7316 results about "Early warning system" patented technology

The invention relates to an artificial intelligence early warning system. The system comprises an intelligent Internet of Things and risk factor data acquisition system (100), and a risk factor management system (200), a cloud computing device (300), a cloud storage device (400), a cloud database (500), and an artificial intelligence early warning operation system (600), an artificial intelligenceearly warning server (700), an internet + distributed early warning police booth (800), a five-level artificial intelligence early warning system (900), a four-level artificial intelligence early warning system (1000), a three-level artificial intelligence early warning system (1100), a two-level artificial intelligence early warning system (1200) and a one-level artificial intelligence early warning system (1300). The artificial intelligence early warning system of the present invention collects, compares, analyzes, deduces, evaluates the risk factors, and carries out the cloud computing, cloud storage, graded alarming and prevention and control, so that all-weather 24-hour monitoring on monitoring points around the police box is achieved, a user can share information, the utilization rate of information resources is increased, and the safety guarantee is increased for maintaining the stability of the borderlands.

The invention discloses an early warning method and a device for vehicle collision. The early warning method is characterized in that the method comprises the following steps: after a vehicle is fired, colliding an early warning system to begin initializing each parameter, using an OBD information collection module, a sensor information collection module and a GPS information collection module to collect information of the vehicle, using an inter-vehicle information exchange module to collect peripheral vehicle information, sending the information of the vehicle to the peripheral vehicles, calculating individualized collision probability according to self state of a driver, and warning the driver; and the device consists of the OBD information collection module, the sensor information collection module, the GPS information collection module, the inter-vehicle information exchange module, an information exchange module in the vehicles, a collision detection module and a vehicle collision warning module. Each module exchanges information in the vehicle through a wireless local area network in the vehicle, does not change an electric line of the vehicle and does not increase wire harness inside the vehicle, and can effectively reduce occurrence of traffic accidents, so as to reduce casualties.

An early warning system and method for generating an alert regarding a potential attack on a client device is provided for based on real-time analysis. The early warning system and method generally comprise receiving data associated with an attack alert, wherein the attack alert corresponds to an electrical signal that indicates detection of a malware attack from a remote source. The received data is analyzed using an attack-specific engine that is configured to generate an attack-specific result. An attack value is computed based on the attack-specific result and a consideration of potential attack targets, wherein the attack value is compared to a threshold value so as to determine whether or not to generate an early warning alert. An early warning alert is generated when the attack value matches or exceeds the threshold value.

The invention discloses an area road network traffic safety situation early warning system and a method thereof. The system comprises monitoring equipment, a data transmission system, a data process system and an early warning system. The method comprises the following steps: acquiring data information of road traffic, meteorology, illegal behaviors, and accidents through the monitoring equipment; sending the data information through the data transmission system; carrying out a multiple heterogeneous treatment on the acquired data information through the data process system, and merging data of the same kind; analyzing and assessing early warning grade through the early warning system, and determining and publishing a early warning scheme. Thereby road network traffic safety situation information can be comprehensively grasped, and dangerous source existing in the road network can be discovered timely to determine an early warning grade and generate an intelligent early warning countermeasure. Pertinence, instantaneity and validity of a measure of a road traffic management department actively preventing traffic accidents are improved. Technology support is provided in the invention to reduce area road network traffic risk factor and prevent major and extraordinarily serious road traffic accidents.

Multi channel distributed behavioral analysis architecture provides a software solution to the major operational challenges faced with providing an early warning system for impending cyber security events. Most cyber security events are premeditated. However, many current cyber security defense technologies only address the real-time detection of a software vulnerability, the presence of malware (known or unknown “zero day”), anomalies from pre-established data points, or the signature of an active security event. The system and method of the multi channel distributed behavioral analysis architecture introduces a technique which provides the data collection, assessment, and alerting ability prior to the occurrence of an event based on threat actor behavior.

The invention relates to a vehicle anti-collision early warning system based on a vehicle-mounted sensing network. The vehicle anti-collision early warning system comprises an subject vehicle (SV) information module, a self-learning functional module, an information memory module, a vehicle collision judging module, an anti-collision early warning device module, a DSRC (Dedicated Short Range Communications) vehicle-vehicle communication module and a neighborhood vehicle (NV) anti-collision early warning system, wherein the SV information module consists of an information acquiring and processing module and a module including the ID (Identity) and the size fixed information of a vehicle; the information acquiring and processing module is used for exchanging data with the anti-collision early warning device module through the self-learning functional module and the vehicle collision judging module; the module including the ID (Identity) and size fixed information of the vehicle is used for exchanging data with the anti-collision early warning device module through the information memory module and the vehicle anti-collision judging module; and the information memory module is in DSRC wireless communication with the NV anti-collision early warning system of a surrounding vehicle through the DSRC vehicle-vehicle communication module. By adopting the vehicle anti-collision early warning system, the vehicle running state can be forecast, and the effectiveness and suitability of the anti-collision early warning system are enhanced.

The invention discloses a personal image designing and product recommendation method based on online shopping. The method comprises the steps of personal data collecting, personal figure simulation, product simulation, simulated fitting, personal image designing, specific circumstance image designing, related matching suggestion and commodity recommendation, early purchase warning and social sharing. The method has universality and transportability and aims at different terminals and devices, the terminals and the devices are convenient to carry, and users are served everywhere. The image designing can be carried out according to different occasions and different circumstances of the users. The strong individualized costume matching function and the intelligent commodity recommendation function are achieved. The large-scale data analyzing and mining function is achieved. The interests and hobbies of the users are learned continuously, the analysis of the behavior of the users is carried out, and intimate service is continuously provided for the users.

A detection and monitoring method and system which makes it possible to detect the presence of moisture problems when they manifest as abnormal humidity in one or more discrete ventilation zones within a building envelope. The abnormal humidity can then be investigated and resolved or mitigated to minimize the potential for building damage or adverse occupant health effects occur. The present invention provides an early warning system that will alert personnel of the occurrence of a moisture problem.

The invention relates to a smart dust type transportation sensor, a signal control network and an information transmission system thereof, which comprises at least one of smart dust traffic state sensor nodes and control / relay nodes which are installed on a traffic lane, at roadside or in a place and at the proper position of the space thereof, at least one base station installed at the roadside or the proper position or an upper-layer device provided with the base station, wherein, the smart dust sensor nodes comprise at least one traffic state sensor element or traffic state acquisition component, a smart dust component and a group of local power supply devices for supplying power for the electric circuit of the nodes, the smart dust control / relay nodes comprise a smart dust component and a group of local power supply devices for supplying power for the electric circuit of the nodes, and the base station comprises a gateway and a smart dust component. The invention can be used for constructing various smart dust type intelligent transportation systems, anti-theft systems, security monitoring systems and early-warning systems.

The invention provides a lane departure control system and a lane departure control method. The lane departure control system detects whether vehicles depart from lanes or not based on a grid coordinate central axis and the distance among the vehicles and lane lines and detects whether obstacles exist within adjacent lane lines or not and whether vehicles come posterolaterally or not by means of digital image processing so as to provide early warning for safety driving. According to the lane departure control system and the lane departure control method, vehicle body information is acquired in real time, and different lane line types, different vehicle speeds and whether drivers have intention to change the lanes or not are specifically analyzed; when the vehicles are detected to have a tendency to depart from the lanes, an early warning system sends out a warning voice signal and a visual signal to remind the drivers of correcting departure of the vehicles or to assist the vehicles to keep the normal driving state after the vehicles change the lanes safely; and when the vehicles depart without being corrected, a vehicle body controller is started to perform safety driving assistance, so that driving safety of the drivers is effectively guaranteed, and accidents are reduced.

The invention discloses an actually-enhanced driver-assisted early warning system, which comprises a vehicle camera unit, a central processor unit and a head-up display unit. The vehicle camera unit comprises a front camera for shooting circumstance of a road ahead and two face cameras for shooting head information of a driver, wherein the front camera is arranged in the front of a middle-rear view mirror; the face cameras are arranged in an instrument panel symmetrically; and the three cameras are connected with the central processor unit. The central processor unit is used for identifying the specific locations of external risk factors according to the specific image contents of the front camera, and marking the locations in the images. The head-up display unit is arranged in the front of a steering wheel and below a front windshield and is used for projecting modified identification information to the front windshield together with warning prompt patterns after receiving an early warning command. The actually-enhanced driver-assisted early warning system can effectively avoid the distraction of the driver so as to improve an early warning effect.

The invention relates to an early warning method for preventing rear-end collision with a rearward vehicle and an early warning system thereof, wherein the method comprises the following steps: 1) arranging an early warning system for preventing rear-end collision with the rearward vehicle, which comprises an information acquisition unit, a system control unit comprising a singlechip as well as an early warning execution unit; wherein, an early warning module for preventing rear-end collision with the rearward vehicle is prearranged inside the singlechip, a collision warning range and a formula calculating the collision time of the vehicles are prearranged inside the early warning module for preventing rear-end collision with the rearward vehicle; 2) acquiring the distance between the rearward vehicle and own vehicle and relative speed information and acquiring own speed information; 3) calculating time of collision TTC and a warning time threshold of collision TTC_W of the rearward vehicle and own vehicle; 4) generating a control instruction in accordance with the difference value between the calculated time threshold of collision TTC and the warning time threshold of collision TTC_W of the rearward vehicle and own vehicle as well as the prearranged collision warning range; 5) sending corresponding warning information according to the control instruction. The invention can real-timely and accurately monitor the relative motion state between own vehicle and the rear vehicle that travels in the same traffic lane, thus effectually preventing the rear-end collision of the vehicles that traveling at high speed.

The invention discloses a back sight image cognition based on-vehicle blind area early warning system and a method, wherein the system is composed of cameras (1 and 2) mounted on a rearview mirror to monitor the blind area, a digital signal processor (DSP), a sound prompting device, a power source and a plurality of data cables. The system reads the automobile travelling signal through the data cables, acquires the road surface image of the blind area (4 and 5) by adopting the rearview cameras, the processor processes the image, detects the automobile (3) in the blind area, analyzes the travelling state of the automobile, and realizes the multi-stage tracking for the automobile, when the driver intends to switch lanes, if another automobile in the blind area is not far from the automobile, then the driver is warned by the sound prompting device, so that the danger of collision during switching lanes is avoided. The back sight image cognition based on-vehicle blind area early warning system and the method are applied to the active safety driving, and has the advantages of simple system configuration, low cost, high safety performance, good real-time performance and complex environment adaptability.

The invention discloses VANET-based early-warning system and early-warning method for driving safety in an expressway, and relates to an early-warning system and an early-warning method for driving safety in an expressway, for realizing real-time and effective safety early-warning on running vehicles. The invention designs a Vehicle ad-hoc network-based early-warning vehicle-mounted system for driving safety in an expressway. By virtue of the system, the different levels of early-warning prompts of the current driving safety of vehicles can be given according to the weather / road conditions (visibility, road slippery degree and the like), the current running state (real-time position and real-time speed) of a vehicle and the running states of 'neighbour' vehicles in a certain space range around the vehicle. On the basis of VANET, the system enables the vehicles to carry put wireless ad-hoc networking in a certain space range and share in-network vehicle running state information, and automatically generates safety early-warning information for every vehicle in the network, thus improving the driving safety of the vehicles on a road. The system and the method disclosed by the invention are applicable to a driving process in an expressway.

The invention provides a large-range fire disaster analyzing and early warning system which comprises a fire disaster characteristic database, a video capture module, a temperature collection module, a video quality improvement module, a fire disaster characteristic extraction module, a fire disaster characteristic identification module, a fire disaster management and control trigger rule judgment module and a fire disaster real-time management and control platform, wherein the fire disaster characteristic database comprises a smoke / flame image model; the video capture module is used for capturing digital video images within a large range; the temperature collection module is used for collecting temperature information through a thermal imaging product; the video quality improvement module is used for carrying out quality improvement on the video image; the fire disaster characteristic extraction module is used for carrying out foreground extraction, target matching and target classification on a video sequence; the fire disaster characteristic identification module is used for comparing and identifying a video object with the fire disaster characteristic database according to parameters set by a user; the fire disaster management and control trigger rule judgment module is used for judging whether a rule is broken or not according to the rule preset by the user by combining video characteristics and temperature values, and if so, sending out abnormal information; and the fire disaster real-time management and control platform is used for receiving a video analysis result and issuing a management and control order according to the analysis result.

The invention relates to a front small-region object recognition and vehicle early warning method, and belongs to technical field of early warning for collision in front of vehicles. The front small-region object recognition and vehicle early warning method specifically comprises the steps that an image of a target to be recognized in front of a vehicle is acquired, and a region of interest (ROI)image is obtained; image preprocessing is performed on the obtained region of interest image, the preprocessed region of interest image is inputted into an improved YOLO convolutional network structure model to perform target recognition, and a target regression frame and a target category are outputted; the recognition result is inputted into a vehicle early warning system, if the target regression frame is located beyond the range of a vehicle driving route or the target is recognized to be of a non-dangerous category, the target is marked as a non-dangerous target, and the vehicle does notperform early warning; and if the target regression frame is located within the vehicle driving route and the recognized object belongs to a dangerous category or the object cannot be recognized but has certain speed features, the target is marked as a dangerous target, the vehicle performs early warning to remind a driver to pay attention so as to avoid occurrence of an accident.

The invention discloses a grid meteorological disaster monitoring and early warning system which comprises a data collection subsystem, a data analysis subsystem, a data storage subsystem and a disaster weather comprehensive display subsystem, wherein the data collection subsystem is responsible for completing a collection task of original meteorological monitoring data. The original meteorological monitoring data is composed of automatic meteorological station data, Doppler radar data, meteorological satellite data and value forecasting data. The data analysis subsystem is responsible for analysis of original meteorological data, cutting a satellite cloud picture, and finally storing processed data into the data storage subsystem. The data storage subsystem is responsible for storing original data of data of various stages and types, including original data, a relational data, a vector data and a picture, the original data is received from a meteorological department, the relational data is analyzed by the data analysis subsystem, the vector data is analyzed by the data analysis subsystem, and the picture is processed by the data analysis subsystem. The disaster weather comprehensive display subsystem is responsible for system function display. The grid meteorological disaster monitoring and early warning system can accurately position grid facilities which are affected by disaster weather.

The invention relates to an automobile lane changing early-warning method and a lane changing early-warning system. The method comprises the steps of (1) arranging the lane changing early-warning system which comprises an information collecting unit, a system control unit and an early-warning execution unit, wherein a critical safety distance computing module and an early-warning decision module are arranged in the system control unit, and a computing formula for critical safety distance which is right suitable for lane changing and an early-warning decision condition are contained; (2) collecting information of distance between the closest target automobiles in a primary lane where a user automobile is located and a lane-changing target lane in a given front-back range and the user automobile and relative speed information and speed information of the user automobile; (3) computing the critical safety distance suitable for lane changing and comparing actual distance and computed critical safety distance and generating an early-warning control instruction; and (4) sending corresponding alarming information according to the early-warning control instruction. By means of the automobile lane changing early-warning method and the lane changing early-warning system, surrounding driving environment of the user automobile can be detected comprehensively, lane-changing safety under different working conditions can be judged, and collision accidents in the lane changing process can be effectively prevented.

The invention relates to the field of coal mine safety technique, specifically to a down-hole coal and gas outburst hazard early warning system and early warning method. The coal and gas outburst synthesized early-warning system, uses the existing local area network to connect a synthesized early-warning data server, an early-warning data management system and the existing coal mine safety monitoring system; analyzes the coal and gas outburst early-warning data in the synthesized early-warning data server by an outburst early-warning module; and emits early-warning information based on the analyzed result. The inventive coal and gas outburst synthesized early warning system and early warning method can perform centralized management and comprehensive analysis of the geological structure, coal seam occurrence, gas occurrence, mining production, daily forecast indicators, outburst forecast, gas emission and other security information that originally scatter in various functional sections of coal mine on the geographical information system GIS platform, integrates the existing resources, improves the accuracy of early warning, so that the early warning is both real-time and forward-looking, and can effectively prevent the occurrence of coal and gas outburst in coal mine.

The invention provides an on-board track traffic passenger flow transport capability and a running safety intelligent monitoring and pre-warning system, which is characterized in that the system comprises at least one or one group of vehicle running state gaining intelligent sensing device(s) in a passenger flow transport capability / scene image sensor, a mechanical vibration / noise sensor, a wheel track state and vehicle chassis image sensor and a road condition image information intelligent sensor, at least a set of train monitoring and pre-warning controllers which can carry out the network assembly of the vehicle running state gaining intelligent sensing devices, carry out information communication with all vehicle running state gaining intelligent sensing devices, carry out data memory and data integration, analysis and processing, achieve system function arrangement, operation, pre-warning and control and carry out information communication with earthwork equipments; all intelligent sensing devices and the train monitoring and pre-warning controllers are connected with each other by communication buses which are matched with each other. The system of the invention has the advantages of multi-function, high intelligent informatization level, high performance / price ratio, high reliability, etc., is easy to be expended and can be applied under all-weather meteorologic conditions.

The invention designs a lithium ion battery thermal runaway early warning system and an early warning method. The early warning system comprises various sensors, a battery management system, a warningdevice and an automatic emergency fire extinguishing device. The sensors comprise an ultrasonic sensor, a temperature sensor, a voltage sensor and a smoke sensor. The ultrasonic sensor can reflect abattery internal gas state characteristic, so prejudgment and diagnosis are carried out on battery thermal safety in a thermal runaway risk emerging early phase timely and early warning is rapid and efficient. The battery management system carries out data analysis based on various sensor combined detection, compares a plurality of parameters with set thresholds, sends out different levels of early warning signals and takes different control policies. A safety accident risk resulting from thermal runaway is reduced, and personnel injury is reduced.

The invention discloses a deep convolutional neural network-based abnormal crowd behavior visual detection and analysis early warning system. The system comprises a camera mounted at a monitoring target facility, a security prevention cloud server and an abnormal crowd behavior visual detection and analysis early warning system. In the system, various human body objects in the target facility areextracted through a deep convolutional neural network technology; then motion states of human bodies are calculated, identified and judged by using an optical flow method; different states of the human body objects are subjected to clustering and crowd modeling; further crowd objects are subjected to density calculation and danger index calculation; and finally according to different combinationsof crowd density, motion vector values and duration quantitative index data, various abnormal crowd behaviors are identified and judged, and according to the states of the abnormal crowd behaviors, corresponding crowd gathering management control policies are enabled. The deep convolutional neural network-based abnormal crowd behavior visual detection and analysis early warning system provided bythe invention is unlimited in scale, relatively high in precision and relatively good in robustness, and is based on a deep convolutional neural network.

The present invention discloses a forest fire alarm system based on infrared thermal imaging technology comprising: an infrared camera mounted at an elevated location of the land area to be monitored and used to capture infrared thermal images of a monitored area, said camera comprising: a frontal temperature measurement and alarm module for calculating the alarm temperature value by using a temperature monitoring mathematical model, and for transmitting an excessive temperature alarm signal when there are abnormalities in said area; a video conversion device coupled to the infrared camera for converting an infrared thermal image analog signal outputted by the camera into an infrared digital signal, and for receiving from the camera said alarm signal and converting the alarm signal into a digital signal; a monitoring computer for generating and transmitting an infrared camera control signal, and for receiving, analyzing and processing the infrared digital signal to ascertain the location in the monitored area that triggered the infrared camera alarm, and for automatically generating a solution and reporting to the control center.

An early warning system for a tractor operator engaged in towing or pushing an aircraft includes two ultrasonic sensors that are used to create a detection area in which the aircraft should be present when the steering angle is well within a safe range. When one of the detectors fails to detect the presence of the aircraft, then the operator is alerted, before over steering can occur, in order that corrective action can be undertaken. Accordingly, complex distance-measuring algorithms can be avoided as can the requirement that an aircraft fuselage have a specially modified detection region.

The invention discloses a comprehensive monitoring and early warning system based on meteorology and a power grid GIS and a method thereof. The system comprises a data layer and an application layer. The data layer consists of a meteorological database, a power grid GIS database, and a production and operation database. The application layer includes a meteorological monitoring module, a meteorological early warning module, a power grid weather module, an information display module, and an auxiliary decision-making module. The meteorological database, the power grid GIS database, and the production and operation database carry out communication mutually; and the meteorological monitoring module, the meteorological early warning module, the power grid weather module, the information display module, and the auxiliary decision-making module carry out communication with the meteorological database, the power grid GIS database, and the production and operation database respectively. According to the invention, meteorological monitoring information like the temperature, wind direction, and wind speed and the like of important power equipment like a transformer substation, a transmission and transformation line, and a tower can be gotten in real time; and visual meteorological real-time data can be provided for the power grid. Meanwhile, prediction and disaster early warning information of the typhoon and thunder and the like can be provided every 12 hours in the next seven days.

A lateral flow device for testing a bodily fluid, such as urine, blood, mucous, saliva, etc., is provided. The lateral flow device is configured to be attached to an absorbent article via an attachment mechanism located on the lateral flow device or the absorbent article. The lateral flow device includes a chromatographic medium (e.g., porous membrane) that defines a detection zone that provides a signal indicative of the presence or absence of the analyte. The device may also include a control zone that provides a signal indicative of whether a sufficient amount of bodily fluid has been provided and tested. Regardless of its specific configuration, the lateral flow device is configured to be attached onto the absorbent article to provide a user or caregiver with rapid information about a health condition. For example, the device may be attached onto a diaper to provide information about the presence of enzymes or other compounds often encountered with a patient having a urinary tract infection. This information may provide an early warning system to allow the user or caregiver to seek additional testing and / or treatment. Alternatively, semi-quantitative or quantitative results may be derived from the test.

The invention discloses a device detection and early fault warning system and method in a cloud computing environment. The system comprises a real-time monitoring module, a monitoring information presentation module, an early fault warning module and a warning module. The method comprises the following steps that firstly, real-time monitoring is conducted, wherein real-time information collection is conducted, and the real-time information is aggregated and presented; secondly, early fault warning analysis is conducted, wherein the collected information is subjected to early fault warning analysis; thirdly, a warning mechanism is triggered, wherein early warning information is classified. The device detection and early fault warning system and method can support protocols, autonomously and controllably select detecting indexes, adapt to different monitoring modes, customizing warning triggering conditions, extending the number of monitoring devices on a large scale and the like according to the types and the number of devices in a cloud computing data center, collection, monitoring, warning and fault positioning can be intensively conducted in a unified system, and the operation and maintenance efficiency is effectively improved.

The invention relates to an ocean environment monitoring and early warning system, especially relating to an offshore ocean environment real-time monitoring and calamity early warning system based on Internet of things and a geographical information system. The invention is aimed at realizing on-line real-time dynamic monitoring and solves a practical problem that present ocean environment monitoring technology and method are only established on a sampling analysis base. A monitoring device of the system acquires a meteorological element, a hydrological element, GPS information and video monitoring information. Communication between monitoring buoys is realized through a wireless sensing network, and communication between a monitoring ship and an offshore monitoring terminal and communication between offshore monitoring terminals are realized through a wireless microwave communication network. The offshore monitoring terminal sends data to a remote monitoring center through a mobile communication network, the monitor center completes data reception, storage and management, and publishes GIS service and Web service information. Early warning information is automatically sent to an intelligent mobile phone terminal through a background management program. A monitoring early warning information platform provides related service information to a user for browse access.

The invention relates to a pedestrian anti-collision early warning system which comprises a vehicle-mounted terminal and a pedestrian smartphone, wireless communication is conducted between the vehicle-mounted terminal and the pedestrian smartphone through a wireless communication module, a positioning unit and an alarm unit are embedded in the vehicle-mounted terminal, and a GPS module and an alarm module are embedded in the pedestrian smartphone. The invention further discloses an early warning method of the pedestrian anti-collision early warning system using the smartphoone. According to the pedestrian anti-collision early warning system and the early warning method thereof using the smartphone, through the wireless communication, the vehicle-mounted terminal acquires the longitude and latitude, the speed, the ground heading angle and altitude height information of the pedestrian handheld smartphone in real time, calculates and judges the position relation between a vehicle and a pedestrian according to vehicle positioning information and the motion state, and further judges whether collision danger exists or not, and meanwhile, the vehicle-mounted terminal synchronously sends collision alarm information to the smartphone through the wireless communication,, and achieves alarm to the pedestrian in a sound and image mode.

The invention discloses a highway operation safety-based mobile monitoring and early warning system and method. The system comprises a data acquisition unit, a data storage unit, a data processing unit, an electronic display screen and a wireless communication module, wherein the data acquisition unit, the data storage unit, the electronic display screen and the wireless communication module are all connected with the data processing unit; the system is arranged on a vehicle; and an accumulator is adopted to provide power. The method specifically comprises the following steps of: constructing a basic database; acquiring dynamic data by the data acquisition unit in real time; comparing real-time road condition parameters with safe road condition parameters by the data processing unit to generate early warning information; and transmitting the real-time road condition parameters and the early warning information to a monitoring center by the wireless communication module. According to the system and the method, the defects of the conventional fixed monitoring system and patrol vehicle can be made up, real-time detection and analysis of the highway road condition parameters are effectively improved, and the highway operation safety level and the emergency management capacity are improved.