337results about How to "Early warning is accurate" patented technology

The invention relates to an intelligent mattress warning system. The intelligent mattress warning system comprises a collection device, an anomaly monitoring module, a cloud server, a mobile terminal and an early warning module. The anomaly monitoring module monitors sleep data collected by the collection device, judges the individual type, and judges whether a direct early warning mode or an analysis early warning mode based on the anomaly variation of the sleep data relative to the individual type; the cloud server counts physiological information of at least one individual based on the sleep data collected by the collection device, recognizes a sleep mode, interactively associates the physiological information, the individual type, the sleep mode and/or abnormal data so as to analyze the abnormal state level of a user, and sends corresponding early warning request information to the early warning module and/or the mobile terminal according to the abnormal state; the early warning module sends out corresponding early warning information based on the early warning request information; the mobile terminal sends assistance information to preset assistance personnel and/or an assistance agency based on the early warning information. According to the intelligent mattress alarm system, early warning is conducted based on the individual type, and the early warning is accurate and rapid.

The invention relates to a vehicle intersection collision early warning method. Firstly, the position, direction, track radius, speed and acceleration information of a local vehicle and a target vehicle is collected; the driving trajectories and the collision point of the local vehicle and the target vehicle are calculated according to the position, direction and track radius information, and a collision area is calculated according to the collision point; whether the time from driving into the area to driving out of the collision area of the local vehicle and the time from driving into the collision area to driving out of the collision area of the target vehicle are overlapped or not is judged, when the two times are overlapped, the time T needed by the driving into the collision area of the local vehicle with a current speed and acceleration is calculated, and if the time T is smaller than a set value, the early warning result of alarm is executed. According to the scheme, the problems that a collision position is not accurate, the estimated time deviation of arriving an intersection is large and a lot of wrong alarms exist in the prior art are solved.

The invention relates to a ransomware prevention method and system. The method comprises the steps of creating at least one bait file with the type conforming to a ransomware encryption type and inserting the bait file into an original file sequence of a to-be-protected disk; judging whether the bait file is changed or not; and prohibiting the to-be-protected disk to be subjected to a preset operation when the bait file is changed. According to the method and the system, the bait file with the type conforming to the ransomware encryption type is created by utilizing a characteristic that ransomware traverses disk files necessarily to search for a file type suitable for encryption, and the bait file is put in the original file sequence of the to-be-protected disk; the effects of prewarning the ransomware and protecting other disk files are achieved by monitoring the bait file; the prewarning accuracy is high; a targeted scheme is designed based on an inevitable common behavior of the ransomware, so that known and unknown ransomware can be detected; and the disk space occupied by the created bait file nearly can be ignored.

The scheme of the invention discloses a vehicle assistance driving system based on the infrared thermal imaging and millimeter wave radar technology. The main functions include pedestrian and vehicledetection, image and sound fusion and collision early warning in driving of the vehicle. The early warning system uses the following technical characteristics: the infrared camera and the millimeter wave radar specialized for vehicle-mounted assistance driving, the data acquired by the radar, such as the distance, the direction and the speed and the images acquired by the infrared camera are fusedfor screening and determining the pedestrians or the vehicles, the pedestrian or vehicle characteristics are extracted through the algorithm, finally the result is displayed on the visual interface and multidimensional early warning information including images, numbers and sound is provided.

The invention discloses an automobile rear-end collision prevention early warning method and system. The system comprises a wireless communication dedicated short range communication (DSRC) device arranged at a roadside, and a vehicle-mounted wireless communication device, a data acquisition unit and a vehicle-mounted terminal which are installed on a vehicle, wherein the data acquisition unit is internally provided with a data acquisition module, a GPS module and an acceleration sensor. Through the DSRC device, wireless communication interaction between vehicles and between vehicles and roads is realized. The vehicle-mounted terminal calculates a safety distance between a vehicle and a front vehicle by use of a minimum safety distance model based on vehicle-road cooperation, an actual distance between the vehicle and the front vehicle is calculated through position information, whether a read-end collision risk exists is determined, if the read-end collision risk exists, a risk prompt is displayed on an interface of the vehicle-mounted terminal, and an alarm is given through sound. According to the invention, the cost of the read-end collision prevention early warning system is reduced, and the early warning accuracy is improved. The system has the advantages of low cost, small volume, accurate early warning and the like, thereby being applied to various road conditions.

The invention discloses an athlete athletic injury risk early warning method. On the bases of reference to models provided by foreign scholars and comprehensive analysis of track and field athlete athletic injury factors, a track and field athlete motion injury risk early warning injury factor dynamic chain model is provided, based on the model, corresponding factors are selected from an athlete risk early warning database, and a track and field athlete motion injury risk early warning injury factor dynamic chain quantitative model is established through the analytic hierarchy process. Index data are discretized according to an SOM neutral network discretization method, a decision table is simplified according to a method based on a discernibility matrix in a rough set, an RBF neutral network is established based on the simplified decision table, the RBF neutral network is trained, and finally a correct diagnosis result is acquired. By the adoption of the method, accurate early warning can be conducted on athletic injuries, the athlete athletic injury risk grade is effectively predicted, and treatment and prevention of the athletic injuries are facilitated.

The embodiment of the invention discloses an on-board battery failure early warning system based on Internet of Vehicles. An Internet of Vehicles OBD terminal acquires voltage information of the on-board battery, and the voltage information is transmitted to an Internet of Vehicles server; the Internet of Vehicles server stores the received voltage information and the time for receiving the voltage information; and according to a preset algorithm, the voltage information and the time for receiving the voltage information, whether the on-board battery fails is judged, and when the on-board battery is judged to fail, early warning information is transmitted to a user terminal. The embodiment of the invention also discloses an on-board battery failure early warning method based on the Internet of Vehicles.

A rapid early-warning system based on a phase-sensitive optical time-domain reflectometer includes a disturbance monitoring and positioning module, and a disturbance signal identifying module. The disturbance monitoring and positioning module: a disturbance monitoring part performs difference on the beat signal intensity of a phase-sensitive optical time-domain reflectometer, the rapid early-warning system based on the phase-sensitive optical time-domain reflectometer can monitor the difference of the beat signal intensity all the time, and once the difference of the beat signal intensity changes, it means that a disturbance signal generated by disturbance occurs; and a positioning module can determine position information of a disturbance point through the time difference of an optical time-domain reflectometer echo. The disturbance signal identifying module includes a pre-treatment module, a feature extraction module, a template training module, a pattern classification module, and a post-treatment module; template training means that templates of a plurality of types of signals can be constructed according to features of a series of different types of disturbance signals; the features of the disturbance signals and preset templates of the plurality of types of signals are matched, and the types of the signals can be determined according the matching degrees; and a warning measure or a no-warning measure can be preformed according to a result of pattern classification.

The invention discloses a global earthquake geomagnetic anomaly big data monitoring and early warning system and a monitoring and early warning method based on a mobile Internet. The system provided by the invention comprises a mobile terminal. The mobile terminal is in bidirectional connection with an intermediate layer. The intermediate layer is in bidirectional connection with a main control cloud end. The intermediate layer comprises a distributed cloud computation unit, a distributed mass storage unit, an automatic structured distribution unit and a data filtering unit. The main control cloud end comprises a comprehensive analysis unit, a decision-making unit and a management subsystem. The global earthquake geomagnetic anomaly big data monitoring and early warning method based on the mobile Internet is characterized in that the mobile Internet is used to collect data collected by an intelligent mobile phone or a tablet personal computer, the main control cloud end is used to analyze the data, and a magnetic field abnormal value is obtained and fed back to the intelligent mobile phone or the tablet personal computer for visually displaying a magnetic field abnormity distribution state. Through the analysis of the main control cloud end, a user is enabled to obtain data of great reference value.

The invention discloses a slope landslide test apparatus which includes a model frame system, an axial loading apparatus, an underground water and rainfall simulating system and a servo control system. The model frame system comprises a loading beam, a counter-force beam, a bearing column, a back wall, side walls and a bottom board, is used for producing a model sample and simulating various test status, and is manufactured by jointing steel structures; the axial loading apparatus is in a structure that a speed reducer drives a ball screw pair, wherein a screw rotating nut moves vertically, and a stress sensor is arranged on a front section of the nut. The servo control system is used for controlling the axial loading apparatus to regulate the force; the underground water and rainfall simulating system is used for simulating an underground water seepage test and a rainfall test, system flow rate controlled by adjusting the pressure of the system. The apparatus can be used for carrying out an indoor similarity simulation test to large-scale slope engineering, thereby tracing, analyzing and researching a dynamic evolution process of slope instability.

The invention discloses an on-line biological safety early warning and monitoring method for the water quality. By means of the method, continuous real-time on-line water comprehensive toxicity early warning according with a toxicology mechanism can be achieved. The method comprises the following steps that the absolute motion behavior changing process of a tested aquatic organism in a to-be-monitored water body is monitored by a biological behavior sensor on line in real time and compared with the motion behavior changing process of a same-variety tested aquatic organism in a pollution-free standard water body, normal motion behavior changes are filtered out to obtain the relative motion behavior changing process of the tested aquatic organism in the to-be-monitored water body, and qualitative and/or quantitative evaluation is conducted on the biological safety of the to-be-monitored water body accordingly. The method is particularly suitable for biological safety early warning on sudden pollution accidents of natural water bodies or drinking water sources and has the advantages that early warning is more precise, pollutant concentration early warning can be conducted on the monitored water body, the method is simple, and secondary pollution cannot be caused to the environment of the to-be-monitored water body.

The invention discloses an equipment abrasion state wireless monitoring device based on the internet of things. The equipment abrasion state wireless monitoring device based on the internet of things comprises a wireless monitoring and transmitting module and a wireless monitoring system module. The wireless monitoring and transmitting module comprises a sensor, a signal amplifier, an analog-digital converter, a microprocessor and a wireless transmitter, wherein the sensor, the signal amplifier, the analog-digital converter, the microprocessor and the wireless transmitter are sequentially connected; the wireless monitoring system module comprises a wireless receiver, a level translator and a PC, wherein the wireless receiver, the level translator and the PC are sequentially connected. According to the equipment abrasion state wireless monitoring device based on the internet of things, a wheel bushing of a traction wheel rope groove reaching to an abrasion critical value is diagnosed in advance through the detection of contact fatigue contacts of the surface of the wheel bushing of the traction wheel rope groove, abrasive wear state and oxidative wear degree, the collected abrasion state information is transmitted to an enterprise management platform or relevant management personnel in a wireless transmission mode, working personnel do not need to descend to a well to detect and eliminate potential safety hazards any more, early warning of abrasion situations of the wheel bushing of the mine traction wheel rope groove is accurately and intelligently carried out in real time, and accordingly safety coefficient of the mine traction wheel is greatly increased in the operation process.

The invention provides an early warning method and a device based on the perception of a user. The method comprises: recognizing and integrating collected IP messages of a control panel and a user panel, and obtaining each web browsing operation record for a single user and single business granularity; calculating the quality parameters of the web browsing operation record, wherein the quality parameters comprise the page response success rate, the page response time, the page display integrity, the page display success rate, the page display time and the page downloading speed; determining the target web browsing operation records conforming to filter conditions according to the preset filter conditions, and calculating the assessed value of the quality parameters according to the quality parameters of the target web browsing operation records; detecting whether the assessed value satisfies the preset early warning threshold or not, if yes, sending out an early warning report which comprises the marks of the quality parameters. Through the adoption of the method, the perception of the user can be comprehensively and accurately evaluated, and the early warning based on the perception of the user can be comprehensively and accurately realized.

The invention discloses an integrated landslide monitoring sensor and belongs to the field of sensors. The integrated landslide monitoring sensor solves the problems that an existing landslide monitoring method is long in measuring period, low in accuracy or complex in system and high in cost. The integrated landslide monitoring sensor comprises a shell, a ground auger, an installation guide pipe, a support, a communication circuit, a signal collecting circuit, multiple sets of moisture measuring units and an antenna. The shell is composed of a shell body and an upper cover, the ground auger is arranged at the bottom end of the shell body, and the installation guide pipe is arranged on the inner wall of the shell body. The support is arranged in the shell body from top to bottom. The upper end and the lower end of the support are connected with the upper cover and the ground anger of the shell respectively. The moisture measuring units are dispersed on the support. The signal collecting circuit is arranged on the support. The communication circuit and the antenna are arranged in the upper cover of the shell. The moisture content signal output end of each set of moisture measuring unit is connected with the moisture content signal input end of the signal collecting circuit. The signal collecting circuit sends collected signals through the antenna.

The invention discloses a tipping warning deice of an automobile crane, which comprises a plurality of oil pressure sensors (1) matched with the number of supporting legs, an analog quantity input circuit (2), a microprocessor (3) and a warning indicator (4), wherein an input end of the analog quantity input circuit (2) is connected with an output end of each oil pressure sensor (1), an output end of the analog quantity input circuit (2) is connected with an A/D module of the microprocessor (3), and the microprocessor (3) is connected with the warning indicator (4) to integrally form the tipping warning device. The tipping warning device detects the bearing reaction condition of each supporting leg of the automobile crane in real time to judge the tipping risk degree of the automobile crane, and warn an operator in time when the automobile crane is confirmed to be in a tipping dangerous condition so that the operator has time to eliminate tipping dangers by an operating method.

The invention provides a rear collision early warning assisting system for a vehicle, and relates to the technical field of vehicle safety. The rear collision early warning assisting system comprises a detecting radar and a vehicle-mounted control unit, wherein the detecting radar is arranged on the lateral rear part of the vehicle and used for detecting a real-time distance between the current vehicle and a rear coming vehicle; a distance threshold or a time threshold is set in the vehicle-mounted control unit, the vehicle-mounted control unit is used for comparing the real-time distance with the distance threshold, or comparing to-be-collided time obtained through conversion of relative speeds of the two vehicles with the time threshold, when the real-time distance is smaller than the distance threshold or the to-be-collided time is smaller than the time threshold, the vehicle-mounted control unit controls the vehicle to be in an rear collision early-warning assisting state, and the vehicle-mounted control unit controls vehicle body components to send audible and visual alarms so as to remind the vehicle behind the current vehicle to pay attention. The rear collision early warning assisting system can evaluate the rear collision of the vehicle according to the distance between the current vehicle and the vehicle behind the current vehicle, and if the distance is too short, the evaluated collision possibility is high, then the front vehicle automatically sends the audible and visual alarm so as to remind the rear vehicle to pay attention; and after being reminded, the rear vehicle can brake or take other measures to improve the driving safety.

The invention relates to a mining fire behavior early warning method and system based on multi-parameter cross-over analysis. According to the four stages of the spontaneous combustion process of coal, that is, the eremacausis stage, the fast oxidation stage, the vigorous oxidation stage and the spontaneous combustion stage and the low-temperature oxidation experiments of different types of coal samples, the threshold values corresponding to temperature and CO concentration in each stage are determined. The temperature, CO concentration, C2H4 concentration and C2H2 concentration in a coal mine fire behavior monitoring area are collected. The collected temperature and CO concentration are compared with the threshold values in each stage, the stage of the fire behavior of the coal mine fire behavior monitoring area is judged according to the comparison result, the C2H4 concentration and the C2H2 concentration, and therefore accurate early warning in each stage of the mining fire behavior is realized. Accurate early warning of the fire behavior in each stage of the spontaneous combustion process of coal can be achieved, the problem that under the condition that the stage of spontaneous combustion is undefined, firefighting measures are taken hastily and then a gas explosion accident is caused is avoided, and great significance in prevention of coal spontaneous combustion fire disasters is achieved.

The invention provides a displacement-based rainfall landslide early-warning method and a displacement-based rainfall landslide early-warning device. The method comprises the steps of obtaining current rainfall intensity of a side slope and current displacement of a target monitoring point; when the current rainfall intensity is greater than target rainfall intensity, judging whether the displacement of the target monitoring point is greater than a target displacement threshold or not; and when the displacement of the target monitoring point is greater than the target displacement threshold, releasing early-warning information. Thus, through implementation of the displacement-based rainfall landslide early-warning method and device, the rainfall landslide can be early warned accurately by combining the rainfall intensity and the displacement of the target monitoring point.

The invention discloses a flow-based risk early-warning system which comprises a flow risk point acquiring sub-system, a risk conduction path model building sub-system, a risk point severity degree evaluating sub-system and an early-warning processing sub-system, wherein the flow risk point acquiring sub-system can acquire the information of each business processing node of the business processing flow of an operation control system, find out business processing nodes with safety risk, and set flow risk points; the risk conduction path model building sub-system can find out from the flow risk points each relative risk point which triggers potential unsafe event, build a risk conduction path model according to the relative risk points and the potential unsafe event, and acquire the severity degree of the potential unsafe event and summarized data information of unsafe information of the relative risk points; the risk point severity degree evaluating sub-system can evaluate to determine the severity degree of each relative risk point according to the risk conduction path model, the severity degree of the potential unsafe event and the summarized data information; and the early-warning processing sub-system warns the risk point with high severity degree early. The flow-based risk early-warning system can give early warnings in time according to the determined severity degree of the risk point in the flow.