39results about How to "Realize intelligent early warning" patented technology

The invention provides a wireless network cloud platform system based on lighting nodes. The wireless network cloud platform system comprises a wireless gateway, at least one wireless lighting driver, at least one wireless lighting controller, at least one positioned terminal and a cloud server client side. A cloud server is connected with a wireless gateway, issues configuration information to the at least one wireless lighting driver and the at least one wireless lighting controller for configuration, controls the at least one wireless lighting driver and judges whether faults exist in a lighting line or not according to a current and energy consumption of the lighting line. Position monitoring is carried out on the positioned terminal according to the positioning information of the positioned terminal, the environment in a preset area is monitored according to environment parameters, and monitoring data are displayed to a user. According to the embodiment, wired lighting control is replaced with the wireless lighting, and labor cost and material cost can be saved. In addition, lighting energy consumption is monitored in real time, dimming is carried out according to current illuminance, and therefore electric energy consumption can be saved.

The invention discloses an overhauling operation control method based on a mobile terminal. The method comprises the following steps: constructing an overhauling operation control platform based on the mobile terminal; constructing a software platform; and the software platform formulating a corresponding operation task according to the overhauling operation task, setting an instruction template and transmitting the task instruction to the corresponding first to Mth mobile terminals, the mobile terminal locking other mobile terminals and viewing the operation progress in real time and the like. The method has the advantages: real-time information communication is performed on the site operation condition by the mobile terminal, so that low efficiency caused by multiple calls or repeated communication with paper is avoided; and an operator uses the mobile terminal to remotely control an intelligent socket to achieve the purposes of intelligent power disconnection and power connection, so that intelligent early warning of potential safety hazards is realized, information can fed back to the mobile terminal and a mobile overhauling operation controller in real time, and the safety of site operation is ensured.

The invention discloses a method used for reminding a user who is to go out and applied to an intelligent terminal as well as the intelligent terminal. The method used for reminding the user who is to go out comprises steps as follows: detecting the weather condition of the area where the intelligent terminal is located, judging whether the user of the mobile terminal is to go out or not if the weather condition of the area where the intelligent terminal is located is detected to be rainy or about to be rainy, and outputting a reminding signal to remind the user that it rains or is about to rain in the area where the intelligent terminal is located if the user is to go out. With the adoption of the technical scheme, an intelligent prewarning can be provided for the user who is to go out.

The invention discloses a system for vehicle-mounted RFID information data relay transmission, which comprises a vehicle-mounted receiving end, a vehicle-mounted relay end, and a vehicle-mounted transmitting end, wherein the vehicle-mounted receiving end is used for receiving signal data transmitted by surrounding vehicle-mounted transmitting ends or signal data transmitted by road-side transmitting ends; the vehicle-mounted relay end transmits the signal data received by the vehicle-mounted receiving end to surrounding other vehicle-mounted receiving ends and road-side receiving ends in a covering mode, or carries out amplification processing on the signal data received by the vehicle-mounted receiving end and then transmits the signal data to the surrounding other vehicle-mounted receiving ends and road-side receiving ends in a covering mode; and the vehicle-mounted transmitting end transmits the vehicle driving state parameters to the surrounding other vehicle-mounted receiving ends and the vehicle-mounted relay ends in a covering mode or transmits the parameters to the road-side receiving ends in a covering mode. Through building a relay system between vehicles, the problem that the metal vehicle body blocks RFID signals can be overcome, effective reading of the driving state parameters between the vehicles can be ensured, and the purposes of intelligent early warning and driving vehicle safety control can be realized.

The invention provides an intelligent early warning model establishment method for an alarm occurrence area, which is applied to the technical field of alarm early warning, and comprises the followingsteps: acquiring a user and position information of the user from a database according to a preset time period, and acquiring pedestrian flow information based on the user and the corresponding position information of the user; determining a target area needing alarm early warning; acquiring historical alarm data of the target area; training a long-term and short-term memory model by adopting thehistorical warning condition data and the pedestrian volume information; wherein the target function is used for calculating an alarm occurrence probability according to prediction information corresponding to a to-be-predicted area, and the to-be-predicted information comprises time required to be predicted, a pedestrian volume mean value in the prediction time and influence factors in the prediction time. The invention further provides an intelligent early warning model establishing device for the alarm occurrence area and a storage medium, and intelligent early warning is carried out through the pedestrian flow information and the historical alarm information.

The invention belongs to the power system field, relates to the application of an infrared thermal imaging technology carrying out fault detection on power equipment and especially relates to a powerequipment state intelligent early warning method based on an infrared image. The method is characterized by constructing an infrared atlas database; carrying out image processing; carrying out character area identification; carrying out limit segmentation; carrying out character identification; constructing an artificial neural network; and acquiring an early warning analysis report. In the invention, the health state evaluation and the intelligent early warning of power equipment based on the infrared image are realized, the high-efficiency management of the infrared image can be realized, and the various characteristic parameters of the infrared image of the power equipment are automatically extracted. The artificial neural network suitable for power equipment maximum operating temperature prediction is designed, and a load current, an atmospheric temperature, relative humidity, a reflection coefficient, a reflection temperature, a photographing distance and a radiation coefficient are taken as inputs so as to realize the power equipment maximum operating temperature prediction. Based on a predicted maximum operating temperature, the health state evaluation and the intelligent early warning of the power equipment are realized.

The invention relates to a dynamic early warning method for third-party construction along a pipeline based on SVM and time-frequency domain features. The method comprises the steps of S1 collecting waveform data in real time, carrying out the threshold triggering and data preprocessing of the waveform data, and obtaining a suspicious waveband and a corresponding suspicious defense area; S2 extracting corresponding time domain features and frequency domain features according to the waveform of the suspicious waveband, and obtaining dynamic space-time big data information corresponding to the suspicious defense area, wherein the dynamic space-time big data information comprises time information, GIS information, weather information and high consequence area information; and S3 inputting thetime domain features, the frequency domain features and the dynamic space-time big data information into an SVM prediction model, and judging whether a vibration source corresponding to the waveformof the suspicious waveband is constructed by a third party or not in real time so as to perform early warning. According to the method, dynamic space-time big data information of each defense area isconsidered, and dynamic intelligent early warning is realized for third-party construction in combination with time domain features and frequency domain features of waveforms.

The invention relates to the technical field of dangerous rock mass monitoring and early warning, in particular to a dangerous rock mass acousto-optic combined intelligent monitoring and early warning method. The method comprises the steps of S1, selecting an object, specifically, selecting a dangerous rock mass below which a threatened object exists; S2, installing instruments, specifically, installing an alarm instrument on a stable mountain body on the inner side or the side of the dangerous rock mass, wherein the alarm instrument comprises a control module, and installing a monitoring instrument on the dangerous rock mass or between the dangerous rock mass and the mountain body; and S3, performing initial data acquisition, specifically, acquiring data of the size, shape, height, inclination direction, inclination angle, displacement, crack width, landform conditions of the dangerous rock mass and distribution of threatened object through two modes, namely, the monitoring instrument and manual observation, and inputting the manually acquired data into the monitoring instrument. According to the technical scheme, the dangerous rock mass is monitored in real time, meanwhile, when the dangerous rock mass collapses, a sound-light alarm signal is sent out at the first time, a safe escape path is pointed out to threatened people, and the personal safety of the people is ensured.

The invention provides a lift car fault judgement method and system based on a multi-axis sensor technology. The system comprises a multi-axis sensor unit, a data acquisition unit, a platform processing unit and a fault early-warning unit; the multi-axis sensor unit is used for acquiring the acceleration and the deceleration of a car, the running speed and vibration data in X-axis, Y-axis and Z-axis directions in real time; the data acquisition unit is used for acquiring data fed back by the multi-axis sensor unit and uploading the data to the platform processing unit and comprises a wirelessmodule connected with the network; the platform processing unit is used for storing and analyzing the data and starting early warning for data exception conditions found through analysis; and the fault early-warning unit is used for displaying early-warning prompts when running conditions of the car are abnormal and comprises a WEB application and an APP. According to the method, self-monitoring,self-diagnosis and intelligent early-warning of faults including the acceleration, the deceleration, the real-time speed, the positional deviation, abnormal vibration in the X-axis, Y-axis and Z-axisdirections and the like during running of the lift car are realized on the basis of the system.

The invention discloses a risk assessment system for realizing intelligent early warning. The system comprises a data acquisition unit and a risk factor input unit; the output end of the data acquisition unit is connected with a data editing module; the output end of the data editing module is connected with a data analysis module; the output end of the data analysis module is connected with a risk assessment unit; the output end of the risk assessment unit is connected with a wireless transmission module; the output end of the wireless transmission module is connected with a data storage device; the output end of the data storage device is connected with a GIS data visualization platform; the output end of the risk assessment unit is connected with a risk test module; and the output end of the risk test module is connected with a risk alarm unit. The invention belongs to the technical field of expressway management. With the risk assessment system for realizing intelligent early warning adopted, the intelligent risk early warning of highway construction data can be realized, and information assessment efficiency can be improved.

The invention discloses a user going-out reminding method applied to an intelligent terminal and an intelligent terminal. The abovementioned user going-out reminding method includes: judging whether a user of an intelligent terminal goes out; if the user is judged to go out, detecting weather conditions of an area where the intelligent terminal; and if the weather conditions of the area where the intelligent terminal are detected to be raining or about to rain, outputting a reminding signal, so as to remind the user that it is raining or is about to rain in the area where the intelligent terminal is. The technical scheme provided by the invention can provide intelligent early warning for the user to go out.

A method for counting the fixed number of staff in the dangerous workplace with multiple entrances and exits is provided. The method comprises: using sensing equipment to collect information of the number of in and out staff; taking an information management system as the intelligent staff counting information platform to combine with the sensing equipment under the agreement so as to collect information of the number of the in and out staff; and carrying out analysis and comparison between the staff counting information and the critical number of the staff required by the workshop, and when an overstaff situation is founded, performing sound and light prompts by using an alarm light, and generating alarm records in the system for user inquiries.

The invention discloses a method used for reminding a user who is to go out and applied to an intelligent terminal as well as the intelligent terminal. The method used for reminding the user who is to go out comprises steps as follows: detecting the weather condition of the area where the intelligent terminal is located, judging whether the user of the mobile terminal is to go out or not and outputting a reminding signal to remind the user that it rains or is about to rain in the area where the intelligent terminal is located if the weather condition of the area where the intelligent terminal is located is judged to be rainy or about to be rainy and the user is to go out. With the adoption of the technical scheme, an intelligent prewarning can be provided for the user who is to go out.

According to the invention, real-time monitoring and behavior analysis are carried out on an operator, non-standard operation and behaviors are intervened, video monitoring and error prevention are integrated, and post-event tracing of an accident can be realized; and an intelligent analysis function is achieved, specific events and user behaviors are monitored, and intelligent early warning of accidents is achieved. A method comprises the following steps: erecting a plurality of cameras on a transformer substation equipment site, acquiring video signals of the cameras in a transformer substation, and transmitting the video signals to a computer; building an artificial intelligence OpenCV visual library, and utilizing a GPU parallel processing technology; and constructing a deep neural network to recognize the image, and realizing behavior analysis, judgment and monitoring of an operator. Video monitoring, intelligent analysis, behavior monitoring and anti-misoperation locking technologies are deeply fused, and when a specific behavior is found, an alarm is automatically generated to inform monitoring personnel of timely early warning, linkage and processing.

The invention discloses a bridge ship collision prevention monitoring and early warning system comprising a detection subsystem used for collecting radar signals, image signals and Beidou positioning signals of coming and going ships and obtaining dynamic information of the coming and going ships; the calculation subsystem is used for predicting surrounding dangerous conditions through a situation awareness theory according to the dynamic information, and generating an early warning signal and a navigation instruction for avoiding the dangerous conditions; the execution subsystem is used for sending an early warning signal and a navigation instruction to the passing ship according to the early warning signal and starting a bridge passive protection device; a data model capable of expressing multi-source, multi-dimension and multi-scale channel elements is designed, a data model conversion scheme is formulated, data geometric position characteristics are analyzed, a risk theoretical model of ship collision bridges and other offshore structures is constructed, a multi-source fusion processing algorithm is developed, and intelligent early warning of ship collision bridges and other offshore structures is achieved.