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Notice of retraction
Vol. 34, No. 8(3), S&M3042

Notice of retraction
Vol. 32, No. 8(2), S&M2292

Print: ISSN 0914-4935
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.

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Sensors and Materials, Volume 32, Number 5(3) (2020)
Copyright(C) MYU K.K.
pp. 1931-1943
S&M2230 Research Paper of Special Issue
https://doi.org/10.18494/SAM.2020.2729
Published: May 31, 2020

Smart Building Hybrid Ventilation System under Wireless Sensor Network Environment [PDF]

Yun-Wu Wu, Jin-Lian Lee, Wei-Chung Kuo, and Ding-Chin Chou

(Received December 4, 2019; Accepted April 24, 2020)

Keywords: green building, Internet of Things, comfort level, indoor temperature regulation

Natural building ventilation is an effective method for maintaining comfortable and healthy indoor environments. This study aims to develop a novel smart building hybrid ventilation system capable of tracking wind direction using wireless control technologies and sensory capabilities. Natural and mechanical ventilation components are integrated to create a highly efficient and healthy ventilation system for a building. With this system, wind speed and direction are measured using a windmill anemometer, and this information is relayed to the control system. The control system uses this information to modify the openings of the adjustable rooftop developed in this study toward the direction of the wind using a set of interlinked devices. This guides fresh airflow indoors, improving the comfort of indoor environments through the circulation of airflow. This is expected to reduce the energy consumption of air-conditioning systems.

Corresponding author: Wei-Chung Kuo


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Cite this article
Yun-Wu Wu, Jin-Lian Lee, Wei-Chung Kuo, and Ding-Chin Chou, Smart Building Hybrid Ventilation System under Wireless Sensor Network Environment, Sens. Mater., Vol. 32, No. 5, 2020, p. 1931-1943.



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