Death Detection and Removal in High-Density Animal Farming: Technologies, Integration, Challenges, and Prospects

Yutong Han, Liangju Wang (), Wei Jiang and Hongying Wang
Additional contact information
Yutong Han: Department of Engineering, China Agricultural University, Beijing 100083, China
Liangju Wang: Department of Engineering, China Agricultural University, Beijing 100083, China
Wei Jiang: Department of Engineering, China Agricultural University, Beijing 100083, China
Hongying Wang: Department of Engineering, China Agricultural University, Beijing 100083, China

Agriculture, 2025, vol. 15, issue 21, 1-34

Abstract: In high-density commercial farms, the timely detection and removal of dead bodies are essential to maintain the well-being of animals and ensure farm productivity. This review systematically synthesizes 128 published studies, 52 of which are highly related to the death detecting topic, covering diverse animal species and farming scenarios. The review systematically synthesizes existing research on death detection methods, dead body removal systems, and their integration. The death detection process is divided into three key stages: data acquisition, dataset establishment, and data processing. Inspection systems are categorized into fixed and mobile inspection systems, enabling autonomous imaging for death detection. Regarding death removal systems, current research predominantly focuses on hardware design for poultry and aquaculture, but real-farm validation remains limited. Key focuses for future development include enhancing the robustness and adaptability of detection models with high-quality datasets, brainstorming for more feasible designs of removal systems to enhance adaptability to diverse farm conditions, and improving the integration of inspection systems with removal systems to conduct fully automated detection-removal operations. Ultimately, the successful application of these technologies will reduce labor dependence, enhance biosecurity, and support sustainable, high-density large-scale animal farming while ensuring both satisfying production and the welfare of animals.

Keywords: precision livestock farming; inspection system; death removal; machine vision; deep learning; agricultural robotics (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2077-0472/15/21/2249/pdf (application/pdf)
https://www.mdpi.com/2077-0472/15/21/2249/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jagris:v:15:y:2025:i:21:p:2249-:d:1781733

Access Statistics for this article

Agriculture is currently edited by Ms. Leda Xuan

More articles in Agriculture from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().