低コストのカラス被害解消のためのAIシステム開発

カテゴリ: 論文誌(論文単位)

グループ名: 【C】電子・情報・システム部門

発行日: 2022/11/01

タイトル(英語): Development of a Low Cost Crow Deterrent AI System

著者名: 伊藤　優太（中京大学），吉川　健太（中京大学），イ　ジェフン（中京大学），ラシキア　城治（中京大学）

著者名(英語): Yuta Itou (Chukyo University), Kenta Yoshikawa (Chukyo University), Lee JaeHun (Chukyo University), George Lashkia (Chukyo University)

キーワード: 深層学習，画像処理，カラス被害解消_x000D_　　deep learning，Image processing，crow deterrent system

要約(英語): Damage caused by crows such as damage to crops, scattering garbage on the streets, assaulting people walking beneath their nests, etc. has become a problem in various parts of the country. There are several damage abatement techniques such as protective nets, scarecrows, flashing lights, etc. However, existing methods have limited effects and are not always practical. Research using promising AI systems use expensive equipment. In this research, we propose an end-to-end real-time crow deterrent system based on the latest deep learning technology, using low-cost equipment. The proposed system detects the crow arrival and generates randomly frightening noises, including predator or bird distress calls. We conducted various experiments and confirmed the effectiveness of the proposed system.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.142 No.11 （2022） 特集：電気関係学会関西連合大会

本誌掲載ページ: 1235-1242 p

原稿種別: 論文／日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/142/11/142_1235/_article/-char/ja/