2355 results about "Blind zone" patented technology

The invention discloses a constructional engineering quality data management method based on artificial intelligence, particularly relates to the field of constructional engineering quality data management, and is used for solving the problems that multi-source heterogeneous quality data is unbalanced in spatial distribution and correlation analysis, monitoring blind areas and abnormal information are difficult to accurately capture. According to the method, by dynamically integrating multi-dimensional quality data of a construction site, unified processing and associated mining of different monitoring indexes in different areas are achieved, and deviation caused by uneven data distribution and local information loss is eliminated; internal association and potential abnormal fluctuation characteristics are extracted from multi-source data by using a space-time sequence analysis and spatial difference analysis method, so that more accurate and comprehensive basic data are obtained under complex conditions; the abnormal or missing data is finely reconstructed and complemented through a data enhancement technology, so that the monitoring data is kept continuous and complete in the space-time dimension, and the overall quality judgment is not influenced by local blind areas or missing points.

The invention relates to the technical field of obstacle detection, and discloses an unmanned subway obstacle intelligent detection system based on a multi-mode AI sensor, and the system comprises the multi-mode AI sensor, a preprocessing unit, a data processing unit, and a communication unit. According to the method, in data preprocessing, point cloud filtering denoising, down-sampling burden reduction, image graying contour highlighting and Gaussian filtering denoising all improve the processing efficiency and the detection precision. Efficient data fusion establishes a multi-coordinate system conversion relation, blind area misjudgment is avoided, and the complex environment adaptability is enhanced. A comprehensive obstacle detection strategy covers laser radar multi-link processing and Canny algorithm application of visual images, mutual verification is carried out, and the reliability is improved. When obstacles are detected, real-time display and graded alarm can be achieved, early warning and scheduling control can be achieved by means of network transmission information, braking or avoiding can be achieved according to conditions, operation safety is guaranteed, and the system is reasonable in structure, has adaptability and expandability and assists technology development.

The invention discloses a smart park security and protection system and a control method thereof, and relates to the technical field of smart security and protection, the system comprises the following components: a diversified sensing module which integrates a video monitoring sensor, a face recognition sensor and a behavior analysis sensor and constructs an omnibearing sensing network. According to the technical scheme, all-dimensional and multi-angle monitoring and recognition of the park are achieved, the information acquisition capacity of the security and protection system is remarkably improved through the technological innovation, the comprehensiveness and accuracy of data are ensured, the diversified sensing module integrates multiple sensors of video monitoring, infrared detection, face recognition and behavior analysis, each sensor performs own functions and complements each other, and the monitoring and recognition efficiency is improved. According to the system, blind areas and errors possibly generated by a single sensor are effectively eliminated, the multi-angle sensing network enables the system to more accurately capture abnormal conditions in the park, and a solid foundation is provided for subsequent intelligent analysis and early warning.

The invention discloses a safety detection system for a tool magazine of a gantry machine tool, relates to the technical field of gantry machine tools, and solves the problems that an object entering a blind area cannot be quickly recognized to belong to a human body, and the comprehensiveness of recognition needs to be improved. By means of two-dimensional coordinate system analysis, central point overlapping and zooming operation, calculating an overlapping area proportion so as to judge whether the area is a human body area or not; the scientific judgment mode improves the accuracy and reliability of recognition, reduces the false alarm rate, ensures the accurate transmission of early warning information, and can quickly send out an early warning signal through the early warning end to remind an operator to take measures in time to avoid danger once the system judges that a change area belongs to a human body area; the real-time response mechanism can effectively reduce the probability of accidents and kill potential risks in the bud.

The invention discloses a vehicle driving assistance system and method based on AR glasses. The system comprises an environment sensing module, a driver state monitoring module, a danger early warning and avoiding module, an automatic driving and auxiliary driving module, a driving simulation and training module, an abnormal behavior recognition module, a road information and navigation module and a health and emergency response module. The environment perception module is used for solving the problem of poor sight in extreme weather and road perception in a complex environment; by means of sensors such as the laser radar and the camera, road obstacles, pedestrians and vehicles can be accurately recognized, highlighted marking in the AR visual field is achieved, accidents caused by sight blind areas or distraction are reduced, indexes such as the blinking frequency and the head posture of a driver can be monitored, immediate reminding is conducted when fatigue or distraction is found, and parking and resting are forcibly suggested when necessary; and when the driver does not respond in time, the system can automatically brake or adjust the direction to avoid collision.

The invention relates to the technical field of construction automatic pay-off control, in particular to a positioning blind area deviation rectification control system of an automatic pay-off robot. When the paying-off robot encounters an obstacle and causes signal loss, the system records loss and recovery positions, and an obstacle area is determined through a connecting line. The robot keeps moving around an obstacle by a constant distance, and coordinate data are collected in real time and mapped to a digital drawing. The system processes a signal blind area which is completely shielded by an obstacle, ensures that the robot continues to execute accurate paying-off operation in the blind area by correcting paying-off coordinates in a drawing, and corrects errors in the blind area. The system optimizes blind area entry points by using a path optimization algorithm in combination with steering times and path length, and error superposition is reduced. After each time of obstacle avoiding or blind area paying-off, the robot returns to a calibration point, position deviation is adjusted in real time through a Kalman filtering algorithm, errors are corrected, the paying-off precision in blind area operation is improved, and deviation accumulation is reduced.

The invention provides a multi-camera cooperative non-blind area intelligent monitoring method, and relates to the technical field of intelligent monitoring and security protection, and the method comprises the steps: carrying out the system calibration of a plurality of cameras, and building a mapping relation between the image coordinates of each camera and a unified world coordinate system; performing time synchronization and preprocessing on the data acquired by the plurality of cameras; continuously tracking the target based on a cross-camera target detection and re-recognition algorithm; based on a multi-view geometric principle, reconstructing a three-dimensional scene structure of a monitoring area in real time; according to the visual angle quality evaluation model, automatically selecting an optimal observation visual angle and controlling the pan-tilt camera to perform active tracking; and carrying out modeling on the cross-camera behavior based on the space-time diagram convolutional network to realize anomaly detection.

The invention discloses a blind area prompting method and device, electronic equipment and a storage medium, and belongs to the technical field of vehicle application, and the method comprises the steps: determining a target blind area of a target vehicle according to a to-be-driven route of the target vehicle; acquiring a first environment image shot by an environment camera corresponding to the target blind area; performing target detection based on the first environment image, and generating first state information of each traffic participant in the target blind area; and based on the first state information of the traffic participant, generating an environment modeling image containing the traffic participant and displaying the environment modeling image. The target vehicle can notice traffic participants in the blind area in time, the driving safety of the target vehicle can be improved, target detection is carried out on the target blind area determined by the to-be-driven route of the target vehicle, the target vehicle can be prevented from processing images of all environment cameras in the current environment, and the driving safety of the target vehicle is improved. The data volume needing to be processed in the blind area detection process is reduced, and the blind area reminding efficiency and speed of the target vehicle can be improved.

The invention provides a vehicle blind area monitoring device and method based on a rear camera. According to at least one implementation mode, the invention provides a vehicle blind area monitoring device based on a rear camera, and the device comprises an image acquisition unit, a control unit and a display unit. The image acquisition unit is configured to acquire a rear image from a rear camera mounted on a vehicle. The control unit is configured to set a region of interest in the rear image based on a steering signal or a lane departure signal of the vehicle, determine whether there is a risk of approaching an object in the region of interest to the vehicle, and generate a blind spot image based on whether there is a risk of approaching. The display unit is configured to display a blind spot image.

The invention relates to a visual calibration method and system for an uncalibrated automatic mechanical arm, the method comprises two calibration modes of'eye on hand 'and'eye outside hand', the'eye on hand 'calculates and determines a hand-eye matrix through a camera and a marker mounted at the tail end of the mechanical arm so as to obtain pose transformation between the tail end of the mechanical arm and a flange in real time. In the calibration of'eyes outside hands', a global camera and a marker installed on the mechanical arm are utilized to determine the position and posture relation between the tail end of the mechanical arm and a target object through coordinate transformation, and therefore accurate calibration of the mechanical arm is achieved. The calibration method is suitable for scenes where D-H parameter precision is poor, a view blind area exists, and real-time deviation correction needs to be conducted through a visual servo system during work of the mechanical arm.

The vehicle control device includes an onboard sensor for acquiring information related to an object OB present around the own vehicle, and a processor capable of executing risk reduction processing to control the own vehicle in a way that reduces the risk of contact with the object based on the acquired information. The processor initiates the risk reduction processing in a specific scene S, where there is a blind spot area BA in the field of view of the onboard sensor, caused by the presence of a preceding vehicle V1 traveling in the same direction as the own vehicle and positioned in the region diagonally ahead of the own vehicle, making it impossible for the onboard sensor to detect the object OB. The risk reduction processing is triggered when the preceding vehicle V1 decelerates, and the cause of the deceleration cannot be detected.

The invention provides a control method and system of a double-arm clothes folding robot, and relates to the technical field of robot control, and the control method constructs a perceived control closed loop by fusing visual, force and tactile multi-modal data. The touch sense and the force sense make up the blind area of the vision in the self-shielding scene, and grabbing, sliding and pleating perception is improved. Based on clothing joint characterization of a visual semantic network, geometric morphology, semantic components and confidence coefficient are structured and coded, a robust state fusing prior and real-time observation is provided for planning, and decision errors caused by deformation and noise are reduced. Long-time-history folding is decomposed into sub-target sequences through a hierarchical strategy, action closed-loop correction is conducted through multi-modal data, and cooperative control over grabbing, folding and pleating is achieved. And finally, a torque instruction is generated based on a control algorithm, interaction compliance and safety are ensured, and the folding success rate and operation stability of the double-arm clothes folding robot under different materials, sizes and initial forms are integrally improved.

The invention discloses a control method for collaborative trajectory planning of a container inspection robot. The control method comprises the following steps: S1, constructing a global task and a map; s2, obtaining real-time state sensing and positioning of the inspection robot (6); s3, establishing a unified three-dimensional cooperative control decision algorithm, and cooperatively controlling the height of an electric rod on the robot and the pitch angle (pitch), the yaw angle (yaw) and the roll angle (roll) of a holder based on the real-time pose of the robot, the distance between the ideal track and the target container and the standard size of the pre-modeled container; s4, the robot runs according to the planned track to execute the task and collects data; s5, performing global state management and safety strategy of the electric rod of the robot; the method has the beneficial effects that a detection blind area is eliminated, and three-dimensional cooperative control is realized; a camera can lock a target in a three-dimensional space at an optimal pose, image quality consistency is ensured, and jitter is inhibited through active holder movement; and full-process automation and safety protection are realized.

The invention relates to the technical field of image monitoring, and discloses a monitoring blind area determination method, system and device, a medium and a product, and the method comprises the steps: determining each patrol space point position and the space position of each camera in a current camera layout scene through a preset three-dimensional model of a transformer substation, and screening out a plurality of non-patrol point positions; and according to the three-dimensional space range of the non-patrolling point positions, defining a patrolling range area, and cutting the area according to unit space to form a three-dimensional space area. And then, unit spaces which are not in the preset inspection included angle and have shelters are removed, the camera inspection layout areas corresponding to the non-inspection point positions are combined, and finally, the monitoring blind area of the transformer substation is determined. According to the method, the monitoring blind area is determined through the inspection point position and the camera position in the three-dimensional model space, the problems of arrangement shielding and dead angles caused by a two-dimensional drawing are effectively avoided, and the camera utilization rate and the working efficiency are remarkably improved.

The invention discloses a non-cooperative target trajectory prediction method fusing camera miss distance and encoder information. According to the method, the actual track sequence of the non-cooperative target is obtained by fusing the miss distance of the camera of the optical telescope and the grating encoder information, the motion track of the tracking target in the blind area time is predicted by using a prediction algorithm, the telescope is controlled to move directly through optical feedback at the camera sampling moment, and the motion track of the tracking target in the blind area time is obtained at the encoder sampling moment. The corresponding predicted value and the encoder measurement value are subtracted to obtain the tracking error in the blind area time, and the tracking error is input into the telescope motion control system, so that the control frequency and closed-loop bandwidth of the telescope motion control system are improved, and the error between the reference trajectory and the actual trajectory of the tracking target is reduced; therefore, the tracking capability of the optical telescope on the non-cooperative target is improved.

The invention relates to the technical field of road early warning, and discloses a blind area pedestrian early warning method and system based on V2X and machine vision, and the key points of the technical scheme are that a road side end RSU carries out edge calculation, and starts to detect road pedestrian information; if the RSU at the roadside end detects that the pedestrian appears on the current road, tracking the pedestrian based on machine vision, and calculating the accurate position of the current pedestrian target; the road side end RSU broadcasts and sends blind area pedestrian information to external traffic participants, and when a driving vehicle enters a V2I communication range, a vehicle-mounted OBU receives pedestrian information of a front road; when the vehicle-mounted OBU receives the information of the pedestrian ahead, collision early warning calculation is carried out, and the possibility of collision is judged; the road pedestrian shielding detection problem can be solved in the roadside system, meanwhile, the vehicle-mounted equipment receives the pedestrian information from the blind area through V2I communication, the front road pedestrian information is obtained through the beyond-visual-range sensing capacity, the driving safety is improved, and the protection measures for the road pedestrians are perfected.

The invention relates to an unmanned aerial vehicle illumination control method and system based on three-dimensional model data. The method comprises the steps of obtaining three-dimensional model data, environment perception data and flight positioning data, and analyzing a target scene and an unmanned aerial vehicle illumination demand. And based on the data, planning the flight path of the unmanned aerial vehicle, and generating flight path planning data. And in combination with environmental perception information, performing illumination analysis on the main illumination end, calculating main illumination power density distribution and a main illumination angle, and identifying a main illumination blind area. And for the blind area, light supplement analysis is performed by using environmental perception data, and blind area illumination power density distribution and a blind area illumination angle are calculated. And finally, synthesizing the main illumination data and the blind area light supplementing data to generate illumination control information of the unmanned aerial vehicle. By adopting the method, the illumination strategy can be intelligently adjusted under different environmental conditions, the illumination effect, the illumination precision and the illumination uniformity of the unmanned aerial vehicle can be effectively improved, the energy utilization efficiency is also improved, and unnecessary energy consumption is reduced.

The invention provides a blind area early warning method and device based on a look-around system, a vehicle and a storage medium, and the method comprises the steps: obtaining a current look-around image, and recognizing an object in the current look-around image and the type of the object; obtaining a plurality of continuous historical look-around images, and obtaining the relative movement speed of each object according to the current look-around image and the plurality of continuous historical look-around images; according to the relative movement speed, the object type and the object number, obtaining an object weighted characteristic value, and according to the current operation state information and the current driving environment information of the vehicle, obtaining an operation state weighted characteristic value and a driving environment weighted characteristic value respectively; according to the object weighted feature value, the running state weighted feature value and the driving environment weighted feature value, a trained early warning strategy classification model is adopted, an early warning strategy is obtained, and blind area early warning is completed. Based on multi-dimensional data analysis, it is ensured that a complex traffic environment can be accurately responded in real time, and the adaptability of blind area early warning is improved.

The invention provides a blind area early warning method and device and a storage medium, and the method comprises the steps: carrying out the multi-dimensional recognition of a vehicle road scene, obtaining the data of a plurality of sensors, determining the environment type of the road scene where a vehicle is located, adjusting the original weight of each sensor based on the environment type, obtaining a first weight corresponding to each sensor, and carrying out the adjustment of the first weight. Through recognition of environment types, weights are dynamically distributed based on indexes related to environment scenes in a non-linear mode so as to adapt to complex scenes. The sensor data is fused according to the first weight, the influence of the data source with low confidence on the fusion processing is dynamically reduced, blind area early warning is performed based on the fusion result, and the false alarm rate is effectively reduced. In addition, according to dynamic weight adjustment of the indexes related to the environment, the response speed of system execution control is increased.

The invention discloses an unmanned aerial vehicle intelligent obstacle avoidance decision-making method and system for a complex environment, and belongs to the technical field of unmanned aerial vehicle obstacle avoidance. The method comprises the steps of S1, environment perception and data acquisition, S2, multi-source data hierarchical fusion processing, S3, complex environment obstacle recognition and risk assessment, S4, dynamic obstacle avoidance path decision and optimization, and S5, obstacle avoidance execution and real-time adjustment. Omnibearing acquisition of obstacle distance, environment images, unmanned aerial vehicle attitude and position data is realized; the method combines an improved YOLOv8 model (adding a CBAM attention mechanism), strengthens the obstacle feature extraction capability under complex weathers such as rain and fog, strong light and dust, can accurately distinguish static obstacles such as buildings and trees from dynamic obstacles such as pedestrians, vehicles and other aircrafts, and solves the problems that a single sensor perceives blind areas and is insufficient in precision in a complex environment.

The invention provides an early warning method based on a driving blind area and related equipment, and the method comprises the steps: determining the driving blind area of a vehicle in the driving process, and recognizing a to-be-detected vehicle in the driving blind area; receiving first driving behavior information of the to-be-detected vehicle, and detecting whether the to-be-detected vehicle has an overtaking intention according to the first driving behavior information; acquiring second driving behavior information of the vehicle, and detecting whether the vehicle has a lane changing intention or not according to the second driving behavior information; under the condition that the to-be-detected vehicle has the overtaking intention and the vehicle does not have the lane changing intention, first early warning information is generated, and the first early warning information is displayed to a driver according to a first display strategy; and under the condition that the to-be-detected vehicle has the overtaking intention and the vehicle has the lane changing intention, generating second early warning information, and displaying the second early warning information to the driver according to a second display strategy. According to the method, the potential collision conflict condition can be predicted in real time, early warning information is sent out in advance, and more abundant lane changing response time is provided for a driver.

The invention belongs to the technical field of subway channel underground excavation deformation monitoring, and particularly discloses a subway channel underground excavation deformation monitoring method based on an ultra-shallow-buried large-flow stratum, and the method comprises the steps: carrying out the geological radar detection of a construction influence range at the early stage of construction, and generating a geological risk distribution diagram; and the geological risk distribution map is used for carrying out risk grade division on the construction influence area to implement differentiated layout of monitoring points, so that on the premise of guaranteeing the monitoring effect, the deformation capture capability of a key area is improved, the monitoring redundancy of a low-risk area is reduced, and the monitoring efficiency is improved. In the construction process, deformation data collected by the monitoring points in all the sub-areas are dynamically analyzed to identify jumping characteristics and stability characteristics of deformation, whether a monitoring blind area or a redundant area exists or not is judged, encryption or migration operation of the monitoring points is triggered accordingly, conversion of the monitoring system from static layout to dynamic evolution is achieved, and the construction efficiency is improved. And the real-time matching between the monitoring point layout and the stratum deformation evolution is effectively ensured.

The invention discloses a monitoring device and a monitoring method for construction organization, belongs to the technical field of intelligent construction safety monitoring, and mainly solves the problems of monitoring blind areas, insufficient fixed visual angle coverage and difficulty in field long-term power supply caused by dynamic shelters in the construction process. According to the technical scheme, a camera is fixed to a double-shaft electric holder with a horizontal rotating and pitching adjusting mechanism, a processor, a communication unit and a battery are arranged in a base, a solar panel is arranged on the top of the base, and an electric lifting column is connected with the base and the holder; the environment sensor group is mounted on the camera; the solar panel is connected with the battery and supplies power to the whole device; the processor calculates a target monitoring path for eliminating a blind area in combination with a preset three-dimensional coordinate of a key area, generates a control signal to drive the holder and the lifting column to move, and dynamically adjusts the path execution frequency and the movement speed of each mechanism according to the electric quantity of a battery and the solar power. The device is mainly used for dynamic dead-corner-free safety monitoring of key areas of a building construction site.

The invention relates to a vehicle infrastructure collaborative perception enhancement method and device, computer equipment and a storage medium. According to the method, the structured occupied main space constructed by the roadside nodes is analyzed, aligned and injected into the vehicle side occupied space in real time, so that the environment states of a blind area, a shielding area and a remote area which cannot be directly observed by the vehicle side are obtained. Time extrapolation is carried out on the dynamic traffic participants and the dynamic traffic participants are mapped to a vehicle side coordinate system, so that position deviation caused by communication delay and sensing time difference can be effectively compensated; spatial resampling and coordinate transformation are executed based on the grid specification of the vehicle-mounted model, and it can be guaranteed that roadside occupation information is consistent with the structure of the vehicle-mounted model; meanwhile, through a fusion mechanism of uncertainty propagation and gating adjustment, reliable weighted absorption of external occupancy priori can be realized in the presence of sensing noise, model errors and positioning errors. Uniform expression of the occupied space of the vehicle side and the road side, time-space consistency alignment and controllable and credible fusion are achieved.

The invention discloses a visual early warning device and early warning method for hearing-impaired people, and the method comprises the steps: presetting a detection range with a user as a center, recognizing a moving object through a millimeter wave radar, and obtaining the motion parameters of the moving object; acquiring a sound signal of a moving object through a microphone array; performing sound type recognition on the sound signal to obtain the sound type and the voice content of the sound signal; constructing a risk assessment model; acquiring a danger level and related information of the moving object; and converting the danger level and the related information into image information and displaying the image information in projection glasses of the user. According to the invention, real-time moving object detection is carried out on the blind area of the back of the hearing-impaired person through the wearable micro radar; and sound signals in the direction of the moving object are collected through the microphone. According to the invention, intelligent guarantee of travel safety of hearing-impaired people is realized, dangerous target information is directly visualized in the projection glasses, active early warning is realized, and the hearing-impaired people can be helped to avoid dangers in time.

A station (STA) in a wireless network. The STA is configured to cause receiving, from a target STA, information associated with a first anchor point (AP) and model training; transmitting, to the first AP, a first request that first AP perform a first ranging with two or more other APs; receiving, from first AP, first ranging data that include location information for first AP; determining a location of first AP based on the first ranging data; training a first model based on the information associated with model training and the location of first AP; transmitting, to first AP, a second request that first AP perform a second ranging with target STA; receiving, from first AP, second ranging data including movement information of target STA; and determining a first predicted position for target STA based on the second ranging data and the trained first model.

The utility model relates to the field of underground garage access safety, in particular to an underground garage access channel safety guidance system. The induction system comprises a controller, at least two displacement sensors and at least two indicator lights; the underground garage access channel is provided with a blind area road section which is provided with at least two entrances and exits. Each entrance is provided with a displacement sensor and an indicator lamp; the controller is connected with all the displacement sensors and all the indicating lamps and used for controlling the indicating lamps at all the entrances and exits to turn on green lights or flicker as green lights when the displacement sensor at only one entrance and exit detects that a moving target enters the blind area road section; and when the displacement sensors of at least two entrances and exits detect that the moving target enters the blind area road section, the indicator lamps of the at least two entrances and exits are controlled to be red or flicker with red lights. According to the utility model, the opposite lane condition of the blind area road section of the underground garage access passage can be well prompted, and drivers and pedestrians are induced to safely pass through the underground garage access passage.

The invention provides a robot obstacle detection method and system in a smart factory environment, and relates to the technical field of obstacles, and the method comprises the steps: determining a strong light region and a high temperature region of a factory according to illumination intensity data and temperature distribution data; taking an overlapped area of the strong light area and the high temperature area as a sensing blind area, and taking the rest area as a non-sensing blind area; according to the metal dust concentration data, the sensing ability grade of each robot is evaluated, and the robot with the sensing ability grade larger than a preset grade and located in the non-sensing blind area serves as a collaborative robot; determining the position and the motion state of an obstacle in the sensing blind area by combining the environment data sent by the cooperative robot and the robot for sensing the blind area; and according to the position and the motion state of the obstacle, constructing an obstacle avoidance map, and according to the obstacle avoidance map, planning an obstacle avoidance path for the cargo robot to pass through the sensing blind area. The robot has the technical effects that the position of the obstacle is accurately detected, and the collision risk of the robot is reduced.

The invention belongs to a positioning method, and provides an indoor and outdoor seamless positioning method, an indoor and outdoor seamless positioning system, electronic equipment and a readable storage medium in order to solve the problems of insufficient positioning reliability, continuity and stability when a modern positioning system, a 5G technology or an inertial navigation system is independently used in a complex environment. The method is used for positioning a moving target in a Beidou and 5G cross environment, the working mode of the moving target in a Beidou and 5G cross area is determined according to Beidou observation information and 5G observation information, different positioning methods are adopted in different working modes, and especially when the working mode is a weak blind area of the cross area, the working mode of the moving target in the Beidou and 5G cross area is determined. Target positioning is carried out by selectively adopting one of Beidou plus inertial navigation positioning, 5G plus inertial navigation positioning and Beidou plus 5G plus inertial navigation positioning; when the working mode is that no blind area exists in the intersection area, target positioning is carried out by adopting Beidou plus 5G plus inertial navigation positioning; and when the working mode is a complete blind area of the intersection area, carrying out target positioning by adopting single inertial navigation positioning.

The invention discloses an automobile driving state blind area monitoring method and a rearview mirror, and relates to the technical field of blind area monitoring. Comprising the following steps of information collection, specifically, sensors and cameras are installed on wheels of an automobile, a steering wheel steering column, an automobile chassis and a steering system respectively, driving state data of the automobile speed, the steering wheel angle, the automobile acceleration and the steering angle and image data around the automobile are collected in real time, and real-time automobile information data are obtained; according to the system, driving state data such as the vehicle speed, the steering wheel angle, the vehicle acceleration and the steering angle are combined, the blind area around the vehicle is monitored in real time through the sensor and the camera, and when the vehicle steers, the blind area monitoring range is adjusted in real time to adapt to the driving direction change; the rearview mirror can display blind area images in real time, the blind area alertness of a driver can be greatly improved, and the traffic accident risk caused by the blind area is effectively reduced.