Livestock Management Using IoT-Enabled Smart Intelligent
DOI:
https://doi.org/10.65150/EP-gjetr/V2E2/2026-04Keywords:
Sensor network, IoT, Livestock management, Smart & Intelligent Information, Asset registry, Private cloud and Parametric performance evaluation.Abstract
With the advent of Internet of Things (IoT), RFID and communication mechanisms, livestock management has become smart and intelligent. As a result, livestock and their end-products are being systematically monitored from their birth to their final destination on the dining table. This paper describes the use of IoTs and sensor network towards addressing various issues in livestock management. The architecture of an IoT-enabled intelligent livestock management (iSILM) is described and its performance evaluated through parametric modeling technique. The iSILM system runs over a private cloud so that all information can be gathered, processed and what-if questions answered using a variety of historical and current data along with an embedded intelligent decision support system. The performance indices indicate that the iSILM system is viable and will value-add to intelligent livestock management programs.
References
1) T.M. Banhazi, et.al, “Precision Livestock Farming: An international review of scientific and commercial aspects”, International Journal of Agricultural and Biological Engineering 5(3):1-9, Jan. 2012.
2) W. Iwasaki, N. Morita, M. Portia and B. Nagata, “IoT sensors for smart livestock management”, Chemical, Gas, and Biosensors for Internet of Things and Related Applications 2019, Pages 207-221
3) P. Gokhale, O. Bhat and S. Bhat, “Introduction to IoT”, Int.l Advanced Research Journal in Science, Engineering and Technology. Vol. 5, Issue 1, January 2018.
4) E.J. Mendis et al., “Abstraction of Heterogeneous IoT Devices for Management of Smart Homes”, 2019 IEEE Latin-American Conference on Communications (LATINCOM), 2019.
5) M. Gupta, M. Abdelsalam, S. Khorsandroo and S. Mittal, “Security and Privacy in Smart Farming: Challenges and Opportunities”, February 2020, IEEE Access PP(99):1-1
6) Modern Techniques for Agricultural Disease Management and Crop Yield Prediction, edited by N. Pradeep, S. Kautish, C.R. Nirmala, V. Goyal, and S. Abdellatif, IGI Global Publ., 2020.
7) A. Villa-HenriksenG, T.C. Edwards, L.A. Pesonen, O. Green and CAG. Sørensen, “Internet of Things in arable farming: Implementation, applications, challenges and potential“, Biosystems Engineering Vol. 191, March 2020, Pages 60-84.
8) V. Lakshmi Narasimhan, “Precision Agricultural Management Information Systems (PAMIS)”, Submitted to ICIOTCT 2020, Patna, India.
9) OSA-EAI Common Conceptual Object Model (CCOM) V3.0 http://www.mimosa.org
10) “Cloud Computing Fundamentals”, https://pdfs.semanticscholar.org/a1d7/b1ac5d8a33e8f6cbd34c69fffcaa238a69fc.pdf (1st June 2020).
11) A. Johnston, “OpenO&M™ and ISO 15926 Collaborative Deployment”, POSC Caesar Members Meeting Oct 20, 2009 Kuala Lumpur, Malaysia.
12) Mimosa Open Standard | Operations & Maintenance Interoperability,
https://www.streetdirectory.com/travel_guide/137713/computers/mimosa_open_standard__oper ations__maintenance_interoperability.html, (29th May 2020).
13) A.D. Mathew, L. Zhang, S. Zhang and L. Ma, “A review of the MIMOSA OSA-EAI database for condition monitoring systems”, Proceedings World Congress on Engineering Asset Management, Gold Coast, Australia, 2006.
14) K. Kaur, M. Selway, G. Grossmann, M. Stumptner, A. Johnston and P. Wong, “Towards an Open Standards-based Architecture for Condition-based Predictive Maintenance and IIoT”, http://www.semantic-web-journal.net/system/files/swj2083.pdf (30th May 2020).
15) University of Alabama, Sensor Application Network Toolkit: https://www.ohloh.net/tags/ogc/swe, 2nd June 2020.
16) OWS-4 Sensor Web Demonstration: http://www.opengeospatial.org/pub/www/ows4/index.html, 2nd June 2020.
17) Common CBRN Sensor Interface (CCSI): http://www.jpeocbd.osd.mil/packs/Default.aspx?pg=860, 2nd June 2020.
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Copyright (c) 2026 V. Lakshmi Narasimhan (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
