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Development and Performance Evaluation of an IoT-Integrated Breath Analyzer

Author

Listed:
  • Abd Alghani Khamis

    (Department of Mechanical Engineering, Faculty of Engineering, Universiti Malaya, Kuala Lumpur 50603, Malaysia)

  • Aida Idris

    (Department of Management, Faculty of Business and Economics, Universiti Malaya, Kuala Lumpur 50603, Malaysia)

  • Abdallah Abdellatif

    (Department of Electrical Engineering, Faculty of Engineering, Universiti Malaya, Kuala Lumpur 50603, Malaysia)

  • Noor Ashikin Mohd Rom

    (Faculty of Management, Multimedia University, Cyberjaya 63100, Malaysia)

  • Taha Khamis

    (Center for Applied Biomechanics (CAB), Department of Biomedical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia)

  • Mohd Sayuti Ab Karim

    (Centre of Advanced Manufacturing and Material Processing (AMMP), Department of Mechanical Engineering, Faculty of Engineering, Universiti Malaya, Kuala Lumpur 50603, Malaysia)

  • Shamini Janasekaran

    (Centre for Advanced Materials and Intelligent Manufacturing, Faculty of Engineering, Built Environment & IT, SEGi University Sdn Bhd, Petaling Jaya 47810, Malaysia)

  • Rusdi Bin Abd Rashid

    (Department of Psychological Medicine, Faculty of Medicine, Universiti Malaya, Kuala Lumpur 50603, Malaysia)

Abstract

Although alcohol consumption may produce effects that can be beneficial or harmful, alcohol consumption prevails among communities around the globe. Additionally, alcohol consumption patterns may be associated with several factors among communities and individuals. Numerous technologies and methods are implemented to enhance the detection and tracking of alcohol consumption, such as vehicle-integrated and wearable devices. In this paper, we present a cellular-based Internet of Things (IoT) implementation in a breath analyzer to enable data collection from multiple users via a single device. Cellular technology using hypertext transfer protocol (HTTP) was implemented as an IoT gateway. IoT integration enabled the direct retrieval of information from a database relative to the device and direct upload of data from the device onto the database. A manually developed threshold algorithm was implemented to quantify alcohol concentrations within a range from 0 to 200 mcg/100 mL breath alcohol content using electrochemical reactions in a fuel-cell sensor. Two data collections were performed: one was used for the development of the model and was split into two sets for model development and on-machine validation, and another was used as an experimental verification test. An overall accuracy of 98.16% was achieved, and relative standard deviations within the range from 1.41% to 2.69% were achieved, indicating the reliable repeatability of the results. The implication of this paper is that the developed device (an IoT-integrated breath analyzer) may provide practical assistance for healthcare representatives and researchers when conducting studies involving the detection and data collection of alcohol consumption patterns.

Suggested Citation

  • Abd Alghani Khamis & Aida Idris & Abdallah Abdellatif & Noor Ashikin Mohd Rom & Taha Khamis & Mohd Sayuti Ab Karim & Shamini Janasekaran & Rusdi Bin Abd Rashid, 2023. "Development and Performance Evaluation of an IoT-Integrated Breath Analyzer," IJERPH, MDPI, vol. 20(2), pages 1-26, January.
    • Handle: RePEc:gam:jijerp:v:20:y:2023:i:2:p:1319-:d:1031944
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    References listed on IDEAS

    as
    1. Abd Alghani Khamis & Siti Zuliana Salleh & Mohd Sayuti Ab Karim & Noor Ashikin Mohd Rom & Shamini Janasekaran & Aida Idris & Rusdi Bin Abd Rashid, 2022. "Alcohol Consumption Patterns: A Systematic Review of Demographic and Sociocultural Influencing Factors," IJERPH, MDPI, vol. 19(13), pages 1-17, July.
    2. Jie Dong & Qiran Zhao & Yanjun Ren, 2022. "Dark Side or Bright Side: The Impact of Alcohol Drinking on the Trust of Chinese Rural Residents," IJERPH, MDPI, vol. 19(10), pages 1-15, May.
    3. Wei Gao & Sam Emaminejad & Hnin Yin Yin Nyein & Samyuktha Challa & Kevin Chen & Austin Peck & Hossain M. Fahad & Hiroki Ota & Hiroshi Shiraki & Daisuke Kiriya & Der-Hsien Lien & George A. Brooks & Ron, 2016. "Fully integrated wearable sensor arrays for multiplexed in situ perspiration analysis," Nature, Nature, vol. 529(7587), pages 509-514, January.
    4. Alicja Beksinska & Emily Nyariki & Rhoda Kabuti & Mary Kungu & Hellen Babu & Pooja Shah & The Maisha Fiti Study Champions & Chrispo Nyabuto & Monica Okumu & Anne Mahero & Pauline Ngurukiri & Zaina Jam, 2022. "Harmful Alcohol and Drug Use Is Associated with Syndemic Risk Factors among Female Sex Workers in Nairobi, Kenya," IJERPH, MDPI, vol. 19(12), pages 1-19, June.
    5. Peter Anderson & Amy O’Donnell & Daša Kokole & Eva Jané Llopis & Eileen Kaner, 2021. "Is Buying and Drinking Zero and Low Alcohol Beer a Higher Socio-Economic Phenomenon? Analysis of British Survey Data, 2015–2018 and Household Purchase Data 2015–2020," IJERPH, MDPI, vol. 18(19), pages 1-13, September.
    6. Celine Saul & Shannon Lange & Charlotte Probst, 2022. "Employment Status and Alcohol-Attributable Mortality Risk—A Systematic Review and Meta-Analysis," IJERPH, MDPI, vol. 19(12), pages 1-10, June.
    7. Jennifer Boyd & Clare Bambra & Robin C. Purshouse & John Holmes, 2021. "Beyond Behaviour: How Health Inequality Theory Can Enhance Our Understanding of the ‘Alcohol-Harm Paradox’," IJERPH, MDPI, vol. 18(11), pages 1-12, June.
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    Cited by:

    1. Jun Liu & Shuang Lai & Ayesha Akram Rai & Abual Hassan & Ray Tahir Mushtaq, 2023. "Exploring the Potential of Big Data Analytics in Urban Epidemiology Control: A Comprehensive Study Using CiteSpace," IJERPH, MDPI, vol. 20(5), pages 1-24, February.

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