IDEAS home Printed from https://ideas.repec.org/a/igg/jwltt0/v17y2021i3p1-14.html
   My bibliography  Save this article

Integrated Smart Home Model: An IoT Learning-Inspired Platform

Author

Listed:
  • Nurshahrily Idura Ramli

    (Universiti Teknologi MARA, Malaysia)

  • Mohd Izani Mohamed Rawi

    (Universiti Teknologi MARA, Malaysia)

  • Fatin Nur Nabila Rebuan

    (Universiti Teknologi MARA, Malaysia)

Abstract

Today, in the realm of Industry 4.0, vastly diverse Internet of Things (IoT) technology are integrated everywhere, not to mention included in academic programs in schools and universities. Domain ratio of the final year projects in Universiti Teknologi Mara exposes a staggering hype in IoT as compared to other domains despite not having IoT included in any of the courses. Meanwhile, to fulfill the needs of the student in exploring this technology, an integrated IoT learning platform is developed. It integrates an IoT smart home model and a web-based interface as a learning platform to inspire hands-on learning for the students. The raspberry pi, motion sensor, analog gas sensor, atmospheric sensor, ultrasonic proximity sensor, and rain detector sensor are integrated together in a Lego-built smart home model where its connectivity and readings are displayed in a simple web interface to enable and inspire learning. A manual to set up the entire model is also prepared as a guide for students to set up and further explore the functionalities and operabilities of “things”.

Suggested Citation

  • Nurshahrily Idura Ramli & Mohd Izani Mohamed Rawi & Fatin Nur Nabila Rebuan, 2021. "Integrated Smart Home Model: An IoT Learning-Inspired Platform," International Journal of Web-Based Learning and Teaching Technologies (IJWLTT), IGI Global, vol. 17(3), pages 1-14, September.
  • Handle: RePEc:igg:jwltt0:v:17:y:2021:i:3:p:1-14
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJWLTT.20220501.oa1
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    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:igg:jwltt0:v:17:y:2021:i:3:p:1-14. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.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.