This study examines the application of big data clustering algorithms in the field of electrical engineeringautomation. Electrical engineeringautomation is a key area that covers power system management, smart grids...
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Trigger-action programming (TAP) is a widely used development paradigm that simplifies the Internet of Things (IoT) automation. However, the exceptional interactions between automation applications may result in inter...
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ISBN:
(纸本)9798350329964
Trigger-action programming (TAP) is a widely used development paradigm that simplifies the Internet of Things (IoT) automation. However, the exceptional interactions between automation applications may result in interferences, such as conflicts and infinite loops, which cause undesirable consequences and even security and safety risks. While several techniques have been proposed to address this problem, they are often restricted in handling explicit and simple conflicts without considering contextual influences. In addition, they suffer from performance issues when applying to large-scale applications. To address these challenges, we design an effective and practical tool KnowDetector with comprehensive domain knowledge to detect application interferences. To detect application interferences, KnowDetector constructs an automation graph with 1) events, conditions, and actions from automation applications, 2) vertices representing physical environment channels, and 3) edges derived from potential semantic relations between the vertices. In order to make the graph extensively capture the interactions between automation applications, we propose a knowledge model named KnowIoT that accurately characterizes IoT devices with command-level IoT services and the intricate relations between these services and the contextual environment. We abstract the interference detection into a graph pattern-matching problem and summarize ten application interference patterns of four types. Finally, KnowDetector can efficiently detect application interferences by searching for sub-graphs matching the patterns within the automation graph. We evaluated KnowDetector on three real-world datasets. The results demonstrated that it outperformed the other state-of-the-art tools with the highest precision, recall, and F-measure. In addition, KnowDetector is scalable to detect application interferences within a large number of applications with a minimal time overhead.
The geomagnetic induced current (GIC) generated by changes in the Earth's magnetic field caused by space weather activities such as solar wind poses a great threat to the safety of the power grid. The GIC predicti...
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In order to simplify the virtual simulation of aircraft power system maintenance, a virtual maintenance process modeling method based on system modeling language (SysML) is proposed by introducing the object-oriented ...
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This paper presents an Explicit Model Predictive Control (EMPC) for building HVAC control considering the Time-of-Use (TOU) electricity prices. The main contribution of this paper lies in evaluation studies in a devel...
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Foreign body detection technology is directly related to the safety of wireless charging systems. Therefore, this essay analyzes the domestic and international research status of foreign body detection technology of r...
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In this paper, a protection scheme for fault detection, classification, and location in non-homogenous HVDC lines is presented based on the rate of change of voltage (ROCOV) signal attained from a single end by applyi...
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The integration of large-scale photovoltaic power plants into the power system has caused voltage control problems, and this article conducts research on reactive power control optimization. Through the comparative an...
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In response to the actual electromagnetic interference problem of Ethernet cards in high-speed railway operation, the TRDP network card Ethernet driver circuit self-developed in the laboratory is taken as the research...
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With the increasing integration of distributed energy sources into the grid, VPP has garnered widespread attention as a distributed energy management technology due to their flexibility, efficiency, and sustainability...
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