The invention discloses a method and apparatus of determining alarm, and an alarm system, and relates to the technical field of communication. The method of determining alarm is applied to the alarm system. The alarm system includes a server, monitored nodes and at least two computing nodes, wherein preset type alarm rules are stored in each computing node. The method of determining alarm includesthe steps: a computing node obtains the monitoring data corresponding to the stored preset type alarm rules, according to the stored preset type alarm rules; the computing node can be any one of thecomputing nodes in the alarm system; and the computing nodes can determine alarm for the monitoring data according to the preset type alarm rules.

Method and apparatus of determining alarm, and alarm system

The invention relates to a method of universal early warning service capable of being defined and extended by a user. Through the method of universal early warning service capable of being defined and extended by the user, based on service data acquired by a monitoring device, an early warning type is added, an early warning rule is configured, a corresponding threshold is changed, an early warning notice is generated, the early warning notice identifies and distinguishes each target user, JPush push service is combined, pushing of the corresponding early warning notice is carried out for a specified user, and diversity and effectiveness of fire early warning are improved.

Method of universal early warning service capable of being defined and extended by user

The invention discloses a method for predicting lightning current amplitudes on the basis of meteorological parameters. The method comprises the following steps of: determining meteorological parameters related to lightning current amplitudes and obtaining numerical values of the meteorological parameters; establishing a relevance model of the numerical values of the meteorological parameter and the lightning current amplitudes by utilizing the numerical value of the meteorological parameters and the lightning current amplitudes corresponding to the numerical values of the meteorological parameters; selecting the numerical values of the meteorological parameters when a power transmission line trips for multiple times due to lightning stroke as input parameters of the relevance model, and selecting the corresponding lightning current amplitudes when the power transmission line trips as output parameters so as to train the relevance model; selecting a numerical value of a history meteorological parameter, and calculating the numerical value of the history meteorological parameter by utilizing a training model so as to obtain a calculated lightning current amplitude; when an error value between the calculated lightning current amplitude and a lightning current amplitude corresponding to the numerical value of the history meteorological parameter satisfies a predetermined error threshold value, taking the training model as a determined prediction model; and inputting a real-time meteorological parameter into the prediction model so as to obtain a real-time lightning current amplitude predicted value.

Method and system for predicting lightning current amplitudes on basis of meteorological parameters

The embodiment of the invention provides a danger early warning method, a device, a system and a video acquisition device. The method is applied to a video acquisition device. Wherein, each monitoringdata carries identification information of a sensor that collects the monitoring data; According to the identification information of the sensors carried in each monitoring data, comparing each monitoring data with the reference data corresponding to the sensors that collect the monitoring data stored locally to obtain the risk coefficients corresponding to all the monitoring data; Wherein, the reference data corresponding to each sensor stored locally is obtained by processing the normal history data through a neural network self-learning algorithm according to the normal history data collected by the sensor; According to the hazard coefficient, it is determined whether or not an alarm is carried out. The embodiment of the invention can effectively carry out hazard early warning on the monitoring scene.

Hazard early war method, device, system and video acquisition device

The present invention relates to a network fault early warning method and device. The method comprises the steps of: obtaining operation data of a target switched network node in a current network; training an artificial neural network model according to the operation data of the target switched network node; and predicting the fault probability of the target switched network node according to thetrained artificial neural network model and the operation data of the current network collected in real time. The network fault early warning method and device can achieve prediction of faults of switched nodes according to the operation data of each node in the network, and can train and update the artificial neural network model through adoption of an adaptive method so as to improve the prediction precision of a failure rate of each switched node in the current network, achieve advanced fault early warning and avoid loss.

Network fault early warning method and device

The invention relates to an early warning method based on rule engine and intelligent prediction. The method comprises steps as follows: various monitoring data sensing gateways wirelessly upload monitoring data to an early warning analyzer, the early warning analyzer analyzes the monitoring data in combination with two modes and finally judges whether the monitoring data meet the early warning condition or not, and the early warning analyzer judges whether early warning is performed or not according to an early warning rule which is analyzed by a rule engine and flexibly configured by a user or according to current monitoring data and future monitoring data predicted from historical data with a neutral network method in combination with the early warning rule or according to historical monitoring data and historical early warning data trained models. Early warning is performed timely if the early warning analyzer gives an early warning. The method is used for solving problems that existing early warning rules in all industries are diversified and complex to manually maintain, heavier in workload, low in early warning timeliness and short in handling and protection time.

Early warning method based on rule engine and intelligent prediction

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Early warning method based on rule engine and intelligent prediction