173results about How to "Improve early warning efficiency" patented technology

The invention discloses an event warning method based on Internet information and belongs to the technical field of information. The method comprises the following steps. Firstly, crawling of webpage information on each set website is performed, the webpage information is stored, and information relevant to an event is obtained. Secondly, junk information filtering is performed on the information which is relevant to the event and obtained by crawling. Thirdly, an event information main body is set up, the information after filtering is sorted based on example names and attributes in the event information main body by utilizing a mode matching method. Fourthly, the sorted information is clustered according to set characteristics, and events in each kind of information are obtained. Fifthly, all the characteristic parameter values of each event are obtained regularly, and if a difference value of all the characteristic parameter values of one event and an average value of the event in a given previous period exceeds a preset threshold, warning on the event is performed. The event warning method based on the internet information ensures timeliness, accuracy and comprehensiveness of information identification and warning of food safety events, and improves efficiency of risk warning of food safety.

The invention relates to a method and a system for monitoring horizontal deformation of a soil body in a mined-out subsidence area and a method for constructing the system. A fiber grating sensor network a(3) monitors the horizontal deformation of a soil body above a pipeline a(2) in real time, acquired data passes through an optical cable a(5) and an optical switch (6) and is demodulated by a fiber grating demodulation instrument (7) and transmitted to a lower computer (8), and the lower computer (8) calls a self-compiled program to control the optical switch (6) and the fiber grating demodulation instrument (7), so that the data is acquired and preprocessed; the preprocessed data is transmitted by a general packet radio service (GPRS) communication module a(9), received by a GPRS communication module b(10) and transmitted to an upper computer (11); and the upper computer (11) analyzes the horizontal deformation data of the soil body, and determines the stable state of the soil body in the mined-out subsidence area and the safety state of the pipeline according to the change of a monitoring curve and a monitoring numerical value.

The invention provides a landslide geological disaster early warning pushing method. The cloud computing technology is utilized for analyzing weather data, position data, geological data, environmental data and the like, an AHP landslide geological risk evaluation system and a geological disaster rainfall induction model are set up, information about time and probability for possible landslide geological disaster occurrence is predicted, and prediction precision is improved; a landslide geological early warning active pushing and preventing emergency response model based on position data service is utilized for pushing early warning and emergency information to terminal equipment, and efficiency of geological disaster early warning and pushing and initiative of disaster response are effectively improved.

The invention discloses a warehouse management system based on the Internet of Things, and a warehousing quality risk estimation method based on the warehouse management system, and relates to the field of cold chain logistics and intelligent warehousing. The system comprises a warehousing environment and material information sensing unit, an RFID middleware unit, warehousing onsite operation units, a data center unit, and a cloud service center unit. The warehousing environment and material information sensing unit is integrated on a sensing label. The RFID middleware unit is integrated on an RRID reader-writer. The warehousing onsite operation units are integrated on the reader-writer and a warehouse working terminal. The data center unit is deployed on the data server. The cloud service center unit is deployed on an application server. According to the invention, a BP neural network algorithm is creatively used for the risk early warning of the system, thereby achieving the real-time state analysis and warning of cold chain warehoused materials, and effectively solving a problem of warehousing quality risk estimation and alarm of fresh agricultural products in a cold chain warehouse. The system is good in application prospect.

The invention discloses an accident pre-warning method, device and system and belongs to the technical field of automobile networking. The method includes that first driving state data sent by a first automobile during current driving and second driving state data sent by a second automobile are received; whether the first driving state data and the second driving state data conform to an accident pre-warning condition or not is determined, and the accident pre-warning condition includes that the first automobile is an abnormal vehicle and the second automobile is a rear vehicle which is located on the same road section to the first automobile; when the data conform to the accident pre-warning condition, accident pre-warning information is sent to the second automobile according to the first driving state data. By means of the accident pre-warning method, device and system, the pre-warning efficiency of road accidents by a monitoring data center can be increased during automobile driving.

The invention discloses a method and a system for monitoring an oil-gas pipeline in a mining subsidence area and a system constructing method. The method comprises the following steps of: monitoring axial strain of a pipe body with a fiber grating strain sensor, monitoring pipe-soil relative replacement with a fiber grating displacement sensor, and monitoring horizontal deformation of a soil body with a fiber grating sensor; demodulating and preprocessing signals acquired by the sensors, and transmitting the signals to a remote monitoring center; further analyzing and processing data in the monitoring center, and computing horizontal deformation change of a soil body on the top of the pipe in the mining subsidence area, axial strain change of the pipe body and pipe-soil relative displacement change; judging the state stabilities of the pipe body strain change and the soil body strain change, and judging whether the data surpass threshold values; when three parameter values are smaller than respective threshold values, judging that the pipeline is in a safe state; and when the axial strain of the pipe body reaches 70 percent of a pipe body limit strain value, or a pipe-soil relative displacement value reaches a threshold value and keeps constant, or a horizontal deformation curve of the soil body changes suddenly, performing pipeline safety joint early-warning.

The invention discloses an anomaly detection early warning method and system. The method comprises the following steps: configuring monitored service indexes on a monitoring platform, and storing configuration information of the service indexes into a database; triggering an offline model training module, training a model offline, and uploading the trained model to a distributed file system, wherein the model is used for predicting monitoring indexes; pushing the index data to a distributed message queue system in real time; loading the configuration information and then storing the model, consuming the index data from the distributed message queue system in real time, taking the index data as input of the model to obtain a prediction result, and judging whether the index data is abnormalor not; and when the index data is abnormal, writing back alarm information of monitoring abnormality to the distributed message queue system, and reading the alarm information from the distributed message queue system in real time by the client. According to the invention, the monitored index data can be consumed in real time and whether abnormality exists or not can be detected, the detection delay problem of the monitoring index is reduced, and the early warning efficiency is greatly improved.

The invention discloses a method for monitoring an oil-gas pipeline in a mining subsidence area based on a fiber grating sensing technology. The method comprises the following steps of: monitoring pipe body axial strain with a fiber grating strain sensor, monitoring pipe-soil relative replacement with a fiber grating displacement sensor, and monitoring soil body horizontal deformation with a fiber grating sensing network; demodulating and preprocessing signals acquired by the sensors, and transmitting the signals to a remote monitoring center; further analyzing and processing data in the monitoring center, and computing mining subsidence soil body horizontal deformation change, pipe body axial strain change and pipe-soil relative displacement change; judging the state stabilities of the pipe body strain change and the soil body strain change, and judging whether the data surpass threshold values; when three parameter values are smaller than respective threshold values, judging that the pipeline is in a safe state; and when the pipe body axial strain reaches 70 percent of a pipe body limit strain value, or a pipe-soil relative displacement value reaches a threshold value and keeps constant, or a soil body horizontal deformation curve changes suddenly, performing pipeline safety joint early-warning.

The invention discloses a flood prevention consultation monitoring device and method based on the Internet of Things, relates to the technical field of flood prevention consultation monitoring, and solves the technical problem that the flood prevention accuracy is reduced due to the fact that regional analysis cannot be performed in the prior art.A region analysis unit is used for carrying out region division on the monitoring region and analyzing the divided regions; the geographical environment of each region is analyzed, the flood prevention accuracy is improved, and the monitoring error is reduced; an early warning signal is generated according to the current environment, so that heavy loss caused by flood due to the fact that the early warning signal is not timely is prevented; the regional analysis is verified, so that the accuracy of the regional data of the database is improved, and early warning errors caused by data exception are prevented; danger signals of different levels are generated according to river analysis, and the influence of flood is judged through real-time data, so that early warning measures of the same level are reasonably matched, the early warning efficiency is effectively improved, and the output cost of early warning is reduced.

The invention relates to the field of coal mine safety, in particular to a warning grading method and a warning method for spontaneous combustion of coal. The coal is prone to spontaneous combustion,and the warning for spontaneous combustion of coal is divided into six grades, namely, grey warning, blue warning, yellow warning, orange warning, red warning and black warning. The warning method includes the following steps: collecting O2, CO, CO2, CH4, C2H4 and C2H6 concentration data; judging the warning grade, and setting a warning threshold as R0, wherein the warning threshold of coal spontaneous combustion can be expressed by the following mathematical formula: R0={[O2]>18% union [CO]>50ppm} intersecting {[O2] belongs to (15%, 18%) union [CO]>100ppm} intersecting {[O2] belongs to (12%,15%) union [CO]>150ppm} intersecting {[O2]<12% union [CO]>200ppm}; and issuing a warning and taking measures according to different thresholds. The spontaneous combustion process of coal can be indicated more accurately and sensitively, and higher preventability is achieved.

The invention discloses a mined-out subsidence area soil horizontal deformation monitoring method and a system thereof. A fiber grating sensing net a (3) real-timely monitors soil horizontal deformation above a pipeline a (2). Collected data is through an optical cable a (5), an optical switch (6), and then is demodulated and transmitted by a fiber grating demodulation device (7) to a lower computer (8). The lower computer (8) calls a self-written program, controls the optical switch (6) and the fiber grating demodulation device (7), and collects the data and carries out pretreatment to the data. The pretreated data is transmitted through a GPRS communication module a (9) and is received by the GPRS communication module b (10) to an upper computer (11). The upper computer (11) analyzes the soil horizontal deformation data and determines a stabilization state of the mined-out subsidence area soil and a safety state of the pipeline according to changes of a monitoring curve and a monitoring value.

The invention relates to a method and system for remote sensing, monitoring and pre-warning of a farmland fire. The method for remote sensing, monitoring and pre-warning of a farmland fire comprises following steps: the area of mature crops in a farmland is obtained according to satellite remote sensing data; the times of fire within a certain time period in the farmland and the burnt area of each fire are obtained according to the area of mature crops; the farmland fire intensity is calculated according to the times of fire in the farmland and the burnt area of each fire; the possibility of a fire is determined according to the farmland fire intensity and the canopy water content of crops; if the possibility of a fire exceeds a preset threshold, a farmland fire pre-warning is sent out. The method is based on statistics of fire intensity for many years and remote sensing inversion of crop canopy water content in a monitored region to give fire pre-warning. The method for monitoring the times of fire and area of a fire is easy and highly precise, and the efficiency of pre-warning is high.

The invention discloses a mountain flood disaster danger dynamic early warning method. Numerical simulation is performed on the mountain flood along the movement by using a two-dimensional diving waveequation on the basis of the real-time data of a watershed investigation and monitoring system, the mountain flood coverage range and coverage depth are predicted on the DEM grid level, and the extent of damage to the affected body, and the safe escape route and other information are analyzed through superposition of the affected body data and timely released to the people of the watershed. The invention also discloses a mountain flood disaster fine graded monitoring and early warning method. The monitoring information influencing the elements of the mountain flood disaster is omnibearingly acquired and analyzed, the process of whole mountain flood formation, occurrence and evolution is seen as the highly dynamic process to be predicted and monitored, and fine early warning of the mountain flood disaster is gradually completed by four steps of prediction before the mountain flood disaster, early warning of the disaster, sending warning of the disaster and dynamic early warning of thedanger. Compared with the present one-step and one-indicator monitoring and early warning technology, the dynamic characteristics and law of the mountain flood disaster are fully combined by the method so as to be more scientific and higher in disaster reduction practicality.

The invention discloses a method and a device for precisely sending a message according to a region. The method comprises the following steps of: 100, collecting signaling data occurring in a mobile network by a mobile user, carrying out preprocessing on the signaling data to generate an original message, and then compounding a call record (CDR); 101, obtaining behavior information of the mobile user from the CDR, meanwhile obtaining the position information of the mobile user when a communication behavior occurs, and finally storing identification information and current position information of the mobile user in a memory in real time; 102, according to position information included in a message distribution area, extracting a user number which appears lately in the region from the memory to generate a message; and 103, submitting a generated message into a message center, and carrying out the sending of the message. By the adoption of the method, the regional precise sending of the message is guaranteed, the mobile user in a regional range is enabled to universally receive the content of the message, and disturbance for a user out of the regional range is prevented.

The present invention discloses a sudden loess landslide early warning method and an application thereof, belonging to the technical field of landslide prevention and control engineering. The method comprises the following steps of: a, preprocessing of deformation monitoring data; b, determination of a multi-stage deformation rate threshold Vt; c, determination of a deformation rate increment [Delta]V; d, division of different landslide deformation rate curve features; and e, integration early warning through combination of the multi-stage deformation rate threshold Vt and the deformation rateincrement [Delta]V. The multi-stage deformation rate threshold is arranged to determine whether the landslide generate a large deformation or not in advance and track a deformation development trendin real time based on the deformation rate increment, and therefore, the combination thereof achieves total-process early warning of the sudden loess landslide, the early warning accuracy and the early warning efficiency are greatly improved, and the disaster prevention applicability is good.

A disaster monitoring and pre-warning system comprises a disaster informing system, peer-to-peer wireless communication devices, a monitoring host and a pre-warning message issuing host. The disaster informing system transfers at least one first disaster information. The peer-to-peer wireless communication devices sense at least one disaster event to generate at least one second disaster information. The at least one second disaster information is transferred by a peer-to-peer technology. The monitoring host receives the at least one first disaster information and the at least one second disaster information to generate a first pre-warning information. The pre-warning message issuing host issues the first pre-warning information.

The present invention discloses a mud-rock flow disaster dangerous case dynamic early warning method. On the basis of river basin investigation and monitoring system real-time data, a two-dimensionaldiving wave equation is employed to perform numerical simulation of mud-rock flow motion along a way, a submerging range and a submerging depth of the mud-rock flow is predicted on a DEM grid level, hazard-affected body data is superimposed to analyze information of degree, affected by the hazard, of a hazard-affected body, safe evacuation lines and the like, and the information is timely published to the population in the basin. The present invention further discloses a mud-rock flow disaster dangerous case dynamic early warning method. Monitoring information influencing mud-rock flow disaster factors is comprehensively obtained and analyzed to allow formation, generation and evolution processes of the whole mud-rock flow as a highly dynamic process to perform prediction and monitoring and perform fine early warning of the mud-rock flow disaster through four steps consisting of pre-disaster prediction, disaster-coming early warning, disaster generation early warning and dangerous casedynamic early warning. Compared to a current one-step and one-index monitoring early warning technology, the method provided by the invention fully combines dynamics features and rules of the mud-rock flow disaster, and is more scientific and higher disaster reduction practicality.

The invention discloses a system for monitoring an oil-gas pipeline in a mining subsidence area and a constructing method thereof. The system comprises a pipe body strain monitoring device, a pipe-soil relative displacement monitoring device and a mining subsidence area horizontal deformation monitoring device; a fiber grating strain sensor a (3) and a pipe-soil relative displacement sensor a (4)are arranged on the monitoring section of an oil-gas pipeline a (2) of a mining subsidence area (1); sensors on every section are connected in series by fusing, and are connected with an optical cable a (7) through a fiber junction box a (6); a fiber grating sensing network a (5) is arranged on the top of the pipeline a (2), and is connected with the optical cable a (7) through the fiber junctionbox a (6); the optical cable a (7) is connected with an optical switch (8); the optical switch (8) is connected with a fiber grating demodulator (9); the demodulator (9) is connected with a lower computer (10); the output of the lower computer (10) is connected with a wireless communication module a (11); and the output of a wireless communication module b (12) is connected with an upper computer(13).

The invention discloses a system for monitoring an oil-gas pipeline in a mining subsidence area based on a fiber grating sensing technology. The system comprises a pipe body strain monitoring device, a pipe-soil relative displacement monitoring device and a mining subsidence area horizontal deformation monitoring device; a fiber grating strain sensor a (3) and a pipe-soil relative displacement sensor a (4) are arranged on the monitoring section of an oil-gas pipeline a (2) of a mining subsidence area (1); sensors on every section are connected in series by fusing, and are connected with an optical cable a (7) through a fiber junction box a (6); the optical cable a (7) is connected with an optical switch (8); the optical switch (8) is connected with a fiber grating demodulator (9); the demodulator (9) is connected with a lower computer (10); data preprocessed with the lower computer (10) are transmitted through a wireless communication module a (11), received by a wireless communication module b (12) and transmitted to an upper computer (13); and a fiber grating sensing network a (5) is used for monitoring soil body horizontal displacement in real time and transmitting data to the upper computer (13).

The invention discloses a vehicle driving risk early warning method and device. The method comprises the following steps of acquiring vehicle data, calculating a current vehicle collision angle and other vehicle collision angles according to the vehicle data; according to the current vehicle collision angle, and other vehicle collision angle and the preset criterion, confirming whether the currentvehicle is in risk of being in collision with other vehicles or not; calculating the risk grade of the collision for a simulation in risk of collision; and carrying out risk early warning according to the risk grade of the collision. According to the method and the device, the vehicle driving risk is analyzed in real time through a preset early warning judgment algorithm, wherein the operation processing amount required by the preset early warning judgment algorithm is small, so that the early warning efficiency is improved; meanwhile, the method and the system are simple in structure, the expandability is high, and the problem that an existing risk early warning system which depends on machine vision is easily interfered by the outside, and the data processing capacity is large is solved; and the accuracy and the instantaneity of early warning are effectively guaranteed.

The invention discloses intelligent on-board equipment and a communication method thereof. An OBD (On-Board Diagnostic) device transmits real-time diagnostic information of a vehicle to a cloud serverthrough an on-board intelligent terminal, and corresponding diagnosis is provided by the cloud server and corresponding service merchant information is pushed to the on-board intelligent terminal. The method of information pushing based on the OBD information ensures pertinence and continuity of vehicle maintenance and service pushing. According to the equipment, all-personnel participation of supervision and early warning of vehicle conditions, road conditions and driving conditions is also realized through adding an early-warning voting module, and an accident occurrence rate is reduced. The invention also discloses the communication method of the intelligent on-board equipment, false-report and report-missing danger cases are avoided to the greatest extent through carrying out voting and statistical analysis on abnormal information, and danger can be avoided in time; and through presetting an abnormal-information list, early warning can also be quickly carried out when an abnormality occurs, and early-warning efficiency is further improved.

The invention discloses a multi-disaster monitoring, early warning and emergency command system, and the system comprises a monitoring system which is used for monitoring and collecting the data of each monitoring point; a transmission system used for transmitting data of each monitoring point; a disaster analysis system used for carrying out analysis operation on the received data according to adisaster model to generate disaster early warning information; a refined meteorological analysis system used for analyzing meteorological historical data and meteorological forecast data of monitoringpoints, lines and planes; a civil air defense patrol reporting system used for sending disaster information; a early warning system used for issuing disaster early warning information in a preset early warning mode according to the disaster early warning information; and an emergency command system used for performing real-time command according to the disaster early warning information. According to the invention, meteorological and geological disasters, river water conservancy, urban traffic, fire protection, mine enterprise safety supervision, hazardous chemical enterprise safety supervision and other information are communicated, one-stop management is realized, and the early warning efficiency is improved; and life and property losses caused by disasters are effectively reduced and avoided.

The invention discloses a disease early-warning method, a disease early-warning device and a computer-readable storage medium, wherein the disease early-warning method, the disease early-warning device and the computer-readable storage medium are applied to the field of knowledge relation analysis, wherein the method comprises the steps of acquiring a knowledge atlas and high-frequency seasonal diseases, wherein medical data generated in diagnosis of a plurality of patients are stored in the knowledge atlas; extracting morbidity data of the high-frequency seasonal disease in the knowledge atlas, wherein the morbidity data comprise morbidity time of all patients in affecting the high-frequency seasonal disease; determining the morbidity time period and morbidity scale of the high-frequencyseasonal disease according to the morbidity data of the high-frequency seasonal disease; and reminding the disease early-warning information, wherein the disease early-warning information comprises the morbidity time period and the morbidity scale of the high-frequency seasonal disease. The disease early-warning method, the disease early-warning device and the computer-readable storage medium predict the morbidity time period and the morbidity scale of the high-frequency seasonal disease, thereby warning management personnel to perform corresponding prevention and medicament preparation, thereby supplying a quick and high-efficiency disease early-warning method.

The invention is applicable to the technical field of wearable electronic equipment, and provides an early warning signal generation method and device. The method includes the steps that a plurality of first temperature sensors are controlled to collect a first temperature value of a first foot area, and a plurality of second temperature sensors are controlled to collect a second temperature valueof a second foot area; the first temperature sensors and the second temperature sensors are fixed to a sock body of a first sock and a sock body of a second sock respectively, and the first foot areaand the second foot area are in mirror symmetry; the collected temperature values are recognized and processed so as to delete abnormal data values in the collected temperature values; on the basis of the temperature values obtained after the abnormal data values are deleted, the difference between the first temperature average value of the first foot area and the second temperature average valueof the second foot area is calculated; a first early warning signal is generated if the difference is larger than a preset threshold value. According to the method, the measurement accuracy of foot temperature data is improved, and automatic identification of foot temperature anomaly is achieved so that a user can obtain feedback information in real time, and the early warning efficiency is improved.

The invention relates to the relative technical filed of integrated circuits, in particular to an electro-migration early warning circuit of an integrated circuit. The electro-migration early warning circuit of the integrated circuit comprises a current output module and one piece or more than one piece of electric conduction metal, wherein the current output module and is in electrical connection with a monitoring metal wire, and the electric conduction metal is wrapped by an oxide layer of the integrated circuit and is in electrical insulation with the monitoring metal wire. The current output module comprises at least one current source, the electric conduction metal and an output end of a current monitoring structure are mutually connected in an electrical mode, and the electric conduction metal encircles the monitoring metal wire. The electro-migration early warning circuit of the integrated circuit achieves the early warning to the failed phenomenon caused by short circuit because of electro-migration, and at the same tine, the electro-migration early warning circuit of the integrated circuit also can be additionally provided with a resistance early warning structure, and therefore the electro-migration early warning circuit can monitor whether resistance is increased or a whisker causes the short circuit. Therefore, early warning efficiency of the electro-migration phenomenon is largely improved.

The invention relates to the technical field of computers, and discloses an interface document configuration method, device and equipment and a storage medium, which are used for improving the interface document generation efficiency and the interface document compatibility. The interface document configuration method comprises the steps of obtaining target source code information and a target configuration template; analyzing the target source code information through a preset source code defect analysis tool to obtain an analysis result; when the analysis result is not passed, sending earlywarning information to the terminal; when the analysis result is yes, calling a preset source code analyzer to analyze the target source code information to obtain interface parameter data; obtainingan initial parameter value, and performing data desensitization processing and data encapsulation on the initial parameter value to obtain response data; and performing data combination and document export on the interface parameter data and the response data based on the target configuration template to obtain an interface configuration file. In addition, the invention also relates to a blockchain technology, and the interface parameter data can be stored in the blockchain node.

The invention discloses a thunder fire early warning identification method based on satellite remote sensing. The method comprises the following steps: acquiring a satellite remote sensing signal; performing three-dimensional lightning data analysis based on time difference positioning; performing multi-source remote sensing data fusion analysis; constructing a forest fire monitoring and forecasting model based on deep learning; and performing satellite remote sensing thunder fire early warning and fire point identification early warning. According to the satellite remote sensing-based thunder fire early warning and identification method provided by the invention, the thunder fire early warning and identification method is established based on the satellite remote sensing data, the unmanned precise early warning and identification of the thunder fire based on the data are realized, the reliability is high, the stability is good, and the early warning and monitoring efficiency is high.

The invention discloses a passenger flow monitoring device and method for a metro station. The passenger flow monitoring device comprises a plurality of cameras, a video analysis host, and a monitoring and alarm host, wherein each camera is arranged on a platform of the metro station; all the cameras are electrically connected with the video analysis host; the video analysis host is electrically connected with the monitoring and alarm host; each camera collects picture information of the corresponding platform in a real-time manner, and sends the picture information to the video analysis host; the video analysis host processes the received picture information of the platforms to generate passenger flow density distribution data, and sends the passenger flow density distribution data to the monitoring and alarm host; and the monitoring and alarm host analyzes the received passenger flow density distribution data to generate passenger flow guidance information, and outputs the passenger flow guidance information. The device and method provided by the invention has the advantages that monitoring is more efficient, the monitoring error rate is reduced, the passenger flow guidance and early warning efficiencies are improved, and better passenger experience is achieved.

The embodiment of the invention provides a mountain torrent disaster early warning method and device, a server and a storage medium. By monitoring data acquisition, calibrating the initial hydrological forecasting model according to the standard water flow in the monitoring data; taking the calibrated model as a target hydrological forecasting model; carrying out flood forecasting calculation on the monitoring data according to the target hydrological forecasting model; and performing evolution overflow calculation on the prediction calculation result according to the evolution overflow modelto obtain an overflow flooding analysis result of the current monitoring area, and further determining whether to generate early warning information for alarming the current monitoring area accordingto the overflow flooding analysis result. Furthermore, the monitoring data is analyzed by combining the target hydrological forecasting model and the evolution overflow model; the purposes of integrated data collection, data analysis and alarming are achieved, the effects of improving mountain torrent disaster early warning and reducing the labor cost are achieved, meanwhile, the early warning precision and the early warning efficiency are improved, and the requirement for accurate and efficient early warning of mountain torrent disasters is met.

The invention discloses a vehicle early warning method, device and equipment and a storage medium. The method comprises the steps: obtaining road end monitoring data which is real-time monitoring data of a road end sensor for a current road; based on the road end monitoring data, carrying out early warning scene recognition on the vehicle on the current road to obtain an early warning scene recognition result, wherein the early warning scene recognition result comprises a target vehicle and an early warning target; sending the early warning target to a vehicle-mounted terminal of the target vehicle, so that the vehicle-mounted terminal obtains a real-time early warning video, wherein the real-time early warning video is video data including mark information of the early warning target; and outputting the real-time early warning video to a vehicle end display device of the target vehicle. By using the technical scheme provided by the invention, vehicle-road data interaction can be realized, the vehicle end acquires surrounding sensing information in real time, drivers and passengers are helped to quickly identify dangerous targets through the early warning video, and the early warning efficiency and accuracy are improved.