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Open AccessArticle

Hybrid Ventilation System and Soft-Sensors for Maintaining Indoor Air Quality and Thermal Comfort in Buildings

1
Department of Instrumentation and Control Engineering and Center for Research in Automatic Control Engineering (C-RACE), Kalasalingam University, Srivilliputhur 626125, India
2
Department of Architecture and Built Environment, University of Northumbria at Newcastle, Newcastle Upon Tyne NE1 8ST, UK
3
Berkeley Education Alliance for Research in Singapore, Singapore 138602, Singapore
*
Author to whom correspondence should be addressed.
Atmosphere 2020, 11(1), 110; https://doi.org/10.3390/atmos11010110
Received: 9 December 2019 / Revised: 23 December 2019 / Accepted: 31 December 2019 / Published: 16 January 2020
(This article belongs to the Special Issue Indoor Thermal Comfort)
Maintaining both indoor air quality (IAQ) and thermal comfort in buildings along with optimized energy consumption is a challenging problem. This investigation presents a novel design for hybrid ventilation system enabled by predictive control and soft-sensors to achieve both IAQ and thermal comfort by combining predictive control with demand controlled ventilation (DCV). First, we show that the problem of maintaining IAQ, thermal comfort and optimal energy is a multi-objective optimization problem with competing objectives, and a predictive control approach is required to smartly control the system. This leads to many implementation challenges which are addressed by designing a hybrid ventilation scheme supported by predictive control and soft-sensors. The main idea of the hybrid ventilation system is to achieve thermal comfort by varying the ON/OFF times of the air conditioners to maintain the temperature within user-defined bands using a predictive control and IAQ is maintained using Healthbox 3.0, a DCV device. Furthermore, this study also designs soft-sensors by combining the Internet of Things (IoT)-based sensors with deep-learning tools. The hardware realization of the control and IoT prototype is also discussed. The proposed novel hybrid ventilation system and the soft-sensors are demonstrated in a real research laboratory, i.e., Center for Research in Automatic Control Engineering (C-RACE) located at Kalasalingam University, India. Our results show the perceived benefits of hybrid ventilation, predictive control, and soft-sensors. View Full-Text
Keywords: indoor air quality (IAQ); hybrid ventilation; demand controlled ventilation (DCV); internet of things (IoT); soft-sensor; convolution neural networks indoor air quality (IAQ); hybrid ventilation; demand controlled ventilation (DCV); internet of things (IoT); soft-sensor; convolution neural networks
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Vadamalraj, N.; Zingre, K.; Seshadhri, S.; Arjunan, P.; Srinivasan, S. Hybrid Ventilation System and Soft-Sensors for Maintaining Indoor Air Quality and Thermal Comfort in Buildings. Atmosphere 2020, 11, 110.

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