IDEAS home Printed from https://ideas.repec.org/a/sae/intdis/v15y2019i11p1550147719888167.html
   My bibliography  Save this article

SAS4P: Providing automatic smoking detection for a persuasive smoking cessation application

Author

Listed:
  • Pedro O Rossel
  • Lorenzo Paredes
  • Antonio Bascur
  • Claudia Martínez-Carrasco
  • Valeria Herskovic

Abstract

Smoking is the biggest avoidable health risk, causing millions of deaths per year worldwide. Persuasive applications are those designed to change a person’s behavior, usually in a specific way. Several mobile phone applications and messaging systems have been used to promote smoking cessation. However, most interventions use participants’ self-reports to track cigarette consumption and avoidance, which may not be accurate or objective. Previous proposals have used sensors to track hand movements and other contextual data to detect smoking or have used devices to detect smoke or breath carbon monoxide. This article proposes a low-cost wearable device that may be worn in a front shirt pocket or clipped to clothing to detect smoke and secondhand smoke. Furthermore, the device is integrated into a persuasive application to promote smoking cessation. The device was evaluated through an experiment to detect whether it may detect direct, passive, and no smoking conditions. The results are promising and may help improve tracking of cigarettes in persuasive applications.

Suggested Citation

  • Pedro O Rossel & Lorenzo Paredes & Antonio Bascur & Claudia Martínez-Carrasco & Valeria Herskovic, 2019. "SAS4P: Providing automatic smoking detection for a persuasive smoking cessation application," International Journal of Distributed Sensor Networks, , vol. 15(11), pages 15501477198, November.
  • Handle: RePEc:sae:intdis:v:15:y:2019:i:11:p:1550147719888167
    DOI: 10.1177/1550147719888167
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/1550147719888167
    Download Restriction: no

    File URL: https://libkey.io/10.1177/1550147719888167?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
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Oresti Banos & Joseph Rafferty & Luis A Castro, 2021. "Internet of things for health and well-being applications," International Journal of Distributed Sensor Networks, , vol. 17(3), pages 15501477219, March.

    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:sae:intdis:v:15:y:2019:i:11:p:1550147719888167. 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: SAGE Publications (email available below). General contact details of provider: .

    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.