IDEAS home Printed from https://ideas.repec.org/h/ito/pchaps/273421.html
   My bibliography  Save this book chapter

Management Methods of Energy Consumption Parameters Using IoT and Big Data

In: Advances in Green Electronics Technologies in 2023

Author

Listed:
  • Fernando Velez Varela
  • Carlos Daniel Valencia Rincon
  • Daniel Revelo Alvarado

Abstract

The continuous monitoring of electrical consumption helps to understand energy expenditure in functional consumption environments, such as campuses. For this reason, this work details the development of a mechanism that can do so, such as a network of sensors that is available in a telemetry system, which is determined to perform the acquisition and analysis of energy parameters. These actions are based on the concepts of Internet of Things (IoT) and Big Data. The acquired data are sent in a virtual local area network (VLAN), which is connected to a database server located in the campus environment, using the IoT concept, through the IEEE802.11/IEEE802.3 standards, so that later the analysis and monitoring of the electrical network can be carried out. For the construction of this prototype, noninvasive current sensors connected to a three-phase meter and a communication card are used to extract data from the meter and send it to the database. In the results, the possibility of specifying 30 energy parameters is obtained, with a packet loss rate equal to zero. With this network of sensors, whatever is in operation, such as low-voltage electrical power transformers, distribution boards, among others, can become intelligent data collection devices, from which information is extracted in real time by telemetry.

Suggested Citation

  • Fernando Velez Varela & Carlos Daniel Valencia Rincon & Daniel Revelo Alvarado, 2023. "Management Methods of Energy Consumption Parameters Using IoT and Big Data," Chapters, in: Albert Sabban (ed.), Advances in Green Electronics Technologies in 2023, IntechOpen.
  • Handle: RePEc:ito:pchaps:273421
    DOI: 10.5772/intechopen.105522
    as

    Download full text from publisher

    File URL: https://www.intechopen.com/chapters/83262
    Download Restriction: no

    File URL: https://libkey.io/10.5772/intechopen.105522?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Keywords

    power consumption; energy; Internet of Things (IoT); big data; telemetry; sensors; convergence;
    All these keywords.

    JEL classification:

    • Q55 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Technological Innovation

    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:ito:pchaps:273421. 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: Slobodan Momcilovic (email available below). General contact details of provider: http://www.intechopen.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.