A method for detecting spatio-temporal anomalies in online river networks

A technology of abnormal events and detection methods, applied in electrical components, network topology, wireless communication, etc., can solve problems such as the inability to comprehensively consider the time-space correlation of network abnormal events, and achieve the goal of terminating the spread of pollution, reducing false alarm rates, and reducing losses Effect

Active Publication Date: 2018-03-20
HOHAI UNIV
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Problems solved by technology

[0005] Purpose of the invention: a method for detecting spatio-temporal anomalies in online river networks, solving the problem that the prior art cannot comprehensively consider the spatio-temporal correlation of network anomalies

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  • A method for detecting spatio-temporal anomalies in online river networks
  • A method for detecting spatio-temporal anomalies in online river networks
  • A method for detecting spatio-temporal anomalies in online river networks

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Embodiment Construction

[0039] Below in conjunction with specific embodiment, further illustrate the present invention, should be understood that these embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention, after having read the present invention, those skilled in the art will understand various equivalent forms of the present invention All modifications fall within the scope defined by the appended claims of the present application.

[0040] The present invention provides an embodiment of an online river network spatiotemporal abnormal event detection algorithm, figure 1 It is the general frame diagram of spatio-temporal anomaly event detection in online river network. It can be seen that the main steps of the embodiment of the present invention are as follows:

[0041] (1) Use the connected dominance set algorithm to select the backbone nodes, and monitor the time and space status of the backbone nodes online instead of monit...

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Abstract

The invention discloses a method for detecting an online river network spatio-temporal abnormal event, which comprises the following steps: firstly, using a connected dominating set algorithm to select a backbone node, and only detecting the state of the backbone node in each time stamp sensor network; then, detecting Whether the backbone node has a spatio-temporal anomaly event; if the backbone node has a time anomaly, add the child node of the backbone node to the candidate set for detection; learn the expected state and observed state of the backbone node with the time anomaly through Bayesian network learning Make a comparison to see if it deviates from the spatial relationship obtained by learning. If a spatial anomaly occurs, the space-time anomaly counter is incremented by 1. At the next timestamp, expand the detection range to include the backbone nodes and nodes in the candidate set, and continue to detect whether spatial anomalies or temporal anomalies occur. Finally, when the number of spatiotemporal anomalies of the backbone node and its candidate set nodes reaches the threshold Q, it is considered that a spatiotemporal anomaly event occurs.

Description

technical field [0001] The invention relates to the technical field of wireless sensor network detection, in particular to a method for detecting spatio-temporal abnormal events in a river network wireless sensor network using a decentralized method. Background technique [0002] With the rapid development of sensor technology and the increasing maturity of wireless communication technology, wireless sensor networks are widely used in ecological scientific observation, environmental monitoring, disaster early warning, and national defense and military fields. In these practical applications, automated anomaly event detection functions are essential. Generally speaking, in order to take corresponding remedial measures for network abnormalities as soon as possible, it is necessary to detect all sudden events that affect system applications in real time, including physical phenomena, pollutant monitoring, etc., and then give early warning prompts. Sensors are deployed in the r...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/30H04W84/18
Inventor 毛莺池接青贾必聪平萍王龙宝许峰周晓峰
Owner HOHAI UNIV
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