KAWASUE Kikuhito

写真a

Affiliation

Engineering educational research section Mechanical Intelligence Engineering Program

Title

Professor

External Link

Degree 【 display / non-display

  • 博士(工学) ( 1996.1   長崎大学 )

Research Areas 【 display / non-display

  • Informatics / Perceptual information processing

 

Papers 【 display / non-display

  • Pig weight prediction system using RGB-D sensor and AR glasses: analysis method with free camera capture direction Reviewed

    Kawasue K., Wai P.P., Win K.D., Lee G., Iki Y.

    Artificial Life and Robotics   28 ( 1 )   89 - 95   2023.2

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    Authorship:Lead author   Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher:Artificial Life and Robotics  

    Pig weights are important indicator for the healthcare and the economic operation of pig farms, and the development of a system to easily estimate these weights is desired. Although load cells are usually used for actual measurement in pig farms, it is not easy to guide pigs weighing more than 100 kg to the scales because many pigs do not like to get on the scales. Therefore, a convenient pig weight estimation system using RGB-D sensors has been developed. An RGB-D sensor (Intel Realsense D455) is used as the sensing device for weight estimation. Weight estimation is performed on 3D point cloud data of photographed pig images. When capturing pigs, it is desirable to have a constant camera orientation toward the pigs However, it is not easy to always capture from the same direction because pigs move around quickly in the piggery. A method with a high degree of freedom in the capture direction by exploiting pig symmetry of the pig’s body is introduced in this paper. The system is applied for a wearing device using AR (Augmented Reality) glasses. Experimental results show the feasibility of this system.

    DOI: 10.1007/s10015-022-00827-x

    Scopus

  • Pig Weight Estimation by Camera and Its Appliation Invited

    KAWASUE Kikuhito

    Journal of The Society of Instrument and Control Engineers   61 ( 10 )   729 - 732   2022.10

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    Authorship:Lead author   Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher:The Society of Instrument and Control Engineers  

    DOI: 10.11499/sicejl.61.729

    CiNii Research

  • Identifying-and-counting based monitoring scheme for pigs by integrating BLE tags and WBLCX antennas Reviewed

    Lee G., Ogata K., Kawasue K., Sakamoto S., Ieiri S.

    Computers and Electronics in Agriculture   198   2022.7

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    Language:Japanese   Publishing type:Research paper (scientific journal)   Publisher:Computers and Electronics in Agriculture  

    Recently, the Internet of Things (IoT) technologies have been applied to pig monitoring. Among these, electronic tags help identify individual growing-finishing pigs. Nevertheless, the tags are insufficient to achieve accurate and reliable monitoring in pigsties. Instead, advanced processing data for individual behaviors, such as visit times in the feeding and resting areas and the number of movements between these areas, are required. Numerically measuring the movements of individual pigs in the pigsty is a precondition for obtaining these data. This paper proposes a monitoring scheme of a large herd of pigs for individual identification and counting. As a technical solution, a monitoring system is developed using Bluetooth low-energy (BLE) tags and wireless broadband leaky coaxial cable (WBLCX) antennas. The monitoring system collects access data transmitted from the BLE tags attached to individual pigs. Then the monitoring scheme estimates the location and movement of each pig by computing the collected data. A series of experiments was conducted to evaluate the detection characteristics between the BLE tags and the WBLCX antennas and to show their performances. In addition, the effectiveness for the proposed area-determination algorithm and the monitoring system was verified by field experiments on a pig farm in Japan. Our experimental results are summarized as follows. First, data comparisons between the area-determination algorithm and visual inspections confirmed the validity of the proposed monitoring scheme. Secondly, by the monitoring scheme, the area movements and the dwell times of pigs in a pigsty could be investigated. From the experimental results, the use of the proposed monitoring is expected to be able to observe the locations and movements for large herds of pigs in the pigsty. This paper proposes a monitoring scheme based on identifying and counting of individual pigs, explains the details of the monitoring scheme on the basis of hardware configurations, and verifies its effectiveness and feasibility via experiments.

    DOI: 10.1016/j.compag.2022.107070

    Scopus

  • Volume-Based Pig Weight Estimation Using an RGB-D Sensor Reviewed

    Khin Dagon Win, Kikuhito Kawasue, Pwint Phoo Wai, Yusuke Iki

    Proc. of 27 nd AROB (Artificial Life an Robotics)   2022.1

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    Authorship:Corresponding author   Publishing type:Research paper (international conference proceedings)  

  • Extraction of Pig Outline and Estimation of Body Weight by Detection of Multiple Lines Structured Light Using Discrete Fourier Transform Reviewed

    WIN Khin Dagon, KAWASUE Kikuhito, YOSHIDA Kumiko

    Engineering in Agriculture, Environment and Food   13 ( 3 )   81 - 88   2021.8

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    Authorship:Corresponding author   Language:English   Publishing type:Research paper (scientific journal)   Publisher:Asian Agricultural and Biological Engineering Association  

    Because pig farms are labor intensive, computer vision-based pig weight estimation system that involve robust maintenance-free parts have been developed; with this system, information on the shape of the pig is used to estimate the pig's weight. While 2D shape information can be useful, 3D information is preferable to ensure more accurate weight estimates. The approach described here uses multiple lines structured light laser projection to extract such 3D shape information. This method allows for the extraction of a clear pig image regardless of the environment and offers more accurate pig weight estimates. This paper introduces the robust image processing system and describes its effectiveness for practical use on pig farms.

    DOI: 10.37221/eaef.13.3_81

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MISC 【 display / non-display

  • 「AR(拡張現実)を用いた豚の体重推定システム」

    川末紀功仁

    BIO九州   2021.10

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    Publishing type:Article, review, commentary, editorial, etc. (trade magazine, newspaper, online media)  

  • カメラによる豚の体重推定とソーティングシステム

    川末紀功仁

    ゼロからわかる!スマート養豚 緑書房   2021.6

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    Publishing type:Article, review, commentary, editorial, etc. (trade magazine, newspaper, online media)  

  • 畜産王国 宮崎でスマート畜産技術を発信!

    川末紀功仁

    臨床獣医   2020.8

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    Language:Japanese   Publishing type:Article, review, commentary, editorial, etc. (trade magazine, newspaper, online media)  

  • 円形シフト法による三次元計測技術

    川末紀功仁

    三次元画像センシングの新展開   2015.5

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    Language:Japanese   Publishing type:Article, review, commentary, editorial, etc. (scientific journal)   Publisher:(株)エヌ・ティー・エス  

  • 液晶パネルを用いた高精細画像計測

    川末紀功仁

    ケミカルエンジニアリング   54 ( 2 )   1 - 6   2009.2

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    Language:Japanese   Publishing type:Article, review, commentary, editorial, etc. (trade magazine, newspaper, online media)   Publisher:化学工業社  

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Presentations 【 display / non-display

  • 豚の自動選別システム

    (2) 須本 修平、辻野 悟史、荒武 成道、川末 紀功仁

    計測自動制御学会システムインテグレーション部門講演会  2021.12 

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    Event date: 2021.12.15 - 2021.12.17

    Presentation type:Oral presentation (general)  

  • 機械学習を用いた豚の体重推定

    金澤 波音、宮崎大学工学部 川末 紀功仁、Khin Dagon, Win、壱岐 侑祐

    計測自動制御学会システムインテグレーション部門講演会 

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    Event date: 2021.12.15 - 2021.12.17

    Presentation type:Oral presentation (general)  

  • AI による豚の体重推定システム

    川末紀功仁,吉田久美子,Khin Dagon Win

    計測自動制御学会システムインテグレーション部門講演会 

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    Event date: 2019.12.12 - 2019.12.14

    Language:Japanese   Presentation type:Oral presentation (general)  

  • カメラによる豚の自動体重選別装置

    吉田久美子,川末紀功仁, Khin Dagon Win

    計測自動制御学会システムインテグレーション部門講演会 

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    Event date: 2019.12.12 - 2019.12.14

    Language:Japanese   Presentation type:Oral presentation (general)  

  • 豚舎実環境下におけるカメラによる豚の体重推定システム

    吉田 久美子, 川末 紀功仁, Khin Dagon Win

    View2019 

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    Event date: 2019.12.5 - 2019.12.6

    Language:English   Presentation type:Oral presentation (general)  

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Awards 【 display / non-display

  • 2021年農業技術10大ニュース

    2021.12   農林水産省  

    川末紀功仁

  • SI2021優秀講演

    2021.12   計測自動制御学会  

    金澤波音、川末紀功仁、Khin Dagon Win, 壱岐侑祐

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    Award type:Award from Japanese society, conference, symposium, etc.  Country:Japan

  • SI2019優秀講演

    2019.12   計測自動制御学会  

    吉田久美子,川末紀功仁,Khin Dagon Win

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    Award type:Award from Japanese society, conference, symposium, etc.  Country:Japan

  • SI2011優秀講演

    2011.12   計測自動制御学会  

    川末紀功仁,小松貴幸,李 涛

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    Award type:Award from Japanese society, conference, symposium, etc.  Country:Japan

  • 日本機械学会奨励賞

    1997.3   日本機械学会  

    川末紀功仁

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    Award type:International academic award (Japan or overseas)  Country:Japan

Grant-in-Aid for Scientific Research 【 display / non-display

  • 大群管理下におけるAIとIoTによる養豚の自動化

    Grant number:20H03108  2020.04 - 2024.03

    独立行政法人日本学術振興会  科学研究費補助金  基盤研究(B)

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    Authorship:Principal investigator 

    国内の養豚場では大規模化が進んでいる。しかしながら,人手不足などの問題から作業者当たりの飼育頭数が増加すると,豚の状態(体重,健康状態)を一頭一頭確認し,状態に応じて個体別に対応することは困難になる。そこで,本研究では,大群飼育されている養豚場において,豚の状態を自動観測し,観測された状態に応じて豚の行動を制御する個体管理自動化システムを構築する。具体的にはカメラで取得された画像からAIにより高精度に体重を測定する技術と局所体温検出技術,およびIoTによる遠隔制御技術を組み合わせて自動管理を実現する。これにより,体重に応じた餌の選択や異常のある豚の選別が自動化される。

  • 非接触画像計測による和牛の体重推定システムの開発

    2011.04 - 2013.03

    科学研究費補助金 

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    Authorship:Principal investigator 

    肉用牛において体重を測定することは重要であるが,牛衡器を保有している農家はほとんど無く,一般的には熟練した人が目視で重量を推定するか,局所的な体各部測定値から体重を推定する方法がとられている。そのため,可搬性があり簡便な牛の体重測定方法の開発が期待されている。そこで画像計測技術を用い,非接触で和牛の体重を自動推定するシステムを試作する。手に保持したレーザ投光器によりマーカーとなるレーザを測定したい箇所に照射し,CCDカメラで体表面に現れるレーザ輝点(輝線)を撮影することで三次元位置を計測し,体重算出式を用いて体重を求めるハンディタイプの計測システムを開発することを目的とする。

  • 自動走行ロボットによる下水管形状計測技術の確立

    2006.04 - 2009.03

    科学研究費補助金 

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    Authorship:Principal investigator 

    下水管軸に対して垂直方向にレーザ光を投光し,管内面で反射する光をCCDで撮影することで下水管形状を計測するシステムを試作した.

  • 高速円形シフトによる多点の三次元位置と速度の同時計測

    2005.04 - 2008.03

    科学研究費補助金  基盤研究(B)

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    Authorship:Principal investigator 

    画像による三次元計測を行うにあたり,計測点が多数存在する場合,それぞれの軌跡が重なり画像処理が困難になる.そこで,撮影される中心点を利用してそれぞれの円軌跡の切り出しを行うアルゴリズムを開発した.

  • 不規則な運動を伴う三次元現象の計測に関する研究

    2005.04 - 2006.03

    科学研究費補助金 

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Other research activities 【 display / non-display

  • AI用豚体重推定データベースの構築

    2019.04 - 2020.03

Available Technology 【 display / non-display