2495 results about "Information fusion" patented technology

The invention discloses a driver fatigue monitoring device based on multivariate information fusion and a monitoring method thereof. The device comprises a digital signal processor, a camera head with a filter, a rectangular ultrared LED light source module mounted on a car windshield, a speaker module and a sensor module comprising an angular sensor and a pressure sensor, wherein the camera head, the rectangular ultrared LED light source module, the speaker module and the sensor module are respectively connected with the digital signal processor. The monitoring method comprises four procedures, namely eye characteristic identification, view line track, driving activity monitoring and fatigue characteristic judgment which merges the fatigue judgment results of the eye characteristic identification, the view line track and the driving activity monitoring to accurately judge the fatigue states of a driver. The invention utilizes an information merging technology to further develop and improve a fatigue driving detection technology, can objectively, rapidly and accurately judge the fatigue state of the driver in real time and avoids traffic accidents caused by fatigue driving.

The invention discloses a simultaneous localization and mapping (SLAM) method for an unmanned aerial vehicle based on mixed vision odometers and a multi-scale map, and belongs to the technical field of autonomous navigation of unmanned aerial vehicles. According to the SLAM method, an overlooking monocular camera, a foresight binocular camera and an airborne computer are carried on an unmanned aerial vehicle platform; the monocular camera is used for the visual odometer based on a direct method, and binocular camera is used for the visual odometer based on feature point method; the mixed visual odometers conduct information fusion on output of the two visual odometers to construct the local map for positioning, and the real-time posture of the unmanned aerial vehicle is obtained; then theposture is fed back to a flight control system to control the position of the unmanned aerial vehicle; and the airborne computer transmits the real-time posture and collected images to a ground station, the ground station plans the flight path in real time according to the constructed global map and sends waypoint information to the unmanned aerial vehicle, and thus autonomous flight of the unmanned aerial vehicle is achieved. Real-time posture estimation and environmental perception of the unmanned aerial vehicle under the non-GPS environment are achieved, and the intelligent level of the unmanned aerial vehicle is greatly increased.

The invention provides a method and a system for remotely monitoring an electric vehicle so as to solve the problems that the safety use of batteries can be ensured, the service life of the batteries can be improved and the cost of the batteries can be reduced. The method comprises the steps of comprehensively monitoring the state of a complete vehicle, a battery state (particularly a single battery state) and vehicle position information in real time during vehicle operating. According to the system, the information interaction function between different monitoring platforms can be realized and the information fusion and processing of mass data can be finished; the remote services such as fault diagnosis, fault early warning, emergency management and the like can be provided for the electric vehicle by the system; and meanwhile, the scheduling and the navigation service for electric energy supply of the electric vehicle, the energy peak scheduling information service and the vehicle route scheduling informationization service can be further provided by the system.

The invention aims to provide an intelligent glasses device and method used for performing interaction based on multimodal input and capable of enabling the interaction to be closer to natural interaction of users. The method comprises the steps of obtaining multiple pieces of input information from at least one of multiple input modules; performing comprehensive logic analysis on the input information to generate an operation command, wherein the operation command has operation elements, and the operation elements at least include an operation object, an operation action and an operation parameter; and executing corresponding operation on the operation object based on the operation command. According to the intelligent glasses device and method, the input information of multiple channels is obtained through the input modules and is subjected to the comprehensive logic analysis, the operation object, the operation action and the operation element of the operation action are determined to generate the operation command, and the corresponding operation is executed based on the operation command, so that the information is subjected to fusion processing in real time, the interaction of the users is closer to an interactive mode of a natural language, and the interactive experience of the users is improved.

The invention requests to protect a multifunctional V2X intelligent roadside base station system. The system comprises roadside sensing equipment, an MEC server, a high-precision positioning service module, a multi-source intelligent roadside sensing information fusion module and a 5G/LTE-V communication module. An intelligent roadside device integrating C-V2X communication, environmental perception and target recognition, high-precision positioning and the like is designed, and the problem that multi-device information fusion and integration are inconvenient in intelligent transportation is solved. In the system, a C-V2X intelligent road side system architecture and a target layer multi-source information fusion method are designed. Road side multi-source environment cooperative sensing is combined, real-time traffic scheduling of the intersection is realized by using a traffic scheduling module in the MEC server, and communication and high-precision positioning services are providedfor vehicle driving, and finally the target information after fusion processing is broadcasted to other vehicles or pedestrians through a C-V2X RSU (LTE-V2X/5G V2X and the like) according to an application layer standard data format, so the driving and traffic safety is improved.

The invention provides an intelligent information fusion method of a distributed multi-sensor. The intelligent information fusion method includes the following steps: (1) directly collecting signals from a distributed ultrasonic wave receiver, sending the signals to a control center, filtering processing the signals through distributed Kalman filtering, (2) after distributed signal filtering processing, aligning time, space and a related track, unifying sample frequency, namely each measure system is provided with current measured data of each sampling instant, and unifying a space and time coordinate system, (3) judging errors through a track correlation method with the deviation between a future point and an observing point as error judgment criteria, and (4) matching each relative track into a novel track through a fusion method of optimal fusion estimation. By means of the intelligent information fusion method of a distributed multi-sensor, the optimal fusion of numbers of estimated values is achieved through a minimum variance principle, and high-precision indoor positioning of supersonic waves is achieved effectively.

The invention discloses a composite machine tool digital twinning monitoring system, which relates to the technical field of digital twinning. The composite machine tool digital twinning monitoring system creates a digital twinning monitoring system through using a machine tool information module, realizes multi-platform, multi-data and multi-interface communication based on an OPCUA transmissioninterface, and constructs a man-machine interaction module; a multi-field data acquisition module acquires multi-source heterogeneous data in real time by adopting different types of sensors, processes the acquired data based on an information fusion technology to form twin data, and forwards the twin data to a modeling calculation module; the modeling calculation module is used for forming a digital twinning body of a compound machine tool through driving of the twin data in combination with rules such as constraint, prediction and decision; and a personalized decision module monitors and manages entity machine tool equipment in real time by reconstructing and optimizing a machine tool monitoring twinning model in real time. According to the composite machine tool digital twinning monitoring system, the monitoring process of the operation of the compound machine tool is simplified, the monitoring precision of the machine tool system is improved, and the active predictive maintenance of the operation of the compound machine tool is realized.

The invention discloses a potential game-based multi-unmanned aerial vehicle cooperative search method. The method comprises steps: 1, modeling of a multi-unmanned aerial vehicle cooperative search problem is carried out; 2, potential game modeling for a multi-unmanned aerial vehicle cooperative motion and potential game solution in a double log-linear learning method are carried out; 3, a probability map is updated according to sensor detection information, information fusion is carried out on the updated probability map, and a target existence probability is acquired; and 4, uncertainty is updated according to the target existence probability, and multi-unmanned aerial vehicle cooperative search is carried out. The method of the invention can realize multi-unmanned aerial vehicle cooperative search, and comprises steps of cooperative motion based on the potential game, updating of the probability map, information fusion and the like, and due to the self distributed control mode, the calculation is simple, the robustness is strong, and external disturbance can be effectively handled.

The invention discloses a human action recognition method based on two-channel infrared information fusion, and the method comprises the following steps of: collecting a human motion video image through an infrared camera, and collecting a human motion voltage signal through a pyroelectric infrared sensor; respectively carrying out feature extraction on the collected human motion video image and human motion voltage signal, wherein human contour energy is obtained from the human motion video image and spectrum signature is obtained from the human motion voltage signal; respectively carrying out principal component analysis on the human contour energy and the spectrum signature; fusing the principal component analysis results on a feature layer; and carrying out classification and identification on the fused features through the support vector machine method combined with corresponding data in the human infrared action data base. According to the method, multi-level human action information in the infrared image is fully utilized and the human direction information in the output signals of the pyroelectric infrared sensor is fused so as to realize classification and identification on different human actions in different directions and ensure accurate action recognition rate.

The invention relates to a human face living body detection method and device, and the method comprises the following steps: S1, receiving a depth image, a color image, and an infrared image which comprise a human face region, and carrying out the registration; S2, detecting human face areas in the depth image, the color image and the infrared image; S3, preprocessing the face region depth image to realize image enhancement and extract an effective face depth image; And S4, respectively inputting the effective face depth image, the color image of the face region and the infrared image into thetrained cascade depth convolutional neural network, and carrying out accurate face living body detection. The device comprises a computer program for realizing the method. Through multi-source information fusion and the cascade deep convolutional neural network, the problem that a traditional monocular color camera cannot well recover face three-dimensional information is solved, and the accuracyof face recognition is improved.

The invention relates to an air-ground cooperative intelligent inspection robot. The robot comprises a robot platform and an unmanned aerial vehicle, wherein the robot platform comprises a vehicle body, wheels, a driving assembly, a mechanical arm, an environment sensing assembly, a communicator, a robot controller and a power supply assembly, and the unmanned aerial vehicle is in communication connection with a base station through the communicator. The inspection method comprises the following steps that air-ground cooperative multi-robot positioning and mapping is carried out, specifically,sensing positioning calculation is carried out, map creation is carried out, and multi-information fusion positioning is carried out; and air-ground cooperative tracking and control is carried out, specifically, unmanned aerial vehicle flight control design is carried out, robot platform trajectory tracking control is carried out, and unmanned aerial vehicle self-help landing control is carried out. The robot can be ensured to execute given navigation and inspection tasks in an omnibearing and all-weather mode, the technologies of the Internet of Things, artificial intelligence and the like are applied, environment sensing, dynamic decision making, behavior control and alarm devices are integrated, the robot has the capabilities of autonomous sensing, walking, protection, interactive communication and the like, basic, repeated and dangerous security work can be completed, and the security operation cost is reduced.

The invention belongs to technical fields characterized by protocols and discloses an attack occurrence confidence-based network security situation assessment method and system. According to the attack occurrence confidence-based network security situation assessment method and system, a machine learning technology is adopted to analyze network stream data and calculate a probability that networkstreams belong to attack streams; a D-S evidence theory is used to fuse the information of multi-step attacks to obtain the confidence of attack occurrence; and a network security situation is calculated by means of situational factor integration on the basis of security vulnerability information, network service information and host protection strategies; and therefore, the accuracy of assessmentis effectively improved. Since the confidence information of detection equipment is added to the assessment system, the influence of false negatives and false positives can be effectively reduced. Anensemble learning method is adopted, so that the accuracy of confidence calculation can be improved. A network attack is regarded as a dynamic process, and merging processing is performed on the information of the multi-step attacks. Information fusion technology is adopted, so that network environment characteristics such as vulnerabilities, service information and protection strategies are comprehensively considered.

The present invention provides a filtering method for IMU multi sensor data fusion, firstly data is collected, aircraft attitude data can be acquired by an IMU inertial measurement unit comprising a gyroscope, an accelerometer and other multiple sensors, and a sensor output information mathematical model expression formula can be established; output data processing is performed, and the output data processing mainly includes removal of interference information and noises by use of slide average filter and resolution of the rotation angle of each sensor based on a four element method; a high-pass filter and a low-pass filter are combined, PI control parameters are added into a low-pass filtering part, proportionality coefficient variable Kp and integral coefficient variable KI are introduced for design of an error correction negative feedback of a second order complementary filter so as to realize the data fusion of each sensor, and finally attitude angles are outputted. By introduction and setting of the PI control parameters, a negative-feedback-containing second order complementary filter algorithm is designed to fuse the information of each sensor to improve the measurement accuracy and dynamic performance of the system.

The invention relates to a method for constructing a semantic map on line by utilizing fusion of a laser radar and a visual sensor. The method comprises the following steps: acquiring an initialized grid map of a current vehicle, and acquiring distance measurement data corresponding to the laser radar and image data corresponding to the visual sensor; performing target detection processing on theranging data of the laser radar to obtain multi-attribute information of a plurality of first-class detection targets; performing feature extraction and matching on the image data of the visual sensorto obtain multi-attribute information of a plurality of second-class detection targets; fusing the multi-attribute information of the first type of detection targets and the second type of detectiontargets, importing the fused multi-attribute information of the detection targets into a Redis database, generating a high-dimensional grid map serving as a semantic map, and storing the multi-attribute information of each detection target in the high-dimensional grid map in a dynamic database table mode. According to the method, the multi-dimensional semantic information of the dynamic and staticenvironments around the vehicle can be represented online in real time.

The invention discloses an online nondestructive testing (NDT) method and an online nondestructive testing (NDT) device for comprehensive internal/external qualities of fruits. The online NDT method of the invention comprises the following steps: a comprehensive quality evaluation model for the fruits is established firstly by a detection device consisting of a conveying system, a machine vision system, an Near Infrared Spectrum (NIR) system and a grading system, and the fruits performs online uniform motion through the conveying system; the machine vision system acquires the image information of the fruits and extracts the external characteristics of the fruits; the NIR system acquires the spectral information of the fruits; the grading system analyses the spectral information by a pre-established mathematical model, and extracts the internal characteristics of the fruits; and the grading system fuses the internal characteristics and the external characteristics of the fruits by a pre-established information fusion model so as to obtain the comprehensive quality level of the fruits. The method and the device of the invention can detect the internal characteristics and the external characteristics of the fruits simultaneously; a DSP high-speed image processing system is used to handle complex image information, which greatly improves the real-time characteristic of the system; and an information fusion technology is used to carry out online real-time detection on the comprehensive qualities of the fruits.

The invention relates to a system and method for integrally and intelligently controlling water and fertilizer in a field based on multi-source information fusion. The system comprises a weather forecast inquiry receiving subsystem, a weather real-time data collecting control subsystem, a cloud computing platform, a central control unit, an irrigation and fertilization control subsystem, an irrigation and fertilization state monitoring system and an online fault detection system. The system provided by the invention is an automatic control system integrated with the functions of weather forecast inquiry, crop cloud computing platform inquiry, farmland weather real-time collection, solid fertilizer rapid solution, mother solution real-time monitoring regulation, irrigation and fertilization state monitoring, online fault detection, irrigation and fertilization and remote intelligent control. According to the invention, the factors, such as, weather forecast, cloud computing platform, weather real-time collection and growth vigor of the crops in the growth process can be comprehensively considered, corresponding irrigation and fertilization decisions can be made, and thus precise irrigation and precise fertilization can be accurately realized; and the growth vigor of the crops can be described in real time, and the irrigation and fertilization can be performed according to the growth vigor of the crops.

The invention discloses an information fusion method for an airborne inertia/Doppler radar integrated navigation system. The method comprises the following six major steps of: I, establishing an error model of an inertia device and a Doppler radar; II, determining a state variable based on the application of inertia/Doppler integrated navigation on an airborne fixed-wing aircraft; III, establishing an inertia/Doppler radar integrated navigation state equation; IV, establishing an inertia/Doppler radar integrated navigation measurement equation; V, discretizing a Kalman filtering continuous system; and VI, performing Kalman filtering data fusion resolving, obtaining the sub-optimal estimation related to navigation parameters through state estimation, and correcting the inertial navigation and Doppler radar in a closed-loop feedback mode at the same time. The method disclosed by the invention makes full use of the Doppler information and inertial navigation information, puts forward a data fusion scheme for airborne inertia/Doppler radar integrated navigation, effectively solves the problem of a navigation error caused by an imperfect error model, and improves the system precision.