Work

Development of AI-based smart box trap system for capturing a harmful wild boar

Year: 2025

Type: article

Abstract: The invasion of crops by harmful wild animals is a significant global issue, with Japan experiencing annual economic losses amounting to billions of yens. To mitigate this problem, most farmers use manually triggered traps. However, these traps are often ineffective and fail to capture the targeted animals. Previous researches have primarily focused on studying wild boar behavior, detecting their presence in crops, and using scare tactics to prevent field destruction. This paper introduces an intelligent system designed to capture wild boars efficiently. The developed system integrates the YOLO recognition algorithm with traditional traps to automatically identify and capture wild boars. By adopting this intelligent approach, the presence of wild boars can be significantly reduced, providing farmers with better security for their crops.

Source: ROBOMECH Journal

DOI: 10.1186/s40648-025-00290-w

Authors: Francis Ifaso Besala, Ryunosuke Niimoto, Jae Hoon Lee, Shingo Okamoto

Institution: Ehime University

Language: English

Topic: Smart Agriculture and AI

Subfield: Plant Science

Field: Agricultural and Biological Sciences

Domain: Life Sciences

SDGs: Zero hunger, Life on land

Open Access status: gold

Estimated APC paid: $1,690