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iSEA: IoT-based smartphone energy assistant for prompting energy-aware behaviors in commercial buildings

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  • Rafsanjani, Hamed Nabizadeh
  • Ghahramani, Ali
  • Nabizadeh, Amir Hossein

Abstract

Providing personalized energy-use information to individual occupants enables the adoption of energy-aware behaviors in commercial buildings. However, the implementation of individualized feedback still remains challenging due to the difficulties in collecting personalized data, tracking personal behaviors, and delivering personalized tailored information to individual occupants. Nowadays, the Internet of Things (IoT) technologies are used in a variety of applications including real-time monitoring, control, and decision-making due to the flexibility of these technologies for fusing different data streams. In this paper, we propose a novel IoT-based smartphone energy assistant (iSEA) framework which prompts energy-aware behaviors in commercial buildings. iSEA tracks individual occupants through tracking their smartphones, uses a deep learning approach to identify their energy usage, and delivers personalized tailored feedback to impact their usage. iSEA particularly uses an energy-use efficiency index (EEI) to understand behaviors and categorize them into efficient and inefficient behaviors. The iSEA architecture includes four layers: physical, cloud, service, and communication. The results of implementing iSEA in a commercial building with ten occupants over a twelve-week duration demonstrate the validity of this approach in enhancing individualized energy-use behaviors. An average of 34% energy savings was measured by tracking occupants’ EEI by the end of the experimental period. In addition, the results demonstrate that commercial building occupants often ignore controlling over lighting systems at their departure events that leads to wasting energy during non-working hours. By utilizing the existing IoT devices in commercial buildings, iSEA significantly contributes to support research efforts into sensing and enhancing energy-aware behaviors at minimal costs.

Suggested Citation

  • Rafsanjani, Hamed Nabizadeh & Ghahramani, Ali & Nabizadeh, Amir Hossein, 2020. "iSEA: IoT-based smartphone energy assistant for prompting energy-aware behaviors in commercial buildings," Applied Energy, Elsevier, vol. 266(C).
    • Handle: RePEc:eee:appene:v:266:y:2020:i:c:s0306261920304049
    DOI: 10.1016/j.apenergy.2020.114892
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    as
    1. Png, Ethan & Srinivasan, Seshadhri & Bekiroglu, Korkut & Chaoyang, Jiang & Su, Rong & Poolla, Kameshwar, 2019. "An internet of things upgrade for smart and scalable heating, ventilation and air-conditioning control in commercial buildings," Applied Energy, Elsevier, vol. 239(C), pages 408-424.
    2. Ghahramani, Ali & Zhang, Kenan & Dutta, Kanu & Yang, Zheng & Becerik-Gerber, Burcin, 2016. "Energy savings from temperature setpoints and deadband: Quantifying the influence of building and system properties on savings," Applied Energy, Elsevier, vol. 165(C), pages 930-942.
    3. Khosrowpour, Ardalan & Xie, Yimeng & Taylor, John E. & Hong, Yili, 2016. "One size does not fit all: Establishing the need for targeted eco-feedback," Applied Energy, Elsevier, vol. 184(C), pages 523-530.
    4. Wei, Min & Hong, Seung Ho & Alam, Musharraf, 2016. "An IoT-based energy-management platform for industrial facilities," Applied Energy, Elsevier, vol. 164(C), pages 607-619.
    5. Guillaume Deffuant & Frederic Amblard & Gérard Weisbuch, 2002. "How Can Extremism Prevail? a Study Based on the Relative Agreement Interaction Model," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 5(4), pages 1-1.
    6. Hamed Nabizadeh Rafsanjani & Changbum R. Ahn & Mahmoud Alahmad, 2015. "A Review of Approaches for Sensing, Understanding, and Improving Occupancy-Related Energy-Use Behaviors in Commercial Buildings," Energies, MDPI, vol. 8(10), pages 1-34, October.
    7. Adhikari, Rajendra & Pipattanasomporn, M. & Rahman, S., 2018. "An algorithm for optimal management of aggregated HVAC power demand using smart thermostats," Applied Energy, Elsevier, vol. 217(C), pages 166-177.
    8. Faruqui, Ahmad & Sergici, Sanem & Sharif, Ahmed, 2010. "The impact of informational feedback on energy consumption—A survey of the experimental evidence," Energy, Elsevier, vol. 35(4), pages 1598-1608.
    9. Allcott, Hunt, 2011. "Social norms and energy conservation," Journal of Public Economics, Elsevier, vol. 95(9-10), pages 1082-1095, October.
    10. Gulbinas, R. & Jain, R.K. & Taylor, J.E., 2014. "BizWatts: A modular socio-technical energy management system for empowering commercial building occupants to conserve energy," Applied Energy, Elsevier, vol. 136(C), pages 1076-1084.
    11. Webber, Carrie A. & Roberson, Judy A. & McWhinney, Marla C. & Brown, Richard E. & Pinckard, Margaret J. & Busch, John F., 2006. "After-hours power status of office equipment in the USA," Energy, Elsevier, vol. 31(14), pages 2823-2838.
    12. Murtagh, Niamh & Nati, Michele & Headley, William R. & Gatersleben, Birgitta & Gluhak, Alexander & Imran, Muhammad Ali & Uzzell, David, 2013. "Individual energy use and feedback in an office setting: A field trial," Energy Policy, Elsevier, vol. 62(C), pages 717-728.
    13. Allcott, Hunt, 2011. "Social norms and energy conservation," Journal of Public Economics, Elsevier, vol. 95(9), pages 1082-1095.
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    4. Ali Karji & Mostafa Namian & Mohammadsoroush Tafazzoli, 2020. "Identifying the Key Barriers to Promote Sustainable Construction in the United States: A Principal Component Analysis," Sustainability, MDPI, vol. 12(12), pages 1-21, June.
    5. Josimar Reyes-Campos & Giner Alor-Hernández & Isaac Machorro-Cano & José Oscar Olmedo-Aguirre & José Luis Sánchez-Cervantes & Lisbeth Rodríguez-Mazahua, 2021. "Discovery of Resident Behavior Patterns Using Machine Learning Techniques and IoT Paradigm," Mathematics, MDPI, vol. 9(3), pages 1-25, January.
    6. Karam M. Al-Obaidi & Mohataz Hossain & Nayef A. M. Alduais & Husam S. Al-Duais & Hossein Omrany & Amirhosein Ghaffarianhoseini, 2022. "A Review of Using IoT for Energy Efficient Buildings and Cities: A Built Environment Perspective," Energies, MDPI, vol. 15(16), pages 1-32, August.

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