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Effects of Positioning of Multi-Sensor Devices on Occupancy and Indoor Environmental Monitoring in Single-Occupant Offices

Author

Listed:
  • Shoaib Azizi

    (Department of Applied Physics and Electronics, Umeå University, 901 87 Umeå, Sweden)

  • Ramtin Rabiee

    (Department of Applied Physics and Electronics, Umeå University, 901 87 Umeå, Sweden)

  • Gireesh Nair

    (Department of Applied Physics and Electronics, Umeå University, 901 87 Umeå, Sweden)

  • Thomas Olofsson

    (Department of Applied Physics and Electronics, Umeå University, 901 87 Umeå, Sweden)

Abstract

The advancements in sensor and communication technologies drive the rapid developments in the applications of occupancy and indoor environmental monitoring in buildings. Currently, the installation standards for sensors are scarce and the recommendations for sensor positionings are very general. However, inadequate sensor positioning might diminish the reliability of sensor data, which could have serious impacts on the intended applications such as the performance of demand-controlled HVAC systems and their energy use. Thus, there is a need to understand how sensor positioning may affect the sensor data, specifically when using multi-sensor devices in which several sensors are being bundled together. This study is based on the data collected from 18 multi-sensor devices installed in three single-occupant offices (six sensors in each office). Each multi-sensor device included sensors to measure passive infrared (PIR) radiation, temperature, CO 2 , humidity, and illuminance. The results show that the positions of PIR and CO 2 sensors significantly affect the reliability of occupancy detection. The typical approach of positioning the sensors on the ceiling, in the middle of offices, may lead to relatively unreliable data. In this case, the PIR sensor in that position has only 60% accuracy of presence detection. Installing the sensors under office desks could increase the accuracy of presence detection to 84%. These two sensor positions are highlighted in sensor fusion analysis as they could reach the highest accuracy compared to other pairs of PIR sensors. Moreover, sensor positioning can affect various indoor environmental parameters, especially temperature and illuminance measurements.

Suggested Citation

  • Shoaib Azizi & Ramtin Rabiee & Gireesh Nair & Thomas Olofsson, 2021. "Effects of Positioning of Multi-Sensor Devices on Occupancy and Indoor Environmental Monitoring in Single-Occupant Offices," Energies, MDPI, vol. 14(19), pages 1-23, October.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:19:p:6296-:d:648915
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    References listed on IDEAS

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    1. Menezes, Anna Carolina & Cripps, Andrew & Bouchlaghem, Dino & Buswell, Richard, 2012. "Predicted vs. actual energy performance of non-domestic buildings: Using post-occupancy evaluation data to reduce the performance gap," Applied Energy, Elsevier, vol. 97(C), pages 355-364.
    2. Eunil Park & Angel P. Del Pobil & Sang Jib Kwon, 2018. "The Role of Internet of Things (IoT) in Smart Cities: Technology Roadmap-oriented Approaches," Sustainability, MDPI, vol. 10(5), pages 1-13, May.
    3. Lin, Hung-Wen & Hong, Tianzhen, 2013. "On variations of space-heating energy use in office buildings," Applied Energy, Elsevier, vol. 111(C), pages 515-528.
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    Cited by:

    1. Aya Nabil Sayed & Faycal Bensaali & Yassine Himeur & Mahdi Houchati, 2023. "Edge-Based Real-Time Occupancy Detection System through a Non-Intrusive Sensing System," Energies, MDPI, vol. 16(5), pages 1-14, March.
    2. Muhammad Emad-Ud-Din & Ya Wang, 2023. "Indoor Occupancy Sensing via Networked Nodes (2012–2022): A Review," Future Internet, MDPI, vol. 15(3), pages 1-20, March.

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