Relevant bibliographies by topics / Precision Livestock Farming (PLF)

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Precision Livestock Farming (PLF)'

Author: Grafiati
Published: 5 June 2025
Last updated: 2 August 2025

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Journal articles on the topic "Precision Livestock Farming (PLF)"

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Berckmans, Daniel. "Precision livestock farming (PLF)." Computers and Electronics in Agriculture 62, no. 1 (2008): 1. http://dx.doi.org/10.1016/j.compag.2007.09.002.

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István Komlósi. "The precision livestock farming." Acta Agraria Debreceniensis, no. 49 (November 13, 2012): 201–2. http://dx.doi.org/10.34101/actaagrar/49/2525.

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The application of information technology is the response of the livestock farming to the demand of customer, legal and economical expectations. This technology is the socalled precision livestock farming (PLF). The elements of the PLF are: continuous monitoring of inputs, animal behaviour by sensors, an algorithm which converts these signals into a figure, this figure is compared to an optimum then adjustment of the input is followed, if it is necesary.
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Dr., Febin Stephan. "Benefits of Precision Livestock Farming." Science World a monthly e magazine 3, no. 1 (2023): 52–53. https://doi.org/10.5281/zenodo.7549599.

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Precision livestock farming (PLF) is a method of rearing livestock that uses contemporary technologies to collect data on each animal on a farm and use that data to optimize management techniques by lowering input costs or enhancing overall farm -productivity. While being aware of and responsible for its environmental effects, PLF enables farmers to improve production, expand their farms, enhance productivity and satisfy the rising demand for animal products. The PLF focuses on the use of information and communication technology (ICT) to boost livestock production efficiency while also pr
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Naresh, M1* Hariharan R² Banoth Sai Nehru³ Gongale Tushar Surendra⁴ Shashikiran S. Doddannavar⁵. "An Overview of Precision Livestock Farming: Innovations in Livestock Farming." Veterinary Today 3, no. 2 (2025): 536–38. https://doi.org/10.5281/zenodo.15025292.

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Precision Livestock Farming (PLF) is an innovative approach that enables real-time monitoring of livestock by equipping animals with sensors to collect and transmit data on their health and behavior. This data helps farmers make informed decisions regarding animal welfare and productivity. The strategic goal of PLF is to promote sustainability in livestock farming, improving efficiency, reducing environmental impact and ensuring both animal and human health. PLF provides a solution for the growing challenges of a decreasing number of farmers and increasing herd sizes by maintaining health moni
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Jiang, Bing, Wenjie Tang, Lihang Cui, and Xiaoshang Deng. "Precision Livestock Farming Research: A Global Scientometric Review." Animals 13, no. 13 (2023): 2096. http://dx.doi.org/10.3390/ani13132096.

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Precision livestock farming (PLF) utilises information technology to continuously monitor and manage livestock in real-time, which can improve individual animal health, welfare, productivity and the environmental impact of animal husbandry, contributing to the economic, social and environmental sustainability of livestock farming. PLF has emerged as a pivotal area of multidisciplinary interest. In order to clarify the knowledge evolution and hotspot replacement of PLF research, based on the relevant data from the Web of Science database from 1973 to 2023, this study analyzed the main character
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Elliott, Kevin C., and Ian Werkheiser. "A Framework for Transparency in Precision Livestock Farming." Animals 13, no. 21 (2023): 3358. http://dx.doi.org/10.3390/ani13213358.

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As precision livestock farming (PLF) technologies emerge, it is important to consider their social and ethical dimensions. Reviews of PLF have highlighted the importance of considering ethical issues related to privacy, security, and welfare. However, little attention has been paid to ethical issues related to transparency regarding these technologies. This paper proposes a framework for developing responsible transparency in the context of PLF. It examines the kinds of information that could be ethically important to disclose about these technologies, the different audiences that might care a
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Liu, Gang, Hao Guo, Alexey Ruchay, and Andrea Pezzuolo. "Recent Advancements in Precision Livestock Farming." Agriculture 13, no. 9 (2023): 1652. http://dx.doi.org/10.3390/agriculture13091652.

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The increasing global demand for sustainably sourced animal-derived food has prompted the development and application of smart technologies to address environmental, economic, and societal concerns, resulting in precision livestock farming (PLF) applications [...]
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Zhao, Yang, Brett C. Ramirez, Janice M. Siegford, et al. "Field Implementation of Precision Livestock Farming: Selected Proceedings from the 2nd U.S. Precision Livestock Farming Conference." Animals 14, no. 7 (2024): 1128. http://dx.doi.org/10.3390/ani14071128.

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Precision Livestock Farming (PLF) involves the real-time monitoring of images, sounds, and other biological, physiological, and environmental parameters to assess and improve animal health and welfare within intensive and extensive production systems [...]
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Khan, Danyal, Haider Zaman, Aimen Sultan, et al. "Exploring the Potential of Precision Livestock Farming Technologies for Enhancing Animal Welfare and Public Health." Scholars Journal of Agriculture and Veterinary Sciences 12, no. 06 (2025): 205–12. https://doi.org/10.36347/sjavs.2025.v12i06.001.

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This review explores the potential of Precision Livestock Farming (PLF) technology to enhance animal welfare and improve public health outcomes in contemporary livestock management. As global food demands increase and the necessity for sustainable agricultural methods escalates, Precision Livestock Farming (PLF) technologies—encompassing sensors, automation systems, and big data analytics—present substantial potential in optimizing animal welfare, mitigating disease outbreaks, and improving production. The main aim of this review is to consolidate the existing literature, pinpoint knowledge de
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Tzanidakis, Christos, Ouranios Tzamaloukas, Panagiotis Simitzis, and Panagiotis Panagakis. "Precision Livestock Farming Applications (PLF) for Grazing Animals." Agriculture 13, no. 2 (2023): 288. http://dx.doi.org/10.3390/agriculture13020288.

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Over the past four decades the dietary needs of the global population have been elevated, with increased consumption of animal products predominately due to the advancing economies of South America and Asia. As a result, livestock production systems have expanded in size, with considerable changes to the animals’ management. As grazing animals are commonly grown in herds, economic and labour constraints limit the ability of the producer to individually assess every animal. Precision Livestock Farming refers to the real-time continuous monitoring and control systems using sensors and computer a
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Dissertations / Theses on the topic "Precision Livestock Farming (PLF)"

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Ferrari, S. "Scientific methodology for sound labelling in relation to precision livestock farming." Doctoral thesis, Università degli Studi di Milano, 2009. http://hdl.handle.net/2434/157889.

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The analysis of animal sounds and vocalizations allows the interpretation of stress, behaviour or disease pattern in a non invasive way, and it might be used to assess welfare, management as well as health status and social adaptation (e.g. hierarchies ). Farm sanitary level especially is crucial for modern livestock farming where high animal density affect health. Monitoring animal health is vital for the sustainable management of a farm but it’s often difficult to apply punctually. The results of a low monitoring are increased disease rate, increased pharmacologic costs and decrease in qua
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Bahlo, Christiane. "Open data and interoperability standards : opportunities for animal welfare in extensive livestock systems." Thesis, Federation University Australia, 2021. http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/177520.

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Extensive livestock farming constitutes a sizeable portion of agriculture, not only in relation to land use, but in contribution to feeding a growing human population. In addition to meat, it contributes other economically valuable commodities such as wool, hides and other products. The livestock industries are adopting technologies under the banner of Precision Livestock Farming (PLF) to help meet higher production and efficiency targets as well as help to manage the multiple challenges impacting the industries, such as climate change, environmental concerns, globalisation of markets, increas
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Johansson, Nicklas. "Effekter av kameraövervakning av boskap hos sex lantbrukare i Sverige." Thesis, Karlstads universitet, Handelshögskolan (from 2013), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-70935.

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Bakgrund: Lantbruket står inför stora framtida utmaningar som t.ex. stora befolkningsökningar och minskade jordbruksarealer. Ett förslag för att lösa en del av problemet och öka effektiviteten inom lantbruket är att implementera och använda olika digitala tjänster och produkter. Ett av koncepten för den digitala tekniken som har lyfts fram av bland annat EU är Smart farming. Konceptet är brett och innefattar många olika tekniska lösningar, varav en av dessa är kameraövervakning av boskapsdjur. Frågeställning: Har de lantbrukare som använder kameraövervakning av boskapsdjur upplevt en förändrin
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Casten, Carlberg Carl Johan, and Elsa Jerhamre. "Artificial Intelligence in Agriculture : Opportunities and Challenges." Thesis, Uppsala universitet, Avdelningen för datorteknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-443576.

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Artificial Intelligence (AI) is increasingly used in different parts of society for providing decision support in various activities. The agricultural sector is anticipated to benefit from an increased usage of AI and smart devices, a concept called smart farming technologies. Since the agricultural sector faces several simultaneous challenges, such as shrinking marginals, complicated pan-European regulations, and demands to mitigate the environmental footprint, there are great expectations that smart farming will benefit both individual farmers and industry stakeholders. However, most previou
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Condotta, Isabella Cardoso Ferreira da Silva. "Automatic assess of growing-finishing pigs\' weight through depth image analysis." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/11/11152/tde-03082017-093143/.

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A method of continuously monitoring weight would aid producers by ensuring all pigs are gaining weight and increasing the precision of marketing pigs thus saving money. Electronically monitoring weight without moving the pigs to the scale would eliminate a stress-generating source. Therefore, the development of methods for monitoring the physical conditions of animals from a distance appears as a necessity for obtaining data with higher quality. In pigs\' production, animals\' weighing is a practice that represents an important role in the control of the factors that affect the performance of
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Anguzza, Umberto. "A method to develop a computer-vision based system for the automaticac dairy cow identification and behaviour detection in free stall barns." Doctoral thesis, Università di Catania, 2013. http://hdl.handle.net/10761/1334.

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In this thesis, a method to develop a computer-vision based system (CVBS) for the automatic dairy cow identification and behaviour detection in free stall barns is proposed. Two different methodologies based on digital image processing were proposed in order to achieve dairy cow identification and behaviour detection, respectively. Suitable algorithms among that used in computer vision science were chosen and adapted to the specific characteristics of the breeding environment under study. The trial was carried out during the years 2011 and 2012 in a dairy cow free-stall barn located in the mu
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Fischer, Amélie. "Etude de la variabilité interindividuelle de l'efficience alimentaire de la vache laitière." Thesis, Rennes, Agrocampus Ouest, 2017. http://www.theses.fr/2017NSARB296/document.

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L’amélioration de l’efficience alimentaire des animaux peut contribuer à un élevage plus durable par la réduction des ressources utilisées et des rejets associés. Les caractères qui déterminent l’efficience alimentaire des vaches laitières restent mal identifiés. Le projet se propose donc d’identifier les facteurs biologiques associés à la variabilité interindividuelle de l’efficience alimentaire des vaches laitières. La variation d’efficience alimentaire a été estimée avec l’ingéré résiduel, classiquement défini comme la variabilité résiduelle de l’énergie nette ingérée corrigée pour l’énergi
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Rico, José Carlos Silva. "Condicionamento ambiental em suínos na fase de crescimento e engorda." Master's thesis, Universidade de Évora, 2019. http://hdl.handle.net/10174/27904.

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No âmbito do Projeto AWARTECH efetuaram-se dois ensaios com o objetivo de perceber como se monitorizam os parâmetros ambientais e analisar a sua importância na produção e bem-estar animal de suínos em fase de crescimento e engorda. Utilizaram-se 14 fêmeas (7 por ensaio), que foram sujeitas a três ambientes térmicos: inverno (INV), termoneutralidade (TNZ) e verão (VER). Nos dois ensaios, as condições ambientais influenciaram significativamente (p<0,001) a ingestão alimentar (IA), tendo esta sido superior no inverno. Este efeito não foi verificado (p≥0,05) sobre o ganho médio diário (GMD), embor
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Rosa, Filho Gilberto [UNESP]. "Produtividade da soja em função de atributos físicos de um latossolo vermelho distroférrico sob plantio direto." Universidade Estadual Paulista (UNESP), 2008. http://hdl.handle.net/11449/98897.

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Made available in DSpace on 2014-06-11T19:29:45Z (GMT). No. of bitstreams: 0 Previous issue date: 2008-06-05Bitstream added on 2014-06-13T20:39:22Z : No. of bitstreams: 1 rosafilho_g_me_ilha.pdf: 2808164 bytes, checksum: fea19015d3a1c7ee15b5d9dd2e55686b (MD5)<br>Atualmente, no cenário nacional, a cultura da soja no sistema plantio direto é amplamente utilizada na integração agricultura-pecuária. No ano agrícola de 2006/07, no município de Selvíria (MS), foi analisada a produtividade da soja, em plantio direto, em função de alguns atributos físicos de um Latossolo Vermelho Distroférrico (Typi
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Sarout, Bruna Nunes Marsiglio. "Behavioural circadian rhythms : a novel approach to monitor sheep in extensive systems and study the differences between beef steers for methane emission, feed efficiency and growth." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2017. http://hdl.handle.net/10183/164375.

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As tecnologias baseadas em sensores estão cada vez mais disponíveis e podem ser usadas para coletar informações detalhadas sobre o comportamento animal. Com esta informação é possível avaliar o ritmo circadiano de variáveis comportamentais e monitorar sua resposta. A identificação de variações na resposta deste ritmo tem o potencial de detectar problemas de saúde e questões de bem-estar animal. O objetivo deste trabalho foi estudar os ritmos circadianos comportamentais como uma nova abordagem para monitorar ovelhas em sistemas extensivos e estudar a emissão de metano, eficiência alimentar e cr
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Books on the topic "Precision Livestock Farming (PLF)"

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Cox, S., ed. Precision Livestock Farming. Wageningen Academic Publishers, 2003. http://dx.doi.org/10.3920/978-90-8686-515-4.

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Cox, S., ed. Precision Livestock Farming '05. Wageningen Academic Publishers, 2005. http://dx.doi.org/10.3920/978-90-8686-548-2.

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Cox, S., ed. Precision livestock farming '07. Wageningen Academic Publishers, 2007. http://dx.doi.org/10.3920/978-90-8686-604-5.

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Lokhorst, C., and P. W. G. Groot Koerkamp, eds. Precision livestock farming '09. Wageningen Academic Publishers, 2009. http://dx.doi.org/10.3920/978-90-8686-663-2.

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Halachmi, Ilan, ed. Precision livestock farming applications. Wageningen Academic Publishers, 2015. http://dx.doi.org/10.3920/978-90-8686-815-5.

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Banhazi, T., V. Halas, and F. Maroto-Molina, eds. Practical Precision Livestock Farming. Wageningen Academic Publishers, 2022. http://dx.doi.org/10.3920/978-90-8686-934-3.

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Cox, S. W. R. (Sidney Walter Reginald), Institutet för jordbruks- och miljöteknik, and Sveriges lantbruksuniversitet, eds. Precision livestock farming '05. Wageningen Academic Publishers, 2005.

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Van Erp-Van der Kooij, E., ed. Precision technology and sensor applications for livestock farming and companion animals. Wageningen Academic Publishers, 2021. http://dx.doi.org/10.3920/978-90-8686-917-6.

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Grandin, Temple, ed. Improving animal welfare: a practical approach. 3rd ed. CABI, 2021. http://dx.doi.org/10.1079/9781789245219.0000.

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Abstract The third edition of this book contains a total of 20 chapters (including 3 new chapters), including the implementation of an effective animal welfare programme; the importance of measurement to improve the welfare of livestock, poultry and fish; the social and ethical importance of agricultural animal welfare; the implementation of effective animal-based measurements for assessing animal welfare on farms and slaughter plants; how to improve livestock handling and reduce stress; painful husbandry procedures in livestock and poultry; the importance of good stockmanship and its benefits
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Banhazi, T., V. Halas, and F. Maroto-Molina. Practical Precision Livestock Farming: Hands-On Experiences with PLF Technologies in Commercial and R&d Settings. Wageningen Academic Publishers, 2022.

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Book chapters on the topic "Precision Livestock Farming (PLF)"

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Mottram, T. T. F. "Chapter 23: How to commercialise PLF technologies." In Practical Precision Livestock Farming. Wageningen Academic Publishers, 2022. http://dx.doi.org/10.3920/978-90-8686-934-3_23.

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Guzhva, O., and J. M. Siegford. "Chapter 21: The unintended (and unconsidered) consequences of PLF: ethical and social considerations of PLF running the farm." In Practical Precision Livestock Farming. Wageningen Academic Publishers, 2022. http://dx.doi.org/10.3920/978-90-8686-934-3_21.

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Halachmi, I., A. Schlageter Tello, A. Peña Fernández, et al. "2.5. Discussion: PLF applications of automatic lameness detection." In Precision livestock farming applications. Wageningen Academic Publishers, 2015. http://dx.doi.org/10.3920/978-90-8686-815-5_2.5.

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Halachmi, I., A. Schlageter Tello, A. Peña Fernández, et al. "3.5. Discussion: how PLF delivers added value to farmers." In Precision livestock farming applications. Wageningen Academic Publishers, 2015. http://dx.doi.org/10.3920/978-90-8686-815-5_3.5.

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Halachmi, I., A. Schlageter Tello, A. Peña Fernández, et al. "7.4. Discussion: PLF in milk quality and milk contents." In Precision livestock farming applications. Wageningen Academic Publishers, 2015. http://dx.doi.org/10.3920/978-90-8686-815-5_7.4.

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Hemeryck, M., and D. Berckmans. "5.4. Pig cough monitoring in the EU-PLF project: first results." In Precision livestock farming applications. Wageningen Academic Publishers, 2015. http://dx.doi.org/10.3920/978-90-8686-815-5_5.4.

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Halachmi, I., A. Schlageter Tello, A. Peña Fernández, et al. "6.4. Discussion: PLF for automatic detection of animal health in cows." In Precision livestock farming applications. Wageningen Academic Publishers, 2015. http://dx.doi.org/10.3920/978-90-8686-815-5_6.4.

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Halachmi, I., A. Schlageter Tello, A. Peña Fernández, et al. "4.6. Discussion: PLF in genetics & health of beef, calves and heifers." In Precision livestock farming applications. Wageningen Academic Publishers, 2015. http://dx.doi.org/10.3920/978-90-8686-815-5_4.6.

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Halachmi, I., A. Schlageter Tello, A. Peña Fernández, et al. "5.7. Discussion: PLF for automatic detection of animal health – poultry and pigs." In Precision livestock farming applications. Wageningen Academic Publishers, 2015. http://dx.doi.org/10.3920/978-90-8686-815-5_5.7.

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Siegford, Janice M., and Kaitlin Wurtz. "Practical considerations for the use of precision livestock farming to improve animal welfare." In Bridging research disciplines to advance animal welfare science: a practical guide. CABI, 2021. http://dx.doi.org/10.1079/9781789247893.0015.

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Conference papers on the topic "Precision Livestock Farming (PLF)"

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Qazi, Ahmed, Taha Razzaq, and Asim Iqbal. "AnimalFormer: Multimodal Vision Framework for Behavior-based Precision Livestock Farming." In 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). IEEE, 2024. http://dx.doi.org/10.1109/cvprw63382.2024.00795.

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Alomair, Reem, Abrar Al-Amoudi, Abdulrahman Javaid, Mustafa Alnaser, and Shiekhah Al binali. "Enhancing Precision Livestock Farming Management with AI-Driven Ear Tag Detection and OCR Recognition." In 2024 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD). IEEE, 2024. https://doi.org/10.1109/ictmod63116.2024.10878196.

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Gabato, Aaron Jay, Joshua Vendivil, Bea Alessandra Sison, Khavee Agustus Botangen, Neal Del Rosario, and Kier Santiago. "Development of an RFID-Based Record Management Web Portal for Goats Towards Precision Livestock Farming." In 2024 IEEE International Conference on Computing (ICOCO). IEEE, 2024. https://doi.org/10.1109/icoco62848.2024.10928232.

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Farhan, Muhammad, Goldwin Sonick Wijaya Thaha, Eduardus Alvito Kristiadi, and Kusprasapta Mutijarsa. "Cattle Anomaly Behavior Detection System Based on IoT and Computer Vision in Precision Livestock Farming." In 2024 International Conference on Information Technology Systems and Innovation (ICITSI). IEEE, 2024. https://doi.org/10.1109/icitsi65188.2024.10929192.

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Grigorev, Georgii V., Mikhail E. Pitertsev, and Egor I. Fomichev. "Multimodal sensor fusion and embedded control for obstacle-aware feed pusher robotics in precision livestock farming." In Fourth International Conference on Digital Technologies, Optics, and Materials Science (DTIEE 2025), edited by Arthur Gibadullin and Khamza Eshankulov. SPIE, 2025. https://doi.org/10.1117/12.3072669.

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"Current trends and perspective of Precision Livestock Farming (PLF) with relation to IoT and data science tools." In Current Trends and Perspectives of IoT/AI Technologies in Livestock Industry. Food and Fertilizer Technology Center for the Asian and Pacific Region, 2019. http://dx.doi.org/10.56669/dtvu2247.

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Dineva, Kristina, and Tatiana Atanasova. "MODELLING AND SIMULATION OF CLOUD-BASED DIGITAL TWINS IN SMART FARMING." In 22nd SGEM International Multidisciplinary Scientific GeoConference 2022. STEF92 Technology, 2022. http://dx.doi.org/10.5593/sgem2022v/6.2/s25.31.

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Digital Twins can be seen as powering the next generation of IoT-connected solutions. Digital Twins model the real world by using historical and real-time data to represent the past and present and simulate the predictable future. Digital twins are related to a set of concepts such as digital representation and 3D visualization, integration, monitoring, control, computation, prediction, and decision-making. They are digital replicas of physical objects having bidirectional data flow. The physical object and its digital twin are synchronized, and the simulations, optimizations and visualization
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Andonovic, Ivan, Craig Michie, Philippe Cousin, Ahmed Janati, Congduc Pham, and Mamour Diop. "Precision Livestock Farming Technologies." In 2018 Global Internet of Things Summit (GIoTS). IEEE, 2018. http://dx.doi.org/10.1109/giots.2018.8534572.

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Gomes, Jonas S., José Maria N. David, Regina Braga, et al. "Architecture for Decision Support in Precision Livestock Farming." In Brazilian e-Science Workshop. Sociedade Brasileira de Computação, 2021. http://dx.doi.org/10.5753/bresci.2021.15787.

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The use of sensors in the agricultural domain generates a massive volume of heterogeneous data that must be treated, stored, and processed for decision-making. These decisions must be taken considering the diversity of devices and contextual information, which is often not considered but is important to the decision-making process. This paper presents an architecture to integrate data from sensors related to precision livestock farms. The integration and processing of these data can support decision-making, lead to more accurate results and enhance agribusiness sustainability.
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Milan, Hugo FM, Kristen M. Perano, and Kifle G. Gebremedhin. "Survey and future prospects in precision dairy farming." In 10th International Livestock Environment Symposium (ILES X). American Society of Agricultural and Biological Engineers, 2018. http://dx.doi.org/10.13031/iles.18-053.

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Reports on the topic "Precision Livestock Farming (PLF)"

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Tubb, Catherine, and Tony Seba. Rethinking Food and Agriculture 2020-2030: The Second Domestication of Plants and Animals, the Disruption of the Cow, and the Collapse of Industrial Livestock Farming. RethinkX, 2019. http://dx.doi.org/10.61322/ijip9096.

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Abstract:
By 2030, the number of cows in the U.S. will have fallen by 50% and the cattle farming industry will be all but bankrupt. All other livestock industries will suffer a similar fate, while the knock-on effects for crop farmers and businesses throughout the value chain will be severe. Rethinking Food and Agriculture shows how the modern food disruption, made possible by rapid advances in precision biology and an entirely new model of production we call Food-as-Software, will have profound implications not just for the industrial agriculture industry, but for the wider economy, society, and the en
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