IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i5p2607-d757069.html
   My bibliography  Save this article

Applications of Smart Technology as a Sustainable Strategy in Modern Swine Farming

Author

Listed:
  • Shad Mahfuz

    (Animal Nutrition and Feed Science Laboratory, Department of Animal Science and Technology, Sunchon National University, Suncheon 57922, Korea
    Department of Animal Nutrition, Sylhet Agricultural University, Sylhet 3100, Bangladesh
    Both authors have contributed equally to the manuscript as co-first authors.)

  • Hong-Seok Mun

    (Animal Nutrition and Feed Science Laboratory, Department of Animal Science and Technology, Sunchon National University, Suncheon 57922, Korea
    Department of Multimedia Engineering, Sunchon National University, Suncheon 57922, Korea
    Both authors have contributed equally to the manuscript as co-first authors.)

  • Muhammad Ammar Dilawar

    (Animal Nutrition and Feed Science Laboratory, Department of Animal Science and Technology, Sunchon National University, Suncheon 57922, Korea
    Interdisciplinary Program in IT-Bio Convergence System (BK21 Plus), Sunchon National University, Suncheon 57922, Korea)

  • Chul-Ju Yang

    (Animal Nutrition and Feed Science Laboratory, Department of Animal Science and Technology, Sunchon National University, Suncheon 57922, Korea
    Interdisciplinary Program in IT-Bio Convergence System (BK21 Plus), Sunchon National University, Suncheon 57922, Korea)

Abstract

The size of the pork market is increasing globally to meet the demand for animal protein, resulting in greater farm size for swine and creating a great challenge to swine farmers and industry owners in monitoring the farm activities and the health and behavior of the herd of swine. In addition, the growth of swine production is resulting in a changing climate pattern along with the environment, animal welfare, and human health issues, such as antimicrobial resistance, zoonosis, etc. The profit of swine farms depends on the optimum growth and good health of swine, while modern farming practices can ensure healthy swine production. To solve these issues, a future strategy should be considered with information and communication technology (ICT)-based smart swine farming, considering auto-identification, remote monitoring, feeding behavior, animal rights/welfare, zoonotic diseases, nutrition and food quality, labor management, farm operations, etc., with a view to improving meat production from the swine industry. Presently, swine farming is not only focused on the development of infrastructure but is also occupied with the application of technological knowledge for designing feeding programs, monitoring health and welfare, and the reproduction of the herd. ICT-based smart technologies, including smart ear tags, smart sensors, the Internet of Things (IoT), deep learning, big data, and robotics systems, can take part directly in the operation of farm activities, and have been proven to be effective tools for collecting, processing, and analyzing data from farms. In this review, which considers the beneficial role of smart technologies in swine farming, we suggest that smart technologies should be applied in the swine industry. Thus, the future swine industry should be automated, considering sustainability and productivity.

Suggested Citation

  • Shad Mahfuz & Hong-Seok Mun & Muhammad Ammar Dilawar & Chul-Ju Yang, 2022. "Applications of Smart Technology as a Sustainable Strategy in Modern Swine Farming," Sustainability, MDPI, vol. 14(5), pages 1-15, February.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:5:p:2607-:d:757069
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/5/2607/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/5/2607/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Diana Elena Micle & Florina Deiac & Alexandru Olar & Raul Florentin Drența & Cristian Florean & Ionuț Grigore Coman & Felix Horațiu Arion, 2021. "Research on Innovative Business Plan. Smart Cattle Farming Using Artificial Intelligent Robotic Process Automation," Agriculture, MDPI, vol. 11(5), pages 1-15, May.
    2. Nesrein M. Hashem & Eman M. Hassanein & Jean-François Hocquette & Antonio Gonzalez-Bulnes & Fayrouz A. Ahmed & Youssef A. Attia & Khalid A. Asiry, 2021. "Agro-Livestock Farming System Sustainability during the COVID-19 Era: A Cross-Sectional Study on the Role of Information and Communication Technologies," Sustainability, MDPI, vol. 13(12), pages 1-24, June.
    3. Kaitlin Wurtz & Irene Camerlink & Richard B D’Eath & Alberto Peña Fernández & Tomas Norton & Juan Steibel & Janice Siegford, 2019. "Recording behaviour of indoor-housed farm animals automatically using machine vision technology: A systematic review," PLOS ONE, Public Library of Science, vol. 14(12), pages 1-35, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chanhui Jeon & Haram Kim & Dongsoo Kim, 2024. "A Deep-Learning-Based System for Pig Posture Classification: Enhancing Sustainable Smart Pigsty Management," Sustainability, MDPI, vol. 16(7), pages 1-16, March.
    2. Sung-Wook Choi & Yong Jae Shin, 2023. "Role of Smart Farm as a Tool for Sustainable Economic Growth of Korean Agriculture: Using Input–Output Analysis," Sustainability, MDPI, vol. 15(4), pages 1-21, February.
    3. Silvana Dalmutt Kruger & Antonio Zanin & Orlando Durán & Paulo Afonso, 2022. "Performance Measurement Model for Sustainability Assessment of the Swine Supply Chain," Sustainability, MDPI, vol. 14(16), pages 1-19, August.
    4. Aurel Mihail Țîțu & Vasile Gusan & Mihai Dragomir & Alina Bianca Pop & Ștefan Țîțu, 2024. "Cost Calculation and Deployment Strategies for Collaborative Robots in Production Lines: An Innovative and Sustainable Perspective in Knowledge-Based Organizations," Sustainability, MDPI, vol. 16(13), pages 1-25, June.
    5. Elizabeth Emperatriz García-Salirrosas & Ángel Acevedo-Duque & Viviana Marin Chaves & Paula Andrea Mejía Henao & Juan Carlos Olaya Molano, 2022. "Purchase Intention and Satisfaction of Online Shop Users in Developing Countries during the COVID-19 Pandemic," Sustainability, MDPI, vol. 14(10), pages 1-14, May.
    6. Md Sharifuzzaman & Hong-Seok Mun & Keiven Mark B. Ampode & Eddiemar B. Lagua & Hae-Rang Park & Young-Hwa Kim & Md Kamrul Hasan & Chul-Ju Yang, 2024. "Smart Pig Farming—A Journey Ahead of Vietnam," Agriculture, MDPI, vol. 14(4), pages 1-29, March.
    7. Ata Jahangir Moshayedi & Amir Sohail Khan & Jiandong Hu & Abdullah Nawaz & Jianxiong Zhu, 2023. "E-Nose-Driven Advancements in Ammonia Gas Detection: A Comprehensive Review from Traditional to Cutting-Edge Systems in Indoor to Outdoor Agriculture," Sustainability, MDPI, vol. 15(15), pages 1-33, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Huo, Dongyang & Malik, Asad Waqar & Ravana, Sri Devi & Rahman, Anis Ur & Ahmedy, Ismail, 2024. "Mapping smart farming: Addressing agricultural challenges in data-driven era," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
    2. Giancarlo Bozzo & Marialaura Corrente & Giovanni Testa & Gaia Casalino & Michela Maria Dimuccio & Elena Circella & Nazario Brescia & Roberta Barrasso & Francesco Emanuele Celentano, 2021. "Animal Welfare, Health and the Fight against Climate Change: One Solution for Global Objectives," Agriculture, MDPI, vol. 11(12), pages 1-18, December.
    3. Richard B D’Eath & Simone Foister & Mhairi Jack & Nicola Bowers & Qiming Zhu & David Barclay & Emma M Baxter, 2021. "Changes in tail posture detected by a 3D machine vision system are associated with injury from damaging behaviours and ill health on commercial pig farms," PLOS ONE, Public Library of Science, vol. 16(10), pages 1-17, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:5:p:2607-:d:757069. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.