IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2022i1p243-d1013200.html
   My bibliography  Save this article

A Case Study of Human Milk Banking with Focus on the Role of IoT Sensor Technology

Author

Listed:
  • Usha Ramanathan

    (Nottingham Business School, Nottingham Trent University, Nottingham NG1 4FQ, UK)

  • Katarzyna Pelc

    (Bedfordshire Business School, University of Bedfordshire, Luton LU2 8LE, UK)

  • Tamíris Pacheco da Costa

    (School of Biosystems and Food Engineering, University College Dublin, Agriculture Building, UCD Belfield, D04 V1W8 Dublin, Ireland)

  • Ramakrishnan Ramanathan

    (Essex Business School, University of Essex, Southend-on-Sea, Essex SS1 1LW, UK)

  • Natalie Shenker

    (Department of Surgery and Cancer, Imperial College London, Du Cane Road, London W12 0HS, UK
    Human Milk Foundation, Rothamsted Institute, Harpenden AL5 2JQ, UK)

Abstract

Human milk is the biological norm for newborn nutrition, with breast milk from the mother being recognized as the best source of nutrition for infant health. When the mother’s milk is unavailable, donor human milk is the best alternative for infants with low birthweights. Growing recognition of the benefits of donor human milk has led to increasing global interest in monitoring and controlling human milk’s quality to fulfil the need for donor human milk. In response to this need, the REAMIT project proposed to adapt and apply existing innovative technology to continuously monitor and record human milk quality and signal potential milk quality issues. IoT sensors and big data technology have been used to monitor conditions that may increase spoilage (such as temperature and humidity) in the transportation stage. The sensors were installed in the insulated bags used to transport the milk from the donor’s home or hospital to the human milk bank and vice versa. The temperature and humidity were collected every 30 min, whilst the GPS locator sent data every 2 min. The data are collected in the cloud using GPRS/CAT-M1 technology. An algorithm was designed to send alerts when the milk temperature is above the prespecified threshold specified by the organisation, i.e., above −20 °C. The experience showed evidence that IoT sensors can efficiently be used to monitor and maintain quality in supply chains of high-quality human milk. This rare product needs a high level of quality control, which is possible with the support of smart technologies. The IoT technology used can help the human milk supply chain in five different aspects, namely by reducing waste, assuring quality, improving availability, reducing cost and improving sustainability. This system could be extended to various supply chains of rare and precious commodities, including further medical supplies such as human blood and organs, to completely avoid waste and ensure total quality in supply chains.

Suggested Citation

  • Usha Ramanathan & Katarzyna Pelc & Tamíris Pacheco da Costa & Ramakrishnan Ramanathan & Natalie Shenker, 2022. "A Case Study of Human Milk Banking with Focus on the Role of IoT Sensor Technology," Sustainability, MDPI, vol. 15(1), pages 1-17, December.
  • Handle: RePEc:gam:jsusta:v:15:y:2022:i:1:p:243-:d:1013200
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/1/243/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/15/1/243/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sobhi Mejjaouli, 2022. "Internet of Things based Decision Support System for Green Logistics," Sustainability, MDPI, vol. 14(22), pages 1-23, November.
    Full references (including those not matched with items on IDEAS)

    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. Ângela F. Brochado & Eugénio M. Rocha & Diogo Costa, 2024. "A Modular IoT-Based Architecture for Logistics Service Performance Assessment and Real-Time Scheduling towards a Synchromodal Transport System," Sustainability, MDPI, vol. 16(2), pages 1-22, January.

    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:15:y:2022:i:1:p:243-:d:1013200. 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.