Residential College | false |
Status | 已發表Published |
An IoT-Based Smart Controlling System of Air Conditioner for High Energy Efficiency | |
Wei Song1![]() ![]() | |
2018-02-01 | |
Conference Name | 2017 IEEE INTERNATIONAL CONFERENCE ON INTERNET OF THINGS (ITHINGS) AND IEEE GREEN COMPUTING AND COMMUNICATIONS (GREENCOM) AND IEEE CYBER, PHYSICAL AND SOCIAL COMPUTING (CPSCOM) AND IEEE SMART DATA (SMARTDATA) |
Source Publication | 2017 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData)
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Pages | 442-449 |
Conference Date | 21-23 June 2017 |
Conference Place | Exeter, UK |
Publication Place | 345 E 47TH ST, NEW YORK, NY 10017 USA |
Publisher | IEEE |
Abstract | In current electric energy statistics, the largest power is consumed by heating and cooling air conditioners, which are widely used in residential and commercial buildings. Hence, reducing energy consumption of air conditioners is vitally important for improving power utilization efficiency in global energy perspective. To save electricity consumption of air conditioners, this paper proposes an Internet of Things (IoT)-based smart controlling system including smart meter, smart gateway, and cloud computing modules. We manufacture a smart meter to control the compressor operation of air conditioners based on the specified temperature. Meanwhile, it is able to monitor the real-time power consumption datasets, which are delivered to a cloud server via a wireless gateway. Using Zigbee communication protocol, our developed gateway enables automatic detection of smart meter by a broadcasting method. After gathering the IP addresses of connected smart meters, the gateway dispatches controlling signals to relevant meters. We developed a general programming interface to control the operation of this smart gateway so as to support flexible and extensible IoT development. The collected electricity consumption datasets are transmitted to a cloud server in real time via Internet. Meanwhile, the remote operation signals of smart meters are transmitted to the cloud. An extreme learning machine is implemented to analyze the energy distribution for energy consumption prediction. Based on the analysis results and operation signals, the cloud generates an energy-saving decision to control the distributed air conditioners by the smart meters, which are linked to the Internet through the gateways. This way, an individual smart meter controls cooling and heating operations of its corresponding compressor to realize local energy management. Besides, the energy saving strategy eases power grid burden and decrease load of power station. Thus, our proposed system has positive influence on greenhouse gas reduction. |
Keyword | Energy Conservation Smart Meter Iot Cloud Computing |
DOI | 10.1109/iThings-GreenCom-CPSCom-SmartData.2017.72 |
URL | View the original |
Indexed By | CPCI-S |
Language | 英語English |
WOS Research Area | Computer Science |
WOS Subject | Computer Science, Artificial Intelligence ; Computer Science, Cybernetics |
WOS ID | WOS:000426972400068 |
The Source to Article | WOS |
Scopus ID | 2-s2.0-85047401509 |
Fulltext Access | |
Citation statistics | |
Document Type | Conference paper |
Collection | DEPARTMENT OF COMPUTER AND INFORMATION SCIENCE |
Corresponding Author | Wei Song |
Affiliation | 1.Dept. of Digital Media Technology North China University of Technology Beijing, China 2.Department of Computer and Information Science University of Macau Macau, China |
Recommended Citation GB/T 7714 | Wei Song,Ning Feng,Yifei Tian,et al. An IoT-Based Smart Controlling System of Air Conditioner for High Energy Efficiency[C], 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE, 2018, 442-449. |
APA | Wei Song., Ning Feng., Yifei Tian., & Simon Fong (2018). An IoT-Based Smart Controlling System of Air Conditioner for High Energy Efficiency. 2017 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData), 442-449. |
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