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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
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    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
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    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. 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.
    5. 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.
    6. 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.

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