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A Smartphone Application for Personalized and Multi-Method Interventions toward Energy Saving in Buildings

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Listed:
  • Peeraya Inyim

    (OHL—Arellano Construction Co., 7051 SW 12th Street, Miami, FL 33144, USA)

  • Mostafa Batouli

    (Florida International University, College of Engineering and Computing, Florida International University 10555, West Flagler Street, Miami, FL 33174, USA)

  • Maria Presa Reyes

    (Florida International University, College of Engineering and Computing, Florida International University 10555, West Flagler Street, Miami, FL 33174, USA)

  • Triana Carmenate

    (Florida International University, College of Engineering and Computing, Florida International University 10555, West Flagler Street, Miami, FL 33174, USA)

  • Leonardo Bobadilla

    (Florida International University, College of Engineering and Computing, Florida International University 10555, West Flagler Street, Miami, FL 33174, USA)

  • Ali Mostafavi

    (Zachry Department of Civil Engineering, Texas A&M University, 3136 TAMU, College Station, TX 77843, USA)

Abstract

Occupant behavior is a significant contributor to energy waste in buildings. This research introduces an advanced smartphone application, developed based on the theoretical underpinnings of situational awareness theory, to effectively implement multi-method and personalized intervention to encourage energy conservation behaviors of building occupants. The new smart application provides several innovative features, such as energy saving points, customized feedback, and visualized user interface, which are implemented in the application to support multi-method interventions. The application was created using the Java language for Android devices. With the use of the Android platform, the app takes advantage of hardware technology from the user’s mobile device. Measurement of occupancy behavior is accomplished by making use of the device’s positional sensors. Orientation and geomagnetic field sensors serve to provide an accurate location of an occupant inside the building. The application can determine energy waste in a zone by using occupancy behavior. Moreover, the application offers real-time and projected future energy consumption based on occupants’ behaviors. This novel feature can significantly improve communication that can lead to prompt action for building energy reduction. Results show how the app can compile raw data on energy behavior and make it easy to understand for the user through the use of visuals and statistical algorithms.

Suggested Citation

  • Peeraya Inyim & Mostafa Batouli & Maria Presa Reyes & Triana Carmenate & Leonardo Bobadilla & Ali Mostafavi, 2018. "A Smartphone Application for Personalized and Multi-Method Interventions toward Energy Saving in Buildings," Sustainability, MDPI, vol. 10(6), pages 1-19, May.
  • Handle: RePEc:gam:jsusta:v:10:y:2018:i:6:p:1744-:d:149093
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    References listed on IDEAS

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    1. Li, Baizhan & Yao, Runming, 2009. "Urbanisation and its impact on building energy consumption and efficiency in China," Renewable Energy, Elsevier, vol. 34(9), pages 1994-1998.
    2. Midden, Cees J. H. & Meter, Joanne F. & Weenig, Mieneke H. & Zieverink, Henk J. A., 1983. "Using feedback, reinforcement and information to reduce energy consumption in households: A field-experiment," Journal of Economic Psychology, Elsevier, vol. 3(1), pages 65-86.
    3. Ueno, Tsuyoshi & Sano, Fuminori & Saeki, Osamu & Tsuji, Kiichiro, 2006. "Effectiveness of an energy-consumption information system on energy savings in residential houses based on monitored data," Applied Energy, Elsevier, vol. 83(2), pages 166-183, February.
    4. Yun, Geun Young & Steemers, Koen, 2011. "Behavioural, physical and socio-economic factors in household cooling energy consumption," Applied Energy, Elsevier, vol. 88(6), pages 2191-2200, June.
    5. van Houwelingen, Jeannet H & van Raaij, W Fred, 1989. "The Effect of Goal-Setting and Daily Electronic Feedback on In-home Energy Use," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 16(1), pages 98-105, June.
    6. Dounis, A.I. & Caraiscos, C., 2009. "Advanced control systems engineering for energy and comfort management in a building environment--A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(6-7), pages 1246-1261, August.
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    Cited by:

    1. Amanda Ahl & Gina Accawi & Bryce Hudey & Melissa Lapsa & Teresa Nichols, 2019. "Occupant Behavior for Energy Conservation in Commercial Buildings: Lessons Learned from Competition at the Oak Ridge National Laboratory," Sustainability, MDPI, vol. 11(12), pages 1-18, June.
    2. Akrivi Krouska & Katerina Kabassi & Christos Troussas & Cleo Sgouropoulou, 2022. "Personalizing Environmental Awareness through Smartphones Using AHP and PROMETHEE II," Future Internet, MDPI, vol. 14(2), pages 1-16, February.
    3. Hawks, M.A. & Cho, S., 2024. "Review and analysis of current solutions and trends for zero energy building (ZEB) thermal systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).

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