Deep Learning and Data Management for Monitoring, Automation, and Control of Livestock Environment
A special issue of Agriculture (ISSN 2077-0472). This special issue belongs to the section "Artificial Intelligence and Digital Agriculture".
Deadline for manuscript submissions: 30 August 2026 | Viewed by 1147
Special Issue Editor
Special Issue Information
Dear Colleagues,
The rapid advancement of digital technologies has transformed livestock farming and environmental management into highly automated, data-intensive systems, with precision livestock farming now employing deep learning, machine learning, and big data analytics to monitor animal health, behavior, and welfare, while environmental control systems optimize factors such as ventilation, temperature, and emissions. As these AI-driven systems scale, concerns around data management—including ownership, access, privacy, and transparency—have become increasingly important.
This Special Issue aims to explore the convergence of cutting-edge AI applications with responsible data practices in livestock and environmental systems. We seek to highlight how technological innovations are reshaping animal agriculture and resource management, while addressing the ethical and societal implications of data use in these domains.
We welcome original research, review articles, and case studies focused on the following topics:
- AI and deep learning in livestock monitoring and welfare;
- Automation and control of environmental conditions in animal systems;
- Data management frameworks for agricultural technologies;
- Ethical, legal, and social implications of data-driven animal farming;
- Interoperable, scalable, and open-source AI tools.
This Special Issue encourages interdisciplinary contributions bridging agriculture, computer science, engineering, and social sciences to advance sustainable and trustworthy smart livestock systems
Dr. Ziwen Yu
Guest Editor
Manuscript Submission Information
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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- deep learning
- data management
- precision agriculture
- livestock monitoring
- automation and control
- environmental management
- ethical and social implications
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