce the Smart Sensor Data Integrated Processing System, apply it and use the window as a reference to process internal and external sensor data 1) receiveData, 2) parseData, 3) addToDatabase 3 With the process of the stage, we provide and implement the automatic window opening / closing system "Smart Window" which ventilates to create a comfortable indoor environment by autonomous control system. As a result, standby information is collected and monitored, and machine learning for performing statistical analysis and better autonomous control based on the stored data is made possible.

• The Journal of Society for e-Business Studies
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• v.27 no.2
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• pp.205-218
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• 2022

Recently, digital transformation in manufacturing has been accelerating. It results in that the data collection technologies from the shop-floor is becoming important. These approaches focus primarily on obtaining specific manufacturing data using various sensors and communication technologies. In order to expand the channel of field data collection, this study proposes a method to automatically collect manufacturing data based on vision-based artificial intelligence. This is to analyze real-time image information with the object detection and tracking technologies and to obtain manufacturing data. The research team collects object motion information for each frame by applying YOLO (You Only Look Once) and DeepSORT as object detection and tracking algorithms. Thereafter, the motion information is converted into two pieces of manufacturing data (production performance and time) through post-processing. A dynamically moving factory model is created to obtain training data for deep learning. In addition, operating scenarios are proposed to reproduce the shop-floor situation in the real world. The operating scenario assumes a flow-shop consisting of six facilities. As a result of collecting manufacturing data according to the operating scenarios, the accuracy was 96.3%.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.4
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• pp.110-126
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• 2024

Several studies have focused on developing the safest and most efficient path from the current location to the available parking area for vehicles entering a parking lot. In the present study, the parking lot structure and parking environment such as the lane width, width, and length of the parking space, were vaired by referring to the actual parking lot with vertical and horizontal parking. An automatic parking path planning model was proposed by collecting path data by various setting angles and environments such as a starting point and an arrival point, by putting the collected data into a deep learning model. The existing algorithm(Hybrid A-star, Reeds-Shepp Curve) and the deep learning model generate similar paths without colliding with obstacles. The distance and the consumption time were reduced by 0.59% and 0.61%, respectively, resulting in more efficient paths. The switching point could be decreased from 1.3 to 1.2 to reduce driver fatigue by maximizing straight and backward movement. Finally, the path generation time is reduced by 42.76%, enabling efficient and rapid path generation, which can be used to create a path plan for autonomous parking during autonomous driving in the future, and it is expected to be used to create a path for parking robots that move according to vehicle construction.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.221-241
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• 2018

As we enter the knowledge society, the importance of information as a new form of capital is being emphasized. The importance of information classification is also increasing for efficient management of digital information produced exponentially. In this study, we tried to automatically classify and provide tailored information that can help companies decide to make technology commercialization. Therefore, we propose a method to classify information based on Korea Standard Industry Classification (KSIC), which indicates the business characteristics of enterprises. The classification of information or documents has been largely based on machine learning, but there is not enough training data categorized on the basis of KSIC. Therefore, this study applied the method of calculating similarity between documents. Specifically, a method and a model for presenting the most appropriate KSIC code are proposed by collecting explanatory texts of each code of KSIC and calculating the similarity with the classification object document using the vector space model. The IPC data were collected and classified by KSIC. And then verified the methodology by comparing it with the KSIC-IPC concordance table provided by the Korean Intellectual Property Office. As a result of the verification, the highest agreement was obtained when the LT method, which is a kind of TF-IDF calculation formula, was applied. At this time, the degree of match of the first rank matching KSIC was 53% and the cumulative match of the fifth ranking was 76%. Through this, it can be confirmed that KSIC classification of technology, industry, and market information that SMEs need more quantitatively and objectively is possible. In addition, it is considered that the methods and results provided in this study can be used as a basic data to help the qualitative judgment of experts in creating a linkage table between heterogeneous classification systems.

• Korean Journal of Remote Sensing
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• v.37 no.6_2
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• pp.1859-1867
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• 2021

This study investigated seasonal characteristics of the particulate matter (PM) in the atmosphere and rainwater quality in Busan, South Korea, and evaluated the seasonal effect of PM₁₀ concentration in the atmosphere on the rainwater quality using multivariate statistical analysis. The concentration of PM in the atmosphere and meteorological observations(daily precipitation amount and rainfall intensity) are obtained from automatic weather systems (AWS) by the Korea Meteorological Administration (KMA) from March 2020 to August 2020. Rainwater samples (n = 216, 13 rain events) were continuously collected from the beginning of the precipitation using the rainwater collecting device at Pukyong National University. The samples were analyzed for pH, EC (electrical conductivity), water-soluble cations(Na⁺, Mg²⁺, K⁺, Ca²⁺, and NH₄⁺), and anions(Cl^-, NO₃^-, and SO₄^2-). The concentration of PM₁₀ in the atmosphere was steadily measured before and after the precipitation with a custom-built PM sensor node. The measured data were analyzed using principal component analysis (PCA) and Pearson correlation analysis to identify relationships between the concentration of PM₁₀ in the atmosphere and rainwater quality. In spring, the daily average concentration of PM₁₀ (34.11 ㎍/m³) and PM_2.5 (19.23 ㎍/m³) in the atmosphere were relatively high, while the value of daily precipitation amount and rainfall intensity were relatively low. In addition, the concentration of PM₁₀ in the atmosphere showed a significant positive correlation with the concentration of water-soluble ions (r = 0.99) and EC (r = 0.95) and a negative correlation with the pH (r = -0.84) of rainwater samples. In summer, the daily average concentration of PM₁₀ (27.79 ㎍/m³) and PM_2.5 (17.41 ㎍/m³) in the atmosphere were relatively low, and the maximum rainfall intensity was 81.6 mm/h, recording a large amount of rain for a long time. The results indicated that there was no statistically significant correlation between the concentration of PM₁₀ in the atmosphere and rainwater quality in summer.

• Korean Journal of Ecology and Environment
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• v.54 no.4
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• pp.272-279
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• 2021

A pump-type eDNA filtering system that can control voltage and hydraulic pressure respectively has been developed, and applied a filter case that can filter out without damaging the filter. The filtering performance of the developed system was evaluated by comparing the eDNA concentration with the conventional vacuum-pressured filtering method at the catchment conduit intake reservoir. The developed system was divided into a voltage control (manual pump system) method and a pressure control (automatic pump system) method, and the pressure was measured during filtering and the pressure change of each system was compared. The voltage control method started with 65 [KPa] at the beginning of the filtering, and as the filtering time elapsed, the amount of filtrate accumulated in the filter increased, so the pressure gradually increased. As a result of controlling the pressure control method to maintain a constant pressure according to the designed algorithm, there was a difference in the width of the hydraulic pressure fluctuation during the filtering process according to the feedback time of the hydraulic pressure sensor, and it was confirmed that the pressure was converged to the target pressure. The filtering performance of the developed system was confirmed by measuring the eDNA concentration and comparing the voltage control method and the hydraulic control method with the control group. The voltage control method obtained similar results to the control group, but the hydraulic control method showed lower results than the control group. It is considered that the low eDNA concentration in the hydraulic control method is due to the large pressure deviation during filtering and maintaining a constant pressure during the filtering process. Therefore, rather than maintaining a constant pressure during filtering, it was confirmed that a voltage control method in which the pressure is gradually increased as the filtrate increases with the lapse of filtering time is suitable for collecting eDNA. As a result of comparing the average concentration of eDNA in lentic zone and lotic zone as a control group, it was found to be 96.2 [ng µL^-1] and 88.4 [ng µL^-1l], respectively. The result of comparing the average concentration of eDNA by the pump method was also high in the lentic zone sample as 90.7 [ng µL^-1] and 74.8 [ng µL^-1] in the lentic zone and the lotic zone, respectively. The high eDNA concentration in the lentic zone is thought to be due to the influence of microorganisms including the remaining eDNA.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.113-125
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• 2013

Every company wants to know customer's requirement and makes an effort to meet them. Cause that, communication between customer and company became core competition of business and that important is increasing continuously. There are several strategies to find customer's needs, but VOC (Voice of customer) is one of most powerful communication tools and VOC gathering by several channels as telephone, post, e-mail, website and so on is so meaningful. So, almost company is gathering VOC and operating VOC system. VOC is important not only to business organization but also public organization such as government, education institute, and medical center that should drive up public service quality and customer satisfaction. Accordingly, they make a VOC gathering and analyzing System and then use for making a new product and service, and upgrade. In recent years, innovations in internet and ICT have made diverse channels such as SNS, mobile, website and call-center to collect VOC data. Although a lot of VOC data is collected through diverse channel, the proper utilization is still difficult. It is because the VOC data is made of very emotional contents by voice or text of informal style and the volume of the VOC data are so big. These unstructured big data make a difficult to store and analyze for use by human. So that, the organization need to automatic collecting, storing, classifying and analyzing system for unstructured big VOC data. This study propose an intelligent VOC analyzing system based on opinion mining to classify the unstructured VOC data automatically and determine the polarity as well as the type of VOC. And then, the basis of the VOC opinion analyzing system, called domain-oriented sentiment dictionary is created and corresponding stages are presented in detail. The experiment is conducted with 4,300 VOC data collected from a medical website to measure the effectiveness of the proposed system and utilized them to develop the sensitive data dictionary by determining the special sentiment vocabulary and their polarity value in a medical domain. Through the experiment, it comes out that positive terms such as "칭찬, 친절함, 감사, 무사히, 잘해, 감동, 미소" have high positive opinion value, and negative terms such as "퉁명, 뭡니까, 말하더군요, 무시하는" have strong negative opinion. These terms are in general use and the experiment result seems to be a high probability of opinion polarity. Furthermore, the accuracy of proposed VOC classification model has been compared and the highest classification accuracy of 77.8% is conformed at threshold with -0.50 of opinion classification of VOC. Through the proposed intelligent VOC analyzing system, the real time opinion classification and response priority of VOC can be predicted. Ultimately the positive effectiveness is expected to catch the customer complains at early stage and deal with it quickly with the lower number of staff to operate the VOC system. It can be made available human resource and time of customer service part. Above all, this study is new try to automatic analyzing the unstructured VOC data using opinion mining, and shows that the system could be used as variable to classify the positive or negative polarity of VOC opinion. It is expected to suggest practical framework of the VOC analysis to diverse use and the model can be used as real VOC analyzing system if it is implemented as system. Despite experiment results and expectation, this study has several limits. First of all, the sample data is only collected from a hospital web-site. It means that the sentimental dictionary made by sample data can be lean too much towards on that hospital and web-site. Therefore, next research has to take several channels such as call-center and SNS, and other domain like government, financial company, and education institute.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.24 no.2
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• pp.65-71
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• 2018

Paper packs, glass bottles, metal cans, and plastic materials are classified according to packaging material recycling groups that are Extended Producer Responsibility (EPR). In the case of waste paper pack, the compressed cartons are dissociated to separate polyethylene films and other foreign substance, and then these are washed, pulverized and dried to produce toilet paper. Glass bottle for recycling is provided to the bottle manufacturers after the process of collecting the waste glass bottle, removing the foreign substance, sorting by color, crushing, raw materializing process. Waste glass recycling technology of Korea is largely manual, except for removal of metal components and low specific gravity materials. Metal can is classified into iron and aluminum cans through an automatic sorting machine, compressed, and reproduced as iron and aluminum through a blast furnace. In the case of composite plastic material, the selected compressed product is crushed and then recycled through melt molding and refined products are produced through solid fuel manufacturing steps through emulsification and compression molding through pyrolysis. In the recycling process of paper packs, glass bottles, metal cans, and plastic materials, the influx of recycled materials and other substances interferes with the recycling process and increases the recycling cost and time. Therefore, the government needs to improve the legal system which is necessary to use materials and structure that are easy to recycle from the design stage of products or packaging materials.

• Journal of Intelligence and Information Systems
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• v.17 no.2
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• pp.119-128
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• 2011

The Sensor technology and portable device capability able to collect recent user information and the information about the surrounding environment haven been highly developed. A user can be made use of various contents and the option is also extending with this technology development. In particular, the initial portable device had simply a call function, but now that has evolved into 'the 4th screen' which including movie, television, PC ability. also, in the past, a portable device to provided only the services of a SMS, in recent years, it provided to interactive video service, and it include technology which providing various contents. Also, it is rising as media which leading the consumption of contents, because it can be used anytime, anywhere. However, the contents available for the nature of user's handheld devices are limited. because it is very difficult for making the contents separately according to various device specification. To find a solution to this problem, the study on one contents from several device has been progressing. The contents conversion technology making use of the profile of device out of this study comes to the force and profile study has been progressing for this. Furthermore, Demand for a user is also increased and the study on the technology collecting, analyzing demands has been making active progress. And what is more, Grasping user's demands by making use of this technology and the study on the technology analyzing, providing contents has been making active progress as well. First of all, there is a method making good use of ZigBee, Bluetooth technology about the sensor for gathering user's information. ZigBee uses low-power digital radio for wireless headphone, wireless communication network, and being utilized for smart energy, automatic home system, wireless communication application and wireless sensor application. Bluetooth, as industry standards of PAN(Personal Area Networks), is being made of use of low power wireless device for the technology supporting data transmission such as drawing file, video file among Bluetooth device. With analyzing the collected information making use of this technology, it utilizes personalized service based on network knowledge developed by ETRI to service contents tailor-made for a user. Now that personalized service builds up network knowledge about user's various environments, the technology provides context friendly service constructed dynamically on the basis of this. The contents to service dynamically like this offer the contents that it converses with utilizing device profile to working well. Therefore, this paper suggests the system as follow. It collects the information, for example of user's sensitivity, context and location by using sensor technology, and generates the profile as a means of collected information as sensor. It collects the user's propensity to the information by user's input and event and generates profile in the same way besides the gathered information by sensor. Device transmits a generated profile and the profile about a device specification to proxy server. And proxy server transmits a profile to each profile management server. It analyzes profile in proxy server so that it selects the contents user demand and requests in contents server. Contents server receives a profile of user portable device from device profile server and converses the contents by using this. Original source code of contents convert into XML code using the device profile and XML code convert into source code available in user portable device. Thus, contents conversion process is terminated and user friendly system is completed as the user transmits optimal contents for user portable device.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1615-1633
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• 2023

Sargassum horneri is one of the floating algae in the sea, which breeds in large quantities in the Yellow Sea and East China Sea and then flows into the coast of Republic of Korea, causing various problems such as destroying the environment and damaging fish farms. In order to effectively prevent damage and preserve the coastal environment, the development of Sargassum horneri detection algorithms using satellite-based remote sensing technology has been actively developed. However, incorrect detection information causes an increase in the moving distance of ships collecting Sargassum horneri and confusion in the response of related local governments or institutions,so it is very important to minimize false detections when producing Sargassum horneri spatial information. This study applied technology to automatically remove false detection results using the GOCI-II-based Sargassum horneri detection algorithm of the National Ocean Satellite Center (NOSC) of the Korea Hydrographic and Oceanography Agency (KHOA). Based on the results of analyzing the causes of major false detection results, it includes a process of removing linear and sporadic false detections and green algae that occurs in large quantities along the coast of China in spring and summer by considering them as false detections. The technology to automatically remove false detection was applied to the dates when Sargassum horneri occurred from February 24 to June 25, 2022. Visual assessment results were generated using mid-resolution satellite images, qualitative and quantitative evaluations were performed. Linear false detection results were completely removed, and most of the sporadic and green algae false detection results that affected the distribution were removed. Even after the automatic false detection removal process, it was possible to confirm the distribution area of Sargassum horneri compared to the visual assessment results, and the accuracy and precision calculated using the binary classification model averaged 97.73% and 95.4%, respectively. Recall value was very low at 29.03%, which is presumed to be due to the effect of Sargassum horneri movement due to the observation time discrepancy between GOCI-II and mid-resolution satellite images, differences in spatial resolution, location deviation by orthocorrection, and cloud masking. The results of this study's removal of false detections of Sargassum horneri can determine the spatial distribution status in near real-time, but there are limitations in accurately estimating biomass. Therefore, continuous research on upgrading the Sargassum horneri monitoring system must be conducted to use it as data for establishing future Sargassum horneri response plans.