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Application of Intelligent Systems in Poultry Farming

A special issue of Applied Sciences (ISSN 2076-3417).

Deadline for manuscript submissions: 20 October 2025 | Viewed by 465

Special Issue Editors

College of Agricultural and Environmental Sciences Athens, University of Georgia, Athens, GA, USA
Interests: precision livestock farming; computer vision; agricultural engineering; environmental control
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Poultry Science, University of Georgia, Athens, GA, USA
Interests: precision poultry and livestock farming; climate-smart farming; computer vision; machine learning; sensors; big data; animal behavior and welfare; animal environment; sustainable agriculture
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Biological and Agricultural Engineering, North Carolina State University, Raleigh, NC 27695, USA
Interests: precision livestock farming; precision poultry; artificial intelligence; computer vision; machine learning; sensors; robotics; animal behavior and welfare
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The poultry industry is facing increasing challenges in areas such as productivity, sustainability, and animal welfare. To address these concerns, the integration of smart technologies, electronic devices, and automated control systems has emerged as a promising solution. The adoption of intelligent systems in poultry farming offers substantial benefits, enhancing both operational efficiency and overall farm management.

Despite the remarkable advantages that intelligent systems offer, their adoption in poultry farming remains limited due to barriers related to system integration and automation. To fully harness the potential of these technologies, it is crucial to foster a greater integration of sensor networks, smart systems, and rapid data-response mechanisms. Therefore, this Special Issue focuses on the application and impact analysis of these smart technologies in poultry farming management systems. The use of artificial intelligence (AI), the Internet of Things (IoT), sensor networks, and big data analytics has proven to significantly improve poultry production. These innovations contribute to reduced production costs, minimized labor, and the creation of a more stress-free environment for the poultry, ultimately leading to higher productivity, increased profitability, and more informed decision-making in farm operations.

This Special Issue aims to delve into the potential, innovations, and challenges associated with the implementation of intelligent systems in poultry farming, providing valuable insights into the future of this essential industry.

Dr. Xiao Yang
Dr. Lilong Chai
Dr. Ramesh Bahadur Bist
Guest Editors

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 2400 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

  • poultry industry
  • smart technologies
  • animal welfare
  • artificial intelligence
  • Internet of Things
  • sensor networks
  • big data analytics
  • automation
  • productivity
  • farm management

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Published Papers (1 paper)

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Research

14 pages, 5405 KiB  
Article
Tracking Poultry Drinking Behavior and Floor Eggs in Cage-Free Houses with Innovative Depth Anything Model
by Xiao Yang, Guoyu Lu, Jinchang Zhang, Bidur Paneru, Anjan Dhungana, Samin Dahal, Ramesh Bahadur Bist and Lilong Chai
Appl. Sci. 2025, 15(12), 6625; https://doi.org/10.3390/app15126625 - 12 Jun 2025
Viewed by 276
Abstract
In recent years, artificial intelligence (AI) has significantly impacted agricultural operations, particularly with the development of deep learning models for animal monitoring and farming automation. This study focuses on evaluating the Depth Anything Model (DAM), a cutting-edge monocular depth estimation model, for its [...] Read more.
In recent years, artificial intelligence (AI) has significantly impacted agricultural operations, particularly with the development of deep learning models for animal monitoring and farming automation. This study focuses on evaluating the Depth Anything Model (DAM), a cutting-edge monocular depth estimation model, for its potential in poultry farming. DAM leverages a vast dataset of over 62 million images to predict depth using only RGB images, eliminating the need for costly depth sensors. In this study, we assess DAM’s ability to monitor poultry behavior, specifically detecting drinking patterns. We also evaluate its effectiveness in managing operations, such as tracking floor eggs. Additionally, we evaluate DAM’s accuracy in detecting disparity within cage-free facilities. The accuracy of the model in estimating physical depth was assessed using root mean square error (RMSE) between predicted and actual perch frame depths, yielding an RMSE of 0.11 m, demonstrating high precision. DAM demonstrated 92.3% accuracy in detecting drinking behavior and achieved an 11% reduction in motion time during egg collection by optimizing the robot’s route using cluster-based planning. These findings highlight DAM’s potential as a valuable tool in poultry science, reducing costs while improving the precision of behavioral analysis and farm management tasks. Full article
(This article belongs to the Special Issue Application of Intelligent Systems in Poultry Farming)
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