• Title/Summary/Keyword: animal tracking system

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A Moving Object Management System for Location Based Service (위치기반서비스를 위한 이동 객체 관리 시스템)

  • 안윤애
    • Journal of the Korea Computer Industry Society
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    • v.4 no.12
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    • pp.986-998
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    • 2003
  • A moving object management system manages spatiotemporal data o( moving objects which change their location continuously over time such as people, animals, cars, cellular phones, and so on. This system can be applied to location based services such as vehicle tracking systems, digital battlefields, and animal habitat management. The existing systems neither suggest location estimation of the moving objects nor handle the loss data of the moving objects in real-time environment. Thus the existing systems have problems that they give the uncertain results of the query processing to the user query. In this paper, we design a new moving object management system. The proposed system processes the past and future location information of the moving objects by the location change function. Also we propose a location triggering method, which supplements loss of the location data of the mobile objects in real-time environment. Finally, we implement and apply the proposed system to a vehicle tracking system based on PDA. Thus we ascertain that the proposed system can be applied to the location based system.

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Development of Animal Tracking Method Based on Edge Computing for Harmful Animal Repellent System. (엣지컴퓨팅 기반 유해조수 퇴치 드론의 동물 추적기법 개발)

  • Lee, Seul;Kim, Jun-tae;Lee, Sang-Min;Cho, Soon-jae;Jeong, Seo-hoon;Kim, Hyung Hoon;Shim, Hyun-min
    • Proceedings of the Korea Information Processing Society Conference
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    • 2020.11a
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    • pp.224-227
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    • 2020
  • 엣지컴퓨팅 기반 유해조수 퇴치 Drone의 유해조수 추적 기술은 Doppler Sensor를 이용해 사유지에 침입한 유해조수를 인식 후 사용자에게 위험 요소에 대한 알림 서비스를 제공한다. 이후 사용자는 Drone의 Camera와 전용 애플리케이션을 이용해 경작지를 실시간으로 보며 Drone을 조종한다. Camera는 Tensor Flow Object Detection Deep Learning을 적용하여 유해조수를 학습 및 파악, 추적한다. 이후 Drone은 Speaker와 Neo Pixel LED Ring을 이용해 유해조수의 시각과 청각을 자극해 도망을 유도하며 퇴치한다. Tensor Flow object detection을 핵심으로 Drone에 접목했고 이를 위해 전용 애플리케이션을 개발했다.

Development of Microsatellite Markers for Discriminating Native Korean and Imported Cattle Breeds (한국 재래품종과 외래품종의 구별을 위한 초위성체 마커의 개발)

  • Kim, Seungchang;Cho, Chang-Yeon;Roh, Hee-Jong;Yeon, Seong-Heum;Choi, Seong-Bok
    • Journal of Life Science
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    • v.27 no.4
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    • pp.464-470
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    • 2017
  • Three Korean native cattle (KNC) and seven exotic breeds (Chikso, Hanwoo, Jeju black, Holstein, Japanese black, Charolais, Angus, Hereford, Simmental, and Cross breed) were characterized by using five microsatellite (MS) markers (INRA30, TGLA325, UMN0803, UMN0905, and UMN0929) from the sex chromosome. Genetic diversity was evaluated across the 10 breeds by using the number of alleles per locus, allele frequency, heterozygosity, and polymorphism information content (PIC) to search for locus and/or breed specific alleles, allowing a rapid and cost-effective identification of cattle samples, avoiding mislabeling of commercial beef. It was divided into two main groups from STRUCTURE analysis, one corresponding to KNC and the other to exotic cattle breeds. These results also showed specific genetic differences between KNC and exotic breeds. Nei's standard genetic distance was calculated and used in the construction of a neighbor-joining tree. Results evidenced a correspondence between genetic distance, breeds' history, and their geographic origin, and a clear separation between KNC and exotic breeds. Overall, this study evidenced that DNA markers can discriminate between domestic and imported beef, contributing to the knowledge on cattle breeds' genetic diversity and relationships by using MS markers of the sex chromosome. These markers would be useful for inhibitory effect about false sales and for building an effective tracking system.

Mathematical modeling for flocking flight of autonomous multi-UAV system, including environmental factors

  • Kwon, Youngho;Hwang, Jun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.14 no.2
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    • pp.595-609
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    • 2020
  • In this study, we propose a decentralized mathematical model for predictive control of a system of multi-autonomous unmanned aerial vehicles (UAVs), also known as drones. Being decentralized and autonomous implies that all members make their own decisions and fly depending on the dynamic information received from other unmanned aircraft in the area. We consider a variety of realistic characteristics, including time delay and communication locality. For this flocking flight, we do not possess control for central data processing or control over each UAV, as each UAV runs its collision avoidance algorithm by itself. The main contribution of this work is a mathematical model for stable group flight even in adverse weather conditions (e.g., heavy wind, rain, etc.) by adding Gaussian noise. Two of our proposed variance control algorithms are presented in this work. One is based on a simple biological imitation from statistical physical modeling, which mimics animal group behavior; the other is an algorithm for cooperatively tracking an object, which aligns the velocities of neighboring agents corresponding to each other. We demonstrate the stability of the control algorithm and its applicability in autonomous multi-drone systems using numerical simulations.

Analysis of Behavioral Characteristics of Broilers by Feeding, Drinking, and Resting Spaces according to Stocking Density using Image Analysis Technique (영상분석기법을 활용한 사육밀도에 따른 급이·급수 및 휴식공간별 육계의 행동특성 분석)

  • Kim, Hyunsoo;Kang, HwanKu;Kang, Boseok;Kim, ChanHo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.12
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    • pp.558-569
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    • 2020
  • This study examined the frequency of a broiler's stay in each area as stock density using an ICT-based image analysis technique from the perspective of precision livestock farming (PLF) according to the increase in the domestic broiler farms to understand the normal behavior patterns of broilers by age. The broiler was used in the experimental box (3.3×2.7 m) in a poultry house in Gyeonggi province. The stock densities were 9.5 birds/㎡ (n=85) and 19 birds/㎡ (n=170), respectively, and the frequency of stay by feeding, water, and rest area was monitored using a top-view camera. The image data of three-colored-specific broilers identified as the stock density were acquired by age (12, 16, 22, 27, and 29 days) for six hours. In the collected image data, the object tracking technique was used to record the cumulative movement path by connecting approximately 640,000 frames at 30 fps to quantify the frequency of stay in each area. In each stock density, it was significant in the order of the rest area, feeding, and water area (p<0.001). In 9.5 birds/㎡, it was at 57.9, 24.2, and 17.9 %, and 73.2, 16.8, and 10 % in 19 birds/㎡. The frequency of a broiler's stay could be evaluated in each area as the stock density using an ICT-based image analysis technique that minimizes stress. This method is expected to be used to provide basic material for developing an ICT-based management system through real-time monitoring.

An Energy Consumption Model using Two-Tier Clustering in Mobile Sensor Networks (모바일 센서 네트워크에서 2계층 클러스터링을 이용한 에너지 소비 모델)

  • Kim, Jin-Su
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.17 no.12
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    • pp.9-16
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    • 2016
  • Wireless sensor networks (WSN) are composed of sensor nodes and a base station. The sensor nodes deploy a non-accessible area, receive critical information, and transmit it to the base station. The information received is applied to real-time monitoring, distribution, medical service, etc.. Recently, the WSN was extended to mobile wireless sensor networks (MWSN). The MWSN has been applied to wild animal tracking, marine ecology, etc.. The important issues are mobility and energy consumption in MWSN. Because of the limited energy of the sensor nodes, the energy consumption for data transmission affects the lifetime of the network. Therefore, efficient data transmission from the sensor nodes to the base station is necessary for sensing data. This paper, proposes an energy consumption model using two-tier clustering in mobile sensor networks (TTCM). This method divides the entire network into two layers. The mobility problem was considered, whole energy consumption was decreased and clustering methods of recent researches were analyzed for the proposed energy consumption model. Through analysis and simulation, the proposed TTCM was found to be better than the previous clustering method in mobile sensor networks at point of the network energy efficiency.

A Comparative Study of Juvenile Black-faced Spoonbills Platalea Minor Home Range in Gujido and Chilsando Islets, South Korea (구지도, 칠산도 저어새 유조의 행동권 비교 연구)

  • Son, Seok-Jun;Kang, Jung-Hoon;Kwon, In-Ki;Kim, Dal-Ho;Lee, Ki-Sup;Yoo, Jeong-Chil
    • Korean Journal of Environment and Ecology
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    • v.34 no.2
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    • pp.99-105
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    • 2020
  • Migratory birds use a variety of breeding and wintering sites, and it is particularly important to understand more information on breeding and feeding sites for the conservation and management of endangered species. Black-faced spoonbills (Platalea minor) are an international endangered species distributed in East Asia. The majority of black-faced spoonbills breed on uninhabited islets off the west coast of the Korean Peninsula during the breeding season, and they are distributed in East Asia such as Taiwan, Hong Kong, southern China, Japan, and Jeju island during the winter season. In this study, we used a wild animal location tracking system to analyze and compare home ranges of three black-faced spoonbills spending the post-fledging stage in Gujido islet in Incheon and Chilsando islet in Yeonggwang each in 2015. The tree black-faced spoonbills in Guji islet showed a home range in coastal areas in Hwanghaenam-do and Gangneung-gun. The home range size (mean±SD) was estimated to be 425.49±116.95 ㎢ using 100% MCP, 43.61±18.51 ㎢ using KDE 95%, and 7.46±3.68 ㎢using KDE 50%. The tree black-faced spoonbills in Chilsando islet showed a home range in the Baeksu tidal flat and the Buan Saemangeum area with a size of 99.38±55.29 ㎢ using 100% MCP, 19.87±6.05 ㎢ using KDE 95%, and 1.16±0.53 ㎢ using KDE 50%. The figured indicated that the tree black-faced spoonbills breeding in Gujido islet had a wider home range than those breeding in Chilsando islet. During the post-fledging stage, the home ranges of black-faced spoonbills were mostly breeding in mudflats. Therefore, it is necessary to minimize human intervention, such as the construction of roads and structures and the human access, to protect the habitats during the period.