• Journal of the Korean Society of Industry Convergence
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• v.25 no.6_1
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• pp.927-939
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• 2022

This study was conducted to develop a Web-GIS based monitoring module of smart city that can effectively respond, manage and improve situation in all stages of illegal dumping management on a city scale. First, five technologies were set for the core technical elements of the module configuration. Five core technical elements are as follows; video screening technology based on motion vector analysis, human behavior detection based on intelligent video analytics technology, mobile app for receiving civil complaints about illegal dumping, illegal dumping risk model and street cleanliness map, Web-GIS based situation monitoring technology. The development contents and results for each set of core technical elements were evaluated. Finally, a Web-GIS based 'illegal dumping monitoring module' was proposed. It is possible to collect and analyze city data at the local government level through operating the proposed module. Based on this, it is able to effectively detect illegal dumpers at relatively low cost and identify the tendency of illegal dumping by systematically managing habitual occurrence areas. In the future, it is expected to be developed in the form of an add-on module of the smart city integration platform operated by local governments to ensure interoperability and scalability.

• Journal of Korea Soil Environment Society
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• v.4 no.1
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• pp.75-83
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• 1999

The purpose of this study is to investigate the chemical characteristics of the leachate for the open(illegal) dumping waste. In this study, the open dumping waste were mixed with 0, 5, 10, 15% of bentonite in each Iysimeter as a rate of weight. The simulation was evaluated by CODcr, ${NO_3}^-$, ${SO_4}^{2-}$, $Cl^-$ and heavy metals in leachate. As a result, the mixed waste with bentonite in all Iysimeters showed the reduction of CODcr and heavy metals were hardly detected. The removal rate of ${NO_3}^-$, ${SO_4}^{2-}$, $Cl^-$ was increased with the mixing rate of bentonite.

• Journal of the Korean Data and Information Science Society
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• v.21 no.5
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• pp.883-890
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• 2010

Illegal waste dumping is one of the major problems that the government agency monitoring water quality has to face. One solution to this problem is to find an efficient way of managing and supervising the water quality under various kinds of conditions. In this article we establish WQMA (water quality monitoring algorithm) based on the time series intervention model. It turns out thatWQMA is quite successful in detecting illegal waste dumping.

• Journal of Korea Multimedia Society
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• v.24 no.11
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• pp.1508-1517
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• 2021

In CCTV environments, a lot of learning image data is required to monitor illegal dumping of garbage with a typical image-based object detection using deep learning method. In this paper, we propose a system to monitor unauthorized dumping of garbage by learning the articular points of the person using only a small number of images without immediate use of the image for deep learning. In experiment, the proposed system showed 74.97% of garbage dumping detection performance with only a relatively small amount of image data in CCTV environments.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.287-288
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• 2020

우리나라의 무단 투기된 쓰레기양은 2019년 2월 기준 33만 톤이며 이를 단속하기 위해 상용화된 쓰레기 무단투기 단속 시스템은 센서를 이용하여 시스템 주변에 사람이 지나가면 영상을 촬영하기 때문에 쓰레기 무단투기자 뿐 아니라 해당 시스템 주변을 지나는 모든 사람을 촬영하기 때문에 불법 쓰레기를 배출하는지 해당 영상을 사람이 일일이 다시 분석해야한다. 본 논문에서는 쓰레기 투기 행위 이미지를 바탕으로 학습시킨 딥러닝 실시간 객체인식 알고리즘인 YOLO-v4를 활용하여 실시간으로 쓰레기 무단투기를 단속하는 시스템을 제시한다.

• Applied Chemistry for Engineering
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• v.27 no.6
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• pp.664-668
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• 2016

The contamination in soil, underground water and river environment became serious due to illegal waste dumping. In this study, our research group analyzed the oil species of illegally disposed oils from J City. After pretreating the mixture of oil, water and solid phases to obtain homogeneous phase components, the physical property analysis, atom analysis, and gas chromatography were performed. From the results showing 11.8% of oxygen content, $-6^{\circ}C$ of pour point and chromatogram pattern. the contaminated oil was identified as a vegetable one. High performance liquid chromatography (HPLC) analysis was also performed in order to know what kind of vegetable oil was, and the ratio of LLO, OOL and POL was found to be high indicating that the disposed oil is majorly the used soybean oil with some vegetable oil mixtures. This study can be used for identifying contaminators for oils from the illegal waste dumping.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.2
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• pp.11-18
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• 2021

A community-centered smart village process model was developed through the theoretical review of the rural field forum. By analyzing the difference in technology demand according to the digital capabilities of leaders by community type, village types were classified and detailed technologies were defined. The smart village process was proposed to enable residents to operate autonomously by inducing continuous interest and participation of local residents through the conception stage, planning stage, implementation and self-reliance stage, and allowing them to cooperate together. The business model canvas was reconstructed to be used in the workshop. It was applied to the village of Yesan-gun. As a result of running a resident workshop using the business model Cambus, the lack of resident awareness and illegal garbage dumping were presented as the first problems to be solved. The value of the village was set as 'a village that is clean and clean with a sense of residents, and a good place to live', and users were expressed as 'family' and 'outsiders'. It was suggested that we meet frequently to convey the value of the village by using broadcasting and announcements as a channel to convey the value. Core activities were to cultivate residents' consciousness, such as implementing a campaign against illegal garbage dumping, and to establish and guide separate collection sites. When a garbage collection center is installed, it was estimated that around 2 million won per month for management costs, and it was investigated that it was possible to spend an hour or so twice a month to solve the problem of illegal dumping. If a method to derive village projects based on the derived business model canvas is developed in the future, it will be more practical.

• Resources Recycling
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• v.16 no.6
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• pp.61-67
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• 2007

Teshima is a quiet and beautiful island, but started to be imaged as an "island of wastes" because of the 600,000 tons of industrial wastes thrown there illegally. Now it symbolizes the problem of industrial wastes in Japan. Teshima development company, an industrial waste disposer, started to dispose industrial wastes illegally in the west side of the island, since the late 1970s. Police Station exposed this illegal act, and arrested 6 persons of the company, including its president, in charge of having violated the Waste Disposal and Public Cleansing Law in 1991. This illegal disposition has continued for 13years until it was exposed by the police. Teshima case of industrial wastes are introduced in this paper.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2013.11a
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• pp.146-147
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• 2013

The oyster shells of about 240,000 tons have been annually produced in south coast of South Korea. However, about 25% of the oyster shells (60,000tons) was recycled as oyster seeding and fertilizer due to the limited amount of consumption for such purposes. The stored amount of oyster shell in the fertilizer manufacturing company is overfilled, and thus cannot accept any more of the waste oyster shells. As a result, landfill and illegal dumping of waste oyster shells have become an increasingly serious issue since 2011. In this research, the problems generated by the oyster shells were investigated through surveying activities. One of the possible alternative solutions that can process large amount of waste economically was found to be the application of oyster shells as a construction materials.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.736-738
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• 2018

최근 딥러닝의 발전에 따라 무인감시, CCTV 등 영상감시 시스템도 지능화되고 있다. 하지만 쓰레기 무단투기 감시는 여전히 관리자가 실시간으로 CCTV 영상을 관제하는 형태로 이루어지고 있다. 이러한 문제를 해결하기 위해 본 논문에서는 CCTV 영상에서 쓰레기 무단투기를 검출하는 방법을 제안하며 검출 방법으로 차 영상과 합성곱 신경망을 이용한다. 실험은 합성곱 신경망에서의 쓰레기봉투 분류 문제 위주로 진행하였다. 합성곱 신경망의 네트워크는 Inception v3를 사용하였으며 실험 결과, 약 99.52%의 쓰레기봉투 분류율을 얻을 수 있었다.