Abstract
This paper presents a cloud-based building energy management system, underpinned by semantic middleware, that integrates an enhanced sensor network with advanced analytics, accessible through an intuitive Web-based user interface. The proposed solution is described in terms of its three key layers: 1) user interface; 2) intelligence; and 3) interoperability. The system's intelligence is derived from simulation-based optimized rules, historical sensor data mining, and a fuzzy reasoner. The solution enables interoperability through a semantic knowledge base, which also contributes intelligence through reasoning and inference abilities, and which are enhanced through intelligent rules. Finally, building energy performance monitoring is delivered alongside optimized rule suggestions and a negotiation process in a 3-D Web-based interface using WebGL. The solution has been validated in a real pilot building to illustrate the strength of the approach, where it has shown over 25% energy savings. The relevance of this paper in the field is discussed, and it is argued that the proposed solution is mature enough for testing across further buildings.
Highlights
P UBLIC buildings have substantial proliferations of control/automation technologies and tend to experience large discrepancies between “designed” and “operational” energy use, as well as increased user comfort dissatisfaction [1], [2]
This paper proposes a methodology that exploits finer integration of sensing, interoperability, intelligence, and user interfaces to confer facility managers (FMs) the desired levels of interaction with the building management systems (BMSs) to address a wide range of energy scenarios
The 3-D graphics software interface to WebGL is written in JavaScript, which allows the use of the document object model to manipulate the Web page, and allows the visualization to be manipulated by standard Web form controls
Summary
P UBLIC buildings have substantial proliferations of control/automation technologies and tend to experience large discrepancies between “designed” and “operational” energy use, as well as increased user comfort dissatisfaction [1], [2]. State-of-the-art research in BMSs involves the use of semantic-based real-time sensing tools [7]–[9] that factor in space occupancy patterns as well as user comfort feedback These tools need to promote more effective energy control strategies through enhanced interoperability with existing energy modeling environments, building control systems, and operational log feeds, and deliver higher-order intelligence (through correlation and analysis of energy modeling predictions and actual use), accessible through more intuitive user-interfaces. This paper proposes a methodology that exploits finer integration of sensing, interoperability, intelligence, and user interfaces to confer FMs the desired levels of interaction (including automation and functionality) with the BMS to address a wide range of energy scenarios This builds on prior work [7], [10], following further experimentation with the approach, development of the underpinning software. This paper discusses the proposed approach and provides concluding remarks and directions for future research
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