1015 results about "Early warning signs" patented technology

A system is provided that furnishes physiological or biomechanical parameters from sensors placed upon or within a subject. The system comprises radio frequency energized biosensor (RFEB) devices that are powered by and communicate with an external receiver and monitoring apparatus. One embodiment of the system provides for infant monitoring in a crib utilizing RFEB devices incorporated into a dermal patch. Said patch communicates with a receiver suspended above the crib and alerts of early warning signs of sudden infant death syndrome (SIDS) or other physiologic abnormalities. Another embodiment comprises implantable RFEB devices that relay information related to the condition of an internal tissue, organ, or cavity to an external receiver, monitor, and recorder. Other embodiments include wearable sensors for detecting a subject attempting to get out of bed, dislodge medical equipment, or stray from a given location.

The invention discloses a bolt loosening monitoring method and an implementation device thereof. According to the method, a bolt loosening situation is determined by monitoring the tension of a screw; if the tension of the screw is lower than a safety threshold value, the bolt is determined to be loosening. A piezoelectric sensing element is arranged between a screw cap and a connected component, and is used for monitoring the change of the tension of the screw in a using process of the bolt, acquiring the feedback response signal under the change, comparing the feedback response signal with a preset safety threshold value, and analyzing to determine the bolt loosening situation; if the tension of the screw is lower than the safety threshold value, the bolt is determined to be loosening, and an early-warning signal is sent out. The bolt loosening monitoring device for implementing the method comprises the piezoelectric sensing element, a data acquisition element, data reading equipment, and a data management analysis and feedback alarm module. By the method and the device, the bolt loosening state can be examined remotely and quickly; the main body of the monitoring device can be detached and replaced; the original structure is little influenced; the method and the device are suitable for large structural bolt monitoring; the manpower and energy resources are saved; the cost and the operating cost are low.

The invention discloses an on-line transmission line lightning shielding failure trip early-warning method. The method comprises the following steps of: performing statistics on historical lightning shielding failure trip information to obtain transmission line lightning shielding failure trip probability distribution by a two-dimensional information diffusion theory and a conditional probability method; selecting radar forecast data, such as echo intensity, echo tops and vertical accumulated liquid water content; establishing a lightning current magnitude prediction model based on a back propagation neural network; and sending real-time early warning and an early warning grade of transmission line lightning shielding failure trip probability according to the predicted lightning current magnitude and the side distance to lightning stroke and by virtue of the transmission line lightning shielding failure trip probability distribution model. According to the real-time forecast data of a meteorological radar, the method provided by the invention can predict the trip probability of a transmission line and send an early warning signal, thereby providing reference for decision-making analysis of grid dispatching operators, making a transmission line dispatching strategy in time, improving power supply reliability, lowering economic loss of a grid, and improving the reliable running ability of the grid.

Embodiments of the present invention relate to a system for monitoring the characteristics of key components of aeronautical machines (e.g., airplanes, helicopters, etc.), processing obtained data, and delivering prognostic health indicators to improve machine performance and detect early warning signs of failure. In one embodiment, a method of maintaining prognostic health management accuracy of an aeronautic system comprises providing a control module and a sensor pod having a plurality of sensors, and physically positioning the plurality of sensors on a mechanical component of an aircraft; obtaining operational data from the sensors while the aircraft is operating in a native environment; transmitting operational data to the control module and determine real-time system performance characteristics; processing real-time system performance characteristics against a set of historical records containing past system performance characteristics and generating predictive indicators for forecasting remaining component lifetime and future component failures; and providing predictive indicators on an indicator means.

The invention provides a lane departure early warning method and a lane departure early warning system, wherein the method comprises the following steps that: a lane line in a lane line image is obtained through a reversing camera arranged at the tail part of an automobile; the mapping relationship between an image coordinate system and a world coordinate system is determined; a second coordinate equation of the lane line in the world coordinate system is determined according to a first coordinate equation of the obtained lane line in the image coordinate system; after the distance from a rear axle center of the automobile to the lane line is determined according to coordinate equation parameters in the second coordinate equation, the distance from a front axle center of the automobile to the lane line is determined; and if the distance from the front axle center of the automobile to the lane line is smaller than a preset distance, and the condition that a steering lamp turning-on signal is not received is determined, an instrument warning device is turned on, so that the instrument warning device gives out a lane departure early warning signal. The goal of providing the lane departure early warning method and the lane departure early warning system is achieved; whether the automobile generates lane departure or not can be effectively and accurately judged; and the automobile lane departure early warning can be accurately performed.

The invention discloses a metering apparatus operation state early warning method which comprises the following steps of: 1, selecting index information that can reflect an operation state of each part from offline input information and online monitoring information of four composition parts of an electric energy metering apparatus; 2, pre-processing data and performing abnormal data removal and replenishment on original data; 3, respectively establishing evaluation systems and carrying out scoring on the operation state of each part by applying an AHP comprehensive evaluation model; 4, carrying out data mining on the evaluation system of each part, selecting evaluation indexes with great influence on the operation states; 5, combining the online monitoring information and by a cloud self-adaptive PSO-BPNN predicting model, predicting a future operation state score value of each composition part; and 6, comparing the predicted operation state score values with an evaluation standard, determining the operation states of four composition parts, and timely giving out an early warning signal. According to the metering apparatus operation state early warning method which is provided by the invention, the operation states of the metering apparatus can be effectively subjected to early warning, thereby improving the pertinency, reliability and scientificity of detection of the electric energy metering apparatus.

The invention relates to an early monitoring device for hydrate blockage of a deep water gas well production pipeline. The early monitoring device comprises a data collecting and transmitting system, a data analyzing and processing system and an automatic hydrate inhibitor injection system. The data collecting and transmitting system monitors temperature and pressure data in the production pipeline in real time and transmits the monitoring data to the data analyzing and processing system. The data analyzing and processing system stores, analyzes and processes the monitoring data, calculates and analyzes the natural gas hydrate blockage condition in the production pipeline and sends out an early warning signal and a hydrate inhibitor injection instruction. The automatic hydrate inhibitor injection system is arranged on a platform and injects hydrate inhibitor into the production pipeline according to the instruction sent by the data analyzing and processing system. By means of the early monitoring device, early monitoring can be achieved for the hydrate blockage position and the blockage severity degree in the production pipeline, sufficient time is provided for field workers to take the hydrate inhibitor injection measure, and more serious blockage conditions are avoided.

The invention discloses a bus driver hand-off-steering-wheel detection warning system and a warning method. The system comprises a camera, a digital signal processor, a GPS (global position system) module, a control module and a GPRS (general packet radio service) module. The method includes the steps of 1), colleting images of a driver operating steering wheel; 2), calculating the images by adopting an operator detection recognition method, distinguishing the state of a driver hand-off steering wheel, and judging out whether a driver is in the state of left-operating hand-off steering wheel, the state of right-operating hand-off steering wheel or the state of both-hand-off steering wheel; 3), judging whether to trigger warning signals or not by adopting a warning logical judgment method; 4), outputting information to an upper computer. By the detection warning system and the warning method, easiness in setting is achieved, the visual system is downsized, a universal foundation technology platform for image processing is provided, any compulsory interference on the body of the driver is omitted, cost is low and the like.

The invention discloses a Yangtze River endemic fish oviposition habitat monitoring method and system based on the Internet of things. The method comprises the steps of performing optimized arrangement of a sensor assembly within a Yangtze River endemic fish breeding inhabitation range, collecting water environment information and fish behavior information of the Yangtze River endemic fish breeding inhabitation range in real time, utilizing a technology of the Internet of things to transmit the collected information to a monitoring control center, enabling the control center to evaluate the monitored water environment in real time by combination with a endemic fish oviposition habitat evaluation model, sending ecologic early warning to a dam dispatching center when the habitat water environment exceeds a fish fitness value, and enabling the dispatching center to adjust a dam running mode timely according to early warning signals so as to improve the oviposition habitat fitness value and protect endemic fish resources. The system comprises a data collecting system, a data transmission system and a data processing system. Automatic positioning, automatic monitoring record and wireless network technologies are adopted, and the goal of real-time monitoring and analysis of the habitat water environment is achieved.

The embodiment of the invention discloses an early warning method for the life service of a solid state disc, an alarm device, the solid state disc and an early warning system. The early warning method for the life service may comprises the following steps of: monitoring the service life state of the solid state disc; judging whether the service life state reaches a set early warning value or not; and sending an early warning signal when the service life state reaches the set early warning value. The technical scheme has the advantages that: by monitoring the service life state of the solid state disc, the early warning for the service life is carried out when the service life state approaches the set early warning value; and a prompt is given before data are possibly lost, so a user can prepare a data backup in advance, and the reliability of the solid state disc and the safety of the data stored in the solid state disc are improved.

A safe early warning method and device for full-section tunneling of a tunnel featuring dynamic water and weak surrounding rock, comprising establishing a dynamic coordinate system with an origin thereof moving along a tunnel excavation line, recording the moving distance of the origin, conducting three-dimensional laser scanning with the origin as a center to obtain point cloud data including coordinate data, collecting surrounding rock data; conducting deformation fitting on the point cloud data, calculating a fitting residual error, removing a noisy point, and conducting preprocessing; combining data of preprocessed point cloud, surrounding rock, and the tunnel excavation line to construct a tunnel excavation dynamic model; conducting stress analysis according to the model and determining whether to send out a safety early warning signal. The device comprises a three-dimensional laser scanner, a geological radar device, a displacement module, an industrial computer, a data transmission module, an alarm, and a server.

The discovery cost forecasting system uses incomplete information to generate forecasts of discovery expenses. Models are generated with different levels of granularity depending upon the available facts and user preferences. An expert provides real-time information to improve the accuracy of the predictions. A scenario analysis is generated that evaluates how changes to the parameters of the matter could affect the forecasted cost. An estimate is generated of the degree of advancement of the matter in its lifecycle as part of the cost forecast. The cost associated with each data source and custodian is tracked and reported. A configurable and extensible cost equation is defined. A dashboard user interface is generated to monitor the entire portfolio to extract easy to understand facts, trends, and early warning signs related to discovery cost management.

The invention discloses a method and a system for power communication failure early warning analysis based on a network model and rule models. The method includes: (1) building the failure early warning analysis network model; (2) building the failure early warning analysis rule models by combining the network model; (3) reading and analyzing all the built rule models, and inputting the rule models to a rule inference engine; (4) acquiring communication network alarm and performance information for normalization, and then inputting the information into the rule inference engine; (5) enabling the rule inference engine to infer according to the performance early warning rule model and to give early warning signals according to a rule conclusion part; (6) enabling the rule inference engine to infer according to the service influence range rule model and to give influenced services and influenced degree of the services; and (7) giving failure handling suggestions according to an early warning handling expert experience repository. By the method and the system, early warning prompts can be automatically given in real time before failures occur, and early warning service influence range and early warning handling suggestions can be given so that a technical means is provided for stable operation of power communication grids.

The invention relates to a method for giving a wire damage alarm when lead wire is coated by ice, which performs calculation and judgment on disconnection, vertical overload of a tower and longitudinal unbalanced tension of the lead wire. The method is implemented by the following work procedures: a, calculating design load and actual load according to tower design, actual vertical span, the design load and ice thickness measurement data; b, at the same time, calculating wire tension and unbalanced tension according to the ice thickness measurement data and wind measurement data; and c, sending early-warning information when any of the design load and the actual load calculation, the wire tension calculation and the unbalanced tension calculation is overloaded. When an icing on-line monitoring device monitors the icing condition of a power supply wire, the method performs calculation and analysis according to the monitored data to judge whether the wire icing condition threatens the safety operation, and send warning signals in time.

The invention discloses an anti-collision early warning system based on 360-degree look-around input. The anti-collision early warning system comprises a look-around fisheye camera, a vehicle-mountedsensor unit, a control module and an early warning and reminding module. The look-around fisheye camera is used for collecting image information around a vehicle; the vehicle-mounted sensor unit is used for collecting vehicle signals; and the control module is connected with the look-around fisheye camera and connected with the vehicle-mounted sensor unit, receives the vehicle signals and / or the image information, performs analysis and process, and outputs an early warning signal. The warning and reminding module receives the early warning signal. The anti-collision warning system is mainly aimed at the conditions that pedestrians / bicycles passing through the front and rear of the vehicle transversely and bicycles passing through the blind area on the right side of the vehicle in the samedirection have possible collision with the vehicle; through video intelligent analysis and processing, the pedestrian collision prevention and protection functions are integrated into a look-around system; and the active / auxiliary safety performance of the 360-degree look-around system is improved in the way of auxiliary display and early warning.

The invention discloses a safety hazard detection system and a safety hazard detection method for a high-voltage transmission line, wherein the system comprises: an image acquisition device for performing image sampling on a warning area under the transmission line; a remote video monitoring system for processing the acquired image information, and sending an early warning signal to a monitoring client according to the processing result; and a monitoring client for receiving the early warning signal sent by the remote video monitoring system, and guiding the maintenance personnel of the transmission line to arrive at the scene to eliminate the safety hazard. In the invention, safety detection is performed according to the image of the warning area under the transmission line collected by the image acquisition device, the remote video monitoring system generates an early warning signal once a safety hazard is detected in the warning area and sends an alarm to the remote monitoring client to remind the transmission line maintenance personnel arrive at the scene to eliminate safety hazards, thereby providing a scientific basis for preventing power transmission line blackouts and gaining great practical value.

The invention discloses a bolt fault monitoring system. The system comprises: a detection element (1), a control element (2) and an alarm element (5). The detection element (1) is used to detect a load or a response of a connected piece (4) which is connected through a bolt (3) and acquire a corresponding load signal or a response signal. The control element (2) is used to receive the load signal or the response signal and compare the load or the response with a predetermined threshold. When the load or the response is out of a threshold scope, the control element (2) makes the alarm element (5) emit an early warning signal. The alarm element (5) is used to emit the early warning signal according to an instruction emitted by the control element (2). Through detecting load changes or response changes of the connected piece, the bolt can be monitored whether to have a fault. A plurality of bolts on the connected piece can be simultaneously monitored so that fault monitoring of a bolt group can be realized. The invention also discloses a bolt fault monitoring method.

The invention discloses an abnormal driving detection method and device, and the method comprises the steps: detecting face image data collected in a preset time period, and extracting a plurality ofhuman eye features representing the lengths and widths of eyelids; obtaining the blinking times according to the relationship between the plurality of human eye features and the eye opening degree; obtaining a fatigue reference value according to the blinking times and the change relation of the eye opening degree along with time in the single blinking process; inputting the fatigue reference value into a detection model to predict the fatigue degree so as to obtain a fatigue prediction value; and when the fatigue prediction value is in different fatigue levels, sending an early warning signalcorresponding to the fatigue level. Aiming at the problems of low accuracy, low safety and the like of the existing fatigue driving detection technology, the detection accuracy and the safety coefficient are improved.

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 discloses a power battery pack internal temperature online detection method and system. The power battery pack internal temperature online detection method includes the steps of determining a power battery pack apparent resistivity detection system platform based on the electrical resistance tomography, obtaining the power battery pack internal apparent resistivity, establishing a smoothness restraining least square method, obtaining three-dimensional inversion images of the power battery pack internal apparent resistivity in real time, and according to the relationship between the power battery pack internal apparent resistivity and changes of the internal temperature, obtaining a power battery pack internal temperature field distribution diagram, determining a partial high temperature abnormal change phenomenon and giving an early warning signal. According to the power battery pack internal temperature online detection method and system, traditional detection limitation is broken through, and the power battery pack internal apparent resistivity based on the electrical resistance tomography is detected so that the internal temperature distribution conditions can be indirectly and accurately obtained. The three-dimensional image inversion method is established, therefore, the power battery pack running health condition can be mastered in an all-directional mode, and the safety performance of a power automobile in practical running is effectively improved.

The invention relates to an on-line detecting device and method for a descending brake distance of a crane hoisting mechanism. The on-line detecting device comprises a crane operation condition signal detection portion 1 and a measuring and recording portion 2, wherein the crane operation condition signal detection portion 1 includes an encoder, a brake power-off detection unit 4 and a hoisting direction detection unit 5; the measuring and recording portion 2 includes a controller 10, a signal interface unit 9, a display and operation unit 11 and a data storage unit 12; the encoder is an incremental encoder 3 or an absolute value encoder 13. The brake distance detecting method includes that the measuring and recording portion 2 monitors the descending brake process of the hoisting mechanism in real time, acquires data of descending brake distance, and calculates the descending brake distance. The measuring and recording portion 2 measures and records the measuring result of every brake distance in real time, and sends out warning signals when the brake distance approaches to or exceeds a specified value to prompt deterioration of brake performance, the variation trend of brake performance can be observed through a brake performance curve, failure of a brake mechanism can be discovered at early stage, accidents caused by deterioration of brake performance can be avoided, early stage forecast can be achieved, and operation safety of the crane can be effectively guaranteed.

The invention discloses an unmanned aerial vehicle route early warning method and device, equipment and a storage medium. The method comprises the following steps: acquiring a plurality of forward original images containing obstacles of the unmanned aerial vehicle by using a monocular camera; determining a non-sky area containing the obstacle in each original image; dividing the non-sky area intoa plurality of grids; determining the distance from the area corresponding to each grid to the unmanned aerial vehicle; determining the overlap ratio of each grid and the course direction; checking whether the distance between the area corresponding to the grid and the unmanned aerial vehicle is smaller than or equal to a preset threshold value or not; checking whether the overlap ratio of the grid and the course direction is smaller than or equal to a preset threshold value or not; and if the conditions are simultaneously met, sending an early warning signal. According to the technical schemeprovided by the embodiment of the invention, remote obstacle detection and early warning are realized, so that the safety of the unmanned aerial vehicle in the navigation flight process can be effectively improved.

The invention provides an underground gas storage safe operation monitoring system and monitoring method. The underground gas storage safe operation monitoring system comprises armored optical cables,quasi-distributed optical fiber pressure sensors and underground three-component detector arrays, wherein the armored optical cables and the quasi-distributed optical fiber pressure sensors are distributed inside and outside all gas injection wells, gas production wells and monitoring well sleeves and outside in-well gas injection and production pipes, and the underground three-component detectorarrays are partially distributed in a monitoring well. The measurement armored optical cables, the quasi-distributed optical fiber pressure sensors and a composite modulation and demodulation instrument placed near a wellhead are fixed to the outer side of the metal sleeve. According to the underground gas storage safe operation monitoring system, real-time on-line monitoring of changes of noise,temperature, pressure, stress / strain and distribution characteristics of microseism events in all wells is comprehensively and fully utilized, intelligent comprehensive analysis and evaluation are carried out on all parameters and information monitored in real time on line, grading classification is carried out on various risks or accidents influencing safe and stable operation of the gas storage, early warning signals and information of accident risks are issued in time, and long-term stable and safe operation of the gas storage is ensured.

The invention provides an early warning device based on an automatic vending machine and a method thereof. The early warning device includes an MCU, a host computer or a background server, at least one sensor, a recording module, an analysis module, an early warning module, a standard single product weight module, and a user identity identification module. The method includes the steps that (1) the sensor collects the status data in real time and provides the status data to the MCU; (2) the recording module stores the status data; (3) the analysis module determines whether there is an abnormalcondition according to the status data analysis and sending the abnormal condition to the early warning module if there is an abnormal condition; and (4) the early warning module determines the earlywarning level based on the abnormal condition and sends the early warning level to the host computer or the background server. With the above-mentioned early warning device and method, device and user behavior analysis is conducted to obtain the early warning level of the device in the abnormal condition, and an early warning signal is sent to the upper computer or the background server to facilitate maintenance personnel to deal with the abnormal condition in time, avoid further damage to the automatic vending machine, and meet the low-cost operating requirement of the automatic vending machine.

The invention discloses a lithium iron phosphate battery state-of-charge monitoring and early warning method based on a neural network, and the method comprises the steps: carrying out the training ofa T-S fuzzy neural network model through a training data set, and obtaining a trained T-S fuzzy neural network model; inputting actual battery voltage, battery current and battery temperature data atthe moment T into the trained T-S fuzzy neural network model, and outputting estimated battery SOC; when the SOC decline rate of the battery is higher than a set value, sending an early warning signal that the electric quantity declines too fast and the battery is abnormal; and when the SOC of the battery is lower than 10%, emitting an early warning signal of the low electric quantity of the battery. According to the lithium iron phosphate battery state-of-charge monitoring and early warning method based on the neural network provided by the invention, the SOC estimation precision can be effectively improved, the battery state-of-charge is monitored and early warned, and the reliability and safety of the battery are improved.

The invention discloses a strong wind early warning modeling method and a strong wind early warning modeling system based on a power grid GIS (geographic information system). The strong wind early warning modeling method comprises the following steps of respectively establishing a strong wind weather chart layer and a power grid equipment chart layer in a platform of the power grid GIS; overlapping the power grid equipment chart layer and a monitored strong wind weather chart layer; establishing risk power grid equipment data in a strong wind influence scope; establishing association between the strong wind influence scope and the power grid equipment; producing different levels of early warning signals according to current real-time wind speed and wind resistant strength information of facilities of a power grid; generating power grid strong wind disaster early warning information; issuing the early warning information; and showing the generated power grid strong wind disaster early warning information by using the power grid GIS equipment chart layer. A professional power grid strong wind early warning model is established, precise monitoring, forecasting and early warning on the facilities and running of the power grid are implemented, a destructive effect on a disaster is reduced effectively, a pointed wind resistant measure standard can be formed, and loss of the power grid is reduced.

The invention discloses a passenger classification protection method, system and device and a computer readable storage medium. The method is applied to a seat, and comprises the steps of: acquiring the posture information of a current passenger, and classifying the current passenger to a corresponding passenger category according to the posture information, with the posture information comprisingbody shape information and / or sitting posture information; and judging whether a collision early warning signal is received, and if yes, adjusting the seat to an optimal protection position accordingto the passenger category. According to the method, current passengers are classified into different categories according to the posture information of the current passengers, when a collision earlywarning signal is received, seats can be adjusted to different positions according to the posture characteristics of different passengers, so that the seats can adapt to the personalized requirementsof different individuals, a personalized pre-collision protection scheme is provided for each individual, and the harm of traffic accidents to the passengers is greatly reduced.

The invention relates to a method and device for detecting abnormal events in surveillance videos. The method includes the steps that according to a pre-built training model, whether to-be-detected features of a received target surveillance video are matched with the training model or not is detected; if not, it is determined that an abnormal event exists in the target surveillance video; according to the abnormal event, an early warning signal is generated and output, wherein the training model is obtained by training based on multiple angles of the abnormal event expression form, and / or thetraining model is obtained by training based on a locality-sensitive hash function in combination with a Bloom filter algorithm. By means of the technical scheme, the adaptability of detecting abnormal events in surveillance videos can be improved, and the false alarm rate can be reduced.

The present invention discloses an anti-collision early warning system for a vehicle and a vehicle comprising the anti-collision early warning system. The anti-collision early warning system includesan alarm host, a laser radar device, an ultrasonic radar device and an alarm device; the warning host includes a positioning device, a database communication device, and a first communication module;the database communication device is used for obtaining height-limiting obstacle positioning information in a database; the positioning device is used for obtaining the positioning information of thevehicle in real time, and determining a distance between a height-limiting obstacle ahead nearest to the vehicle and the vehicle through comparison, and the first communication module instructs the alarm device to send out first-level early warning signals when the distance is too small; the laser radar device is used for detecting the distance of the height-limiting obstacle and instructing the alarm device to send out second-level early warning signals when the distance is too small; and the ultrasonic radar device is used for detecting the distance of the height-limiting obstacle and instructing the alarm device to send out third-level early warning signals when the distance is too small. With the system of the invention adopted, a user can be effectively warned against an obstacle found in a transportation road, and the safety and reliability of goods transportation can be fully guaranteed.

The invention discloses an early-warning and tracing method for unknown infectious diseases. The method comprises the following steps: S1, establishing an early-warning and tracing system for unknowninfectious diseases; S2, collecting doctor-seeing information and positional information of patients, and uploading the doctor-seeing information and the positional information to a database; S3, allowing the database to classify the treatment information of all the patients according to different symptoms; S4, enabling an unknown infectious disease early-warning module to analyze the distributionrule of patients with certain symptoms in the database and to give out an early-warning signal when the density of the patients is high; S5, allowing an unknown infectious disease early-warning and decision-making module to trace back infectious disease patients and possibly infected people; and S6, fitting the occurrence position of a last-generation maximum possible infection source, and carrying out continuous iteration until the a primary-generation maximum possible infection source is traced back. According to the early-warning and tracing method for unknown infectious diseases, early warning can be given out before confirmation of unknown infectious disease, and patients with the infectious diseases and people who may be infected with the infectious diseases can be reversely tracedback after the confirmation of the unknown infectious diseases.