@article{oai:ipsj.ixsq.nii.ac.jp:00234954,
 author = {國枝, 祐希 and 鈴木, 秀和 and Yuki, Kunieda and Hidekazu, Suzuki},
 issue = {6},
 journal = {情報処理学会論文誌},
 month = {Jun},
 note = {自治体職員や地域住民が集積所のゴミ回収状況を確認できるWebサービスがある．従来のゴミ回収状況判定手法は塵芥車に搭載したGPSから得られる位置情報と速度情報に基づいて，ジオフェンシング技術により集積所付近で停止していたら「回収中」，集積所から離反したら「回収済み」と判断していたが，十分な判定精度が得られていなかった．本論文では，塵芥車にゴミを積み込んで圧縮するときに発生する積込動作音をCNN（Convolutional Neural Network）により，リアルタイムで検出する手法を提案する．塵芥車の車載器に提案手法を導入し，フィールド実験によりその有効性を検証する．, There is a web service that allows municipal employees and local residents to check the status of garbage collection at garbage collection stations. A conventional method for detecting the status of garbage collection is based on the location and speed information obtained from GPS data installed in garbage trucks, and uses geo-fencing technology to determine whether garbage is “collecting” when the truck is stopped near a garbage collection station or “collected” when it leaves the station, however, the detection accuracy has not been sufficiently high. This paper proposes a novel method that detects the loading sound of garbage trucks in real time by using a Convolutional Neural Network (CNN). The effectiveness of the proposed method is verified by field experiments using garbage trucks.},
 pages = {1049--1057},
 title = {塵芥車の積込動作音に基づく動的ゴミ回収判定手法},
 volume = {65},
 year = {2024}
}