IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i10p6249-d820184.html
   My bibliography  Save this article

Deployment of Wireless Sensor Network and IoT Platform to Implement an Intelligent Animal Monitoring System

Author

Listed:
  • Jehangir Arshad

    (Department of Electrical & Computer Engineering, COMSATS University Islamabad, Lahore Campus, Lahore 54000, Pakistan
    These authors contributed equally to this work.)

  • Ateeq Ur Rehman

    (Department of Electrical Engineering, Government College University, Lahore 54000, Pakistan
    These authors contributed equally to this work.)

  • Mohamed Tahar Ben Othman

    (Department of Computer Science, College of Computer, Qassim University, Buraydah 51452, Saudi Arabia)

  • Muhammad Ahmad

    (Department of Electrical & Computer Engineering, COMSATS University Islamabad, Lahore Campus, Lahore 54000, Pakistan)

  • Hassaan Bin Tariq

    (Department of Electrical & Computer Engineering, COMSATS University Islamabad, Lahore Campus, Lahore 54000, Pakistan)

  • Muhammad Abdullah Khalid

    (Department of Electrical & Computer Engineering, COMSATS University Islamabad, Lahore Campus, Lahore 54000, Pakistan)

  • Muhammad Abdul Rehman Moosa

    (Department of Electrical & Computer Engineering, COMSATS University Islamabad, Lahore Campus, Lahore 54000, Pakistan)

  • Muhammad Shafiq

    (Department of Information and Communication Engineering, Yeungnam University, Gyeongsan 38541, Korea)

  • Habib Hamam

    (Faculty of Engineering, Université de Moncton, Moncton, NB E1A 3E9, Canada
    International Institute of Technology and Management, Libreville BP1989, Gabon
    Spectrum of Knowledge Production & Skills Development, Sfax 3027, Tunisia
    Department of Electrical and Electronic Engineering Science, School of Electrical Engineering, University of Johannesburg, Johannesburg 2006, South Africa)

Abstract

This study aimed to realize Sustainable Development Goals (SDGs), i.e., no poverty, zero hunger, and sustainable cities and communities through the implementation of an intelligent cattle-monitoring system to enhance dairy production. Livestock industries in developing countries lack the technology that can directly impact meat and dairy products, where human resources are a major factor. This study proposed a novel, cost-effective, smart dairy-monitoring system by implementing intelligent wireless sensor nodes, the Internet of Things (IoT), and a Node-Micro controller Unit (Node-MCU). The proposed system comprises three modules, including an intelligent environmental parameter regularization system, a cow collar (equipped with a temperature sensor, a GPS module to locate the animal, and a stethoscope to update the heart rate), and an automatic water-filling unit for drinking water. Furthermore, a novel IoT-based front end has been developed to take data from prescribed modules and maintain a separate database for further analysis. The presented Wireless Sensor Nodes (WSNs) can intelligently determine the case of any instability in environmental parameters. Moreover, the cow collar is designed to obtain precise values of the temperature, heart rate, and accurate location of the animal. Additionally, auto-notification to the concerned party is a valuable addition developed in the cow collar design. It employed a plug-and-play design to provide ease in implementation. Moreover, automation reduces human intervention, hence labor costs are decreased when a farm has hundreds of animals. The proposed system also increases the production of dairy and meat products by improving animal health via the regularization of the environment and automated food and watering. The current study represents a comprehensive comparative analysis of the proposed implementation with the existing systems that validate the novelty of this work. This implementation can be further stretched for other applications, i.e., smart monitoring of zoo animals and poultry.

Suggested Citation

  • Jehangir Arshad & Ateeq Ur Rehman & Mohamed Tahar Ben Othman & Muhammad Ahmad & Hassaan Bin Tariq & Muhammad Abdullah Khalid & Muhammad Abdul Rehman Moosa & Muhammad Shafiq & Habib Hamam, 2022. "Deployment of Wireless Sensor Network and IoT Platform to Implement an Intelligent Animal Monitoring System," Sustainability, MDPI, vol. 14(10), pages 1-22, May.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:10:p:6249-:d:820184
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/10/6249/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/10/6249/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jehangir Arshad & Musharraf Aziz & Asma A. Al-Huqail & Muhammad Hussnain uz Zaman & Muhammad Husnain & Ateeq Ur Rehman & Muhammad Shafiq, 2022. "Implementation of a LoRaWAN Based Smart Agriculture Decision Support System for Optimum Crop Yield," Sustainability, MDPI, vol. 14(2), pages 1-20, January.
    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. Ridha Ouni & Kashif Saleem, 2022. "Framework for Sustainable Wireless Sensor Network Based Environmental Monitoring," Sustainability, MDPI, vol. 14(14), pages 1-26, July.
    2. Qiao Gang & Aman Muhammad & Zahid Ullah Khan & Muhammad Shahbaz Khan & Fawad Ahmed & Jawad Ahmad, 2022. "Machine Learning-Based Prediction of Node Localization Accuracy in IIoT-Based MI-UWSNs and Design of a TD Coil for Omnidirectional Communication," Sustainability, MDPI, vol. 14(15), pages 1-23, August.

    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. Yuan Liu & Xun He & Wanzhang Wang & Chenhui Zhu & Ruibo Jian & Jinfan Chen, 2022. "Agri-Environment Atmospheric Real-Time Monitoring Technology Based on Drone and Light Scattering," Agriculture, MDPI, vol. 12(11), pages 1-20, November.
    2. Honggang Wang & Peidong Pei & Ruoyu Pan & Kai Wu & Yu Zhang & Jinchao Xiao & Jingfeng Yang, 2022. "A Collision Reduction Adaptive Data Rate Algorithm Based on the FSVM for a Low-Cost LoRa Gateway," Mathematics, MDPI, vol. 10(21), pages 1-21, October.
    3. Valentina Constanta Tudor & Toma Adrian Dinu & Marius Vladu & Dragoș Smedescu & Ionela Mituko Vlad & Eduard Alexandru Dumitru & Cristina Maria Sterie & Carmen Luiza Costuleanu, 2022. "Labour Implications on Agricultural Production in Romania," Sustainability, MDPI, vol. 14(14), pages 1-22, July.
    4. Kayson M. Shurtz & Emily Dicataldo & Robert B. Sowby & Gustavious P. Williams, 2022. "Insights into Efficient Irrigation of Urban Landscapes: Analysis Using Remote Sensing, Parcel Data, Water Use, and Tiered Rates," Sustainability, MDPI, vol. 14(3), pages 1-15, January.
    5. Michail-Alexandros Kourtis & Michael Batistatos & Georgios Xylouris & Andreas Oikonomakis & Dimitris Santorinaios & Charilaos Zarakovitis & Ioannis Chochliouros, 2023. "Energy Efficiency in Agriculture through Tokenization of 5G and Edge Applications," Energies, MDPI, vol. 16(13), pages 1-16, July.

    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:10:p:6249-:d:820184. 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.