Artificial intelligence applied to precision livestock farming: A tertiary study

Recent advances in Artificial Intelligence (AI) are transforming the livestock sector by enabling continuous real-time data monitoring and automated decision support systems. While several secondary studies have explored the application of AI in Precision Livestock Farming (PLF), they often focus on...

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Main Authors: Damiano Distante, Chiara Albanello, Hira Zaffar, Stefano Faralli, Domenico Amalfitano
Format: Article
Language:English
Published: Elsevier 2025-08-01
Series:Smart Agricultural Technology
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Online Access:http://www.sciencedirect.com/science/article/pii/S2772375525001224
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author Damiano Distante
Chiara Albanello
Hira Zaffar
Stefano Faralli
Domenico Amalfitano
author_facet Damiano Distante
Chiara Albanello
Hira Zaffar
Stefano Faralli
Domenico Amalfitano
author_sort Damiano Distante
collection DOAJ
description Recent advances in Artificial Intelligence (AI) are transforming the livestock sector by enabling continuous real-time data monitoring and automated decision support systems. While several secondary studies have explored the application of AI in Precision Livestock Farming (PLF), they often focus on specific AI techniques or particular PLF activities, limiting a broader understanding of the field. This study aims to provide a comprehensive overview of the state-of-the-art of AI applications in PLF, highlighting both achievements and areas that require further investigation. To this end, a tertiary systematic mapping study was conducted following recognized guidelines to ensure reliability and replicability. The research process involved formulating 10 research questions, designing a comprehensive search strategy, and performing a rigorous quality assessment of the identified studies. From an initial pool of 738 retrieved manuscripts, 14 high-quality secondary studies were selected and analyzed. The findings reveal a wide range of AI techniques applied in PLF, particularly in the learning and perception AI domains. These techniques have proven effective in tasks such as animal recognition, abnormality detection, and health and welfare monitoring. However, comparatively less attention has been given to environmental monitoring and sustainability, highlighting an area that warrants further exploration. By offering valuable insights for future research and practical applications, this study suggests directions for both researchers and livestock farmers to unlock AI's full potential in PLF.
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spelling doaj-art-1fa2ea2aab8a4d65b820b097ae818bf12025-08-20T02:06:44ZengElsevierSmart Agricultural Technology2772-37552025-08-011110088910.1016/j.atech.2025.100889Artificial intelligence applied to precision livestock farming: A tertiary studyDamiano Distante0Chiara Albanello1Hira Zaffar2Stefano Faralli3Domenico Amalfitano4Department of Law and Economics, University of Rome UnitelmaSapienza, Piazza Sassari, 4, Rome, 00161, Italy; Corresponding author.Istituto Zooprofilattico Sperimentale dell'Abruzzo e del Molise “G. Caporale”, Via Campo Boario, 1, Teramo, 64100, Italy; Department of Law and Economics, University of Rome UnitelmaSapienza, Piazza Sassari, 4, Rome, 00161, ItalyDepartment of Law and Economics, University of Rome UnitelmaSapienza, Piazza Sassari, 4, Rome, 00161, Italy; University School for Advanced Studies IUSS Pavia, Piazza della Vittoria, 15, Pavia, 27100, ItalyDepartment of Computer Science, Sapienza University of Rome, Via Salaria, 113, Rome, 00198, ItalyDepartment of Electrical Engineering and Information Technology, University of Naples “Federico II”, Via Claudio, 21, Naples, 80125, ItalyRecent advances in Artificial Intelligence (AI) are transforming the livestock sector by enabling continuous real-time data monitoring and automated decision support systems. While several secondary studies have explored the application of AI in Precision Livestock Farming (PLF), they often focus on specific AI techniques or particular PLF activities, limiting a broader understanding of the field. This study aims to provide a comprehensive overview of the state-of-the-art of AI applications in PLF, highlighting both achievements and areas that require further investigation. To this end, a tertiary systematic mapping study was conducted following recognized guidelines to ensure reliability and replicability. The research process involved formulating 10 research questions, designing a comprehensive search strategy, and performing a rigorous quality assessment of the identified studies. From an initial pool of 738 retrieved manuscripts, 14 high-quality secondary studies were selected and analyzed. The findings reveal a wide range of AI techniques applied in PLF, particularly in the learning and perception AI domains. These techniques have proven effective in tasks such as animal recognition, abnormality detection, and health and welfare monitoring. However, comparatively less attention has been given to environmental monitoring and sustainability, highlighting an area that warrants further exploration. By offering valuable insights for future research and practical applications, this study suggests directions for both researchers and livestock farmers to unlock AI's full potential in PLF.http://www.sciencedirect.com/science/article/pii/S2772375525001224Artificial intelligencePrecision livestock farmingTertiary studySystematic mapping
spellingShingle Damiano Distante
Chiara Albanello
Hira Zaffar
Stefano Faralli
Domenico Amalfitano
Artificial intelligence applied to precision livestock farming: A tertiary study
Smart Agricultural Technology
Artificial intelligence
Precision livestock farming
Tertiary study
Systematic mapping
title Artificial intelligence applied to precision livestock farming: A tertiary study
title_full Artificial intelligence applied to precision livestock farming: A tertiary study
title_fullStr Artificial intelligence applied to precision livestock farming: A tertiary study
title_full_unstemmed Artificial intelligence applied to precision livestock farming: A tertiary study
title_short Artificial intelligence applied to precision livestock farming: A tertiary study
title_sort artificial intelligence applied to precision livestock farming a tertiary study
topic Artificial intelligence
Precision livestock farming
Tertiary study
Systematic mapping
url http://www.sciencedirect.com/science/article/pii/S2772375525001224
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AT stefanofaralli artificialintelligenceappliedtoprecisionlivestockfarmingatertiarystudy
AT domenicoamalfitano artificialintelligenceappliedtoprecisionlivestockfarmingatertiarystudy