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Research on Innovative Business Plan. Smart Cattle Farming Using Artificial Intelligent Robotic Process Automation

Author

Listed:
  • Diana Elena Micle

    (Department of Economic Sciences, University of Agricultural Sciences and Veterinary Medicine of Cluj-Napoca, 3–5 Manastur Street, 400372 Cluj-Napoca, Romania)

  • Florina Deiac

    (Department of Economic Sciences, University of Agricultural Sciences and Veterinary Medicine of Cluj-Napoca, 3–5 Manastur Street, 400372 Cluj-Napoca, Romania)

  • Alexandru Olar

    (Department of Economic Sciences, University of Agricultural Sciences and Veterinary Medicine of Cluj-Napoca, 3–5 Manastur Street, 400372 Cluj-Napoca, Romania)

  • Raul Florentin Drența

    (Faculty of Engineering, North University Center of Baia Mare, Technical University of Cluj-Napoca, 400114 Cluj-Napoca, Romania)

  • Cristian Florean

    (Centric IT, 407042 Sannicoară, Romania)

  • Ionuț Grigore Coman

    (Department of Industrial Engineering, Faculty of Machine Building, Technical University of Cluj-Napoca, 400114 Cluj-Napoca, Romania)

  • Felix Horațiu Arion

    (Department of Economic Sciences, University of Agricultural Sciences and Veterinary Medicine of Cluj-Napoca, 3–5 Manastur Street, 400372 Cluj-Napoca, Romania
    Asociatia Clusterul Agro-Food-Ind Napoca (AgroTransilvania Cluster), 407039 Dezmir, Romania)

Abstract

Integrating livestock management with the required devices and sensors is now seen as a critical factor in the agricultural sector’s long-term success. The findings revealed that the agricultural business sector is open to implementing Information and Communication Technology (ICT) solutions, so the aim of this paper is to determine how advantageous it is for Romanian farmers to invest in a project that employs smart cattle farming methods that incorporate Artificial Intelligence (AI), Robotic Process Automation (RPA) and the Internet of Things (IOT). An unstructured interview was used to gather empirical evidence during a focus group meeting. Analyzing the selected primary performance metrics, it was projected that the farm’s profitability would increase by 19 percent, productivity would increase by 21 percent, and the farm’s environmental impact would decrease by 22 percent. Automation and remote work would help minimize the farm’s worker burden while also making control panels, decision-making files, and data analysis more available. In order for the domain to be as prosperous as possible, farmers must be made aware of the benefits of using these emerging technologies for closing the gap between farmers and Information Technology (IT) solution providers, and this can be accomplished through continuous training for both farmers and their technology vendors.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jagris:v:11:y:2021:i:5:p:430-:d:551416
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    References listed on IDEAS

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    1. Walenty Poczta & Joanna Średzińska & Maciej Chenczke, 2020. "Economic Situation of Dairy Farms in Identified Clusters of European Union Countries," Agriculture, MDPI, vol. 10(4), pages 1-22, March.
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    3. Gregory Scott & Ian Chaston, 2013. "Open innovation in an emerging economy," Management Research Review, Emerald Group Publishing Limited, vol. 36(10), pages 1024-1036, September.
    4. Nehring, Richard & Sauer, Johannes & Gillespie, Jeffrey & Hallahan, Charlie, 2016. "United States and European Union Dairy Farms: Where Is the Competitive Edge?," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 19(B), pages 1-22, August.
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    Cited by:

    1. 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.

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