Presenter/Author Type

Faculty

Department or Field of Research

Smart Building, Wireless sensor network, Hybrid

Submission type

Full Paper Submission

Disciplines

Construction Engineering and Management | VLSI and Circuits, Embedded and Hardware Systems

Keywords

Smart Building, Wireless Sensor Network, Hybrid CO2 and Light Sensor, Occupany Estimation

Brief Description

Smart building, which delivers useful services to residents at lowest cost and maximum comfort, has gained increasing attention in recent years. A variety of emerging information technologies have been adopted in modern buildings, such as wireless sensor networks, internet of things, big data analytics, deep machine learning, etc. Most people agree that a smart building should be energy efficient, and consequently, much more affordable to building owners. Building operation accounts for major portion of energy consumption in the United States. HVAC (heating, ventilating, and air conditioning) equipment is a particularly expensive and energy consuming of building operation. As a result, the concept of “demand-driven HVAC control” is currently a growing research topic for smart buildings. In this work, we investigated the issue of building occupancy estimation by using a wireless CO2 sensor network. The concentration level of indoor CO2 is a good indicator of the number of room occupants, while protecting the personal privacy of building residents. Once indoor CO2 level is observed, HVAC equipment is aware of the number of room occupants. HVAC equipment can adjust its operation parameters to fit demands of these occupants. Thus, the desired quality of service is guaranteed with minimum energy dissipation. Excessive running of HVAC fans or pumps will be eliminated to conserve energy. Hence, the energy efficiency of smart building is improved significantly and the building operation becomes more intelligent. The wireless sensor network was selected for this study, because it is tiny, cost effective, non-intrusive, easy to install and flexible to configure. In this work, we integrated CO2 and light senors with a wireless sensor platform from Texas Instruments. Compare with existing occupancy detection methods, our proposed hybrid scheme achieves higher accuracy, while keeping low cost and non-intrusiveness. Experimental results in an office environment show full functionality and validate benefits. This study paves the way for future research, where a wireless CO2 sensor network is connected with HVAC systems to realize fine-grained, energy efficient smart building.

Paper ID 1055.pptx (12932 kB)
ASA symposium presentation slides

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Oct 15th, 2:15 PM Oct 15th, 2:45 PM

Occupancy Estimation in Smart Building using Hybrid CO2/Light Wireless Sensor Network

Smart building, which delivers useful services to residents at lowest cost and maximum comfort, has gained increasing attention in recent years. A variety of emerging information technologies have been adopted in modern buildings, such as wireless sensor networks, internet of things, big data analytics, deep machine learning, etc. Most people agree that a smart building should be energy efficient, and consequently, much more affordable to building owners. Building operation accounts for major portion of energy consumption in the United States. HVAC (heating, ventilating, and air conditioning) equipment is a particularly expensive and energy consuming of building operation. As a result, the concept of “demand-driven HVAC control” is currently a growing research topic for smart buildings. In this work, we investigated the issue of building occupancy estimation by using a wireless CO2 sensor network. The concentration level of indoor CO2 is a good indicator of the number of room occupants, while protecting the personal privacy of building residents. Once indoor CO2 level is observed, HVAC equipment is aware of the number of room occupants. HVAC equipment can adjust its operation parameters to fit demands of these occupants. Thus, the desired quality of service is guaranteed with minimum energy dissipation. Excessive running of HVAC fans or pumps will be eliminated to conserve energy. Hence, the energy efficiency of smart building is improved significantly and the building operation becomes more intelligent. The wireless sensor network was selected for this study, because it is tiny, cost effective, non-intrusive, easy to install and flexible to configure. In this work, we integrated CO2 and light senors with a wireless sensor platform from Texas Instruments. Compare with existing occupancy detection methods, our proposed hybrid scheme achieves higher accuracy, while keeping low cost and non-intrusiveness. Experimental results in an office environment show full functionality and validate benefits. This study paves the way for future research, where a wireless CO2 sensor network is connected with HVAC systems to realize fine-grained, energy efficient smart building.