155results about How to "Realize intelligent analysis" patented technology

The invention discloses an IP camera in a video monitor system, a video monitor system, and a signal processing method of the IP camera. The IP camera can be used for detecting and tracking a moving object in a monitored scene represented by a digital video signal at the same time when acquiring the digital video signal, so as to determine whether to send an alarm or not according to the tracking data analysis, thereby achieving intelligent analysis while video monitoring. For the video monitor system and the IP camera, a moving object detection and tracking module and an intelligent video analysis module can be embedded in the hardware of the IP camera in a software manner to facilitate the function expansion and updating of the video monitor system.

The invention discloses a video monitoring intelligent early-warning system and a video monitoring intelligent early-warning method on the basis of target space relation constraint. The system comprises a video acquisition module, a target component intelligent analysis functional module, a video content visual analysis module, a general behavior rule sample database and an alarm module. On the basis of behavior comprehension on target components, aiming at spatial correlation between targets, the system carries out behavior characteristic analysis, evolution and classification, establishes a spatial correlation mode sample library, implements detection and identification on abnormal behaviors, can more effectively and accurately carry out identification and judgment on emergencies and can lock an abnormity trigger point to provide evidence for post-mordem forensics. The system introduces target space relation constraint, divides a video scene region to complete defining related concepts of the target components of a video, eliminates a certain fuzziness and faults in space semantic information, solves the problems of incompletion and inaccuracy in video content analysis and is more accurate and more efficient to detect abnormal events in a video monitoring range.

The invention discloses an anti-theft monitoring system for electric power facilities. The anti-theft monitoring system for the electric power facilities mainly comprises a outdoor monitoring host, a communication server, a data bank server, a WEB server, a multistage alarm receiving host, a user host and a cell phone terminal. A outdoor terminal is installed on a transformer pole and powered by a three-phase alternating current, and is connected with a various function detection module. The communication server, the data bank server and the WEB server are located at a monitoring center; the outdoor terminal monitors the environmental conditions and various operating parameters to guarantee the safety of the transformer, and transmits data with a communication server of the monitoring center through a GPRS (General Packet Radio Service) wireless network access way and keeps in touch with the communication server; the alarm receiving and management contact with a control center server through an internet access. The anti-theft monitoring system for electric power facilities can accurately analysis and judge the conditions of people approaching, facility vibration, facility slant and the current and voltage of the transformer, and is suitable for popularization and application.

The invention discloses a method and a system for monitoring underground engineering portrait information and monitoring information safely. The system comprises a monitoring measurement information processing system, a portrait information processing system, a comprehensive safety monitoring analyzing module, an early-warning and warning output module and a next-stage geologic structure reporting module. The monitoring measurement information processing system and the portrait information processing system are respectively connected with the input end of the comprehensive safety monitoring analyzing module, and the output end of the comprehensive safety monitoring analyzing module is respectively connected with the next-stage geologic structure reporting module and the early-warning and the warning output module. The method and the system for monitoring the underground engineering portrait information and the monitoring information safely acquire monitoring measurement information and portrait information in real time, analyze safety level of acquired data, perform early warning and warning on dangerous situations and forecast geological situations at the next stage, and have the advantages of performing remote control, timely finding and recording abnormal data information and warning data information, being convenient for technical personnel to analyze, and the like.

The invention provides a test case generation method based on the data code separation technology. The test case generation method comprises the following steps: S1, pre-processing program source codes and generating a program control flow graph; S2, generating a path matrix A according to the program control flow graph and setting corresponding priority factors Beta to all predicates in all paths P; S3, reversely ordering the paths according to the priority factors Beta to obtain a matrix A'; S4, as for the matrix A', selecting a path Pi to calculate test data, and finishing path selection when the order of a matrix A'' constituted by the selected path Pi equals to the order of the path matrix A; S5, generating test data according to the types of predicates in the path Pi; and S6, generating a test case according to the test data and the path Pi. The test case generation method realizes intelligent code analysis, reduces working hours for manual design of both test cases and test data, shortens the test script writing time and improves the test efficiency.

An embodiment of the invention discloses an intelligent interrogation system based on XGBoost disease prediction and a method. The system comprises a client and a service end which are connected through a network. The client comprises an interrogation module and a display module. The service end comprises a data processing module, a data storage module and an XGBoost disease predicting module. Through inputting patient symptom information which is acquired by a client into a trained XGBoost multi-class model, a disease probability predicted value and predicted disease information are output. Furthermore the patient can directly check the related information on the client. Based on machine learning and big data technology, a self-service diagnosis service of the patient can be realized. Thesystem and the method further have advantages of supporting intelligent analysis and prediction on mass patient data, realizing high accuracy and high timeliness in prediction, and realizing simple operation and low cost.

The invention discloses a network event processing method and device. The method comprises the steps that log information of network equipment is collected; events in the log information are analyzed, the events are stored in an event data base; correlating analysis is carried out on the events in the event data base through a correlating analysis algorithm, connection between the events is found; classifying is carried out on the connected events through a classifying algorithm, categories of the events are obtained; processing modes corresponding to the events after classifying are determined. The problem caused by the fact that network behavior is analyzed through a rule model aiming at correlated technologies is solved, and intelligent analysis on the network events is achieved.

The present invention relates to a mobile phone communication monitoring system device of a controllable cradle head. The device comprises a communication monitoring mobile phone device, a cloud server, an intelligent control mobile phone terminal and the controllable cradle head. The communication monitoring mobile phone device is installed on the controllable cradle head and is connected to the cloud server to carry out data transmission and data processing. The cloud server is connected to the intelligent control mobile phone terminal which is used for remotely controlling the controllable cradle head to realize cradle head rotation to capture a face image and searching best video communication and monitoring angles. A camera of the communication monitoring mobile phone device carries out automatic focusing, and the clarity of the face image is improved. The mobile phone communication monitoring system device is combined with the cloud platform, the storage capacity and the safety factor of the information are improved, and the information fusion and intelligent analysis of a communication video and a monitoring video image are realized.

The invention provides an intelligent medical detection method and an intelligent medical detection system based on an Internet cloud service technology. The method comprises the steps that 1, patient information is stored in a cloud server, and a detection device gives a detection result corresponding to the patient information; 2, a ZIGBEE transmission module transmits a ZIGBEE signal including the detection result; 3, a ZIGBEE receiving module monitors a received wireless signal for judging that whether the ZIGBEE signal having the detection result is included in the wireless signal; 4, if the ZIGBEE signal having the detection result is not included in the wireless signal, monitoring is continued, and if the ZIGBEE signal having the detection result is included in the wireless signal, the detection result of the patient is extracted after analyzing the ZIGBEE signal; 5, the detection result information is packaged into an Internet signal, then the Internet signal is encrypted and sent to the cloud server; and 6, the cloud server sends the detection result to a mobile terminal through the Internet. According to the method, the medical detection report is paperless, privacy of the personal information of the user is protected, the detection data can be monitored in real time and intelligently analyzed, remote medical guidance can be implemented, and statistics and analysis of big clinical medical data can be achieved.

The invention discloses a cluster scene intelligent monitoring method and system based on cluster trajectory classification. The method comprises the steps of first, adopting a key point tracking algorithm for obtaining a motion trajectory of a moving object in a monitoring video; then, adopting a spanning tree algorithm of a global uniform Markov random field model for connecting fragment trajectories with the time-space coherence to obtain a complete trajectory tree; then, adopting a confidence-based correlated topic model for learning middle layer features in the trajectory tree and redescribing the middle layer features; then, adopting a multi-class support vector machine classifier for classifying the trajectory tree on the basis of the trajectory tree described by the middle layer features; finally utilizing the confidence-based correlated topic model and a model of the multi-class support vector machine classifier and adopting a minimization information entropy algorithm for classifying the fragment trajectories. The complete cluster scene intelligent monitoring system is designed to replace manual analysis on cluster scene monitoring videos, manpower resources are saved, and the system robustness is good.

The invention discloses a smart grid big data-based electricity price execution checking method. The method comprises the following steps: 1) processing the power consumer power consumption data by utilizing a data pre-processing module; 2) constructing a power consumer typical power consumption track expert library by utilizing a clustering algorithm; and 3) realizing the electricity process execution checking of the power consumers by utilizing a distance discriminant analysis algorithm. According to the clustering algorithm, an initial clustering center can be determined through the density parameters of sample points; by utilizing a method of combining the cluster evaluation index and the score evaluation index, the optimum number of clusters can be determined, so that a power consumer typical power consumption track curve is formed; according to the distance discriminant analysis algorithm, electricity price execution checking discrimination is carried out on new power consumers, and through calculating the electricity price abnormal suspected coefficient, a list of the final the electricity price execution abnormal consumers is determined. According to the method, the intelligent analysis and identification of the power consumption behavior tracks can be realized, the remote online diagnosis of the consumer electricity price execution can be realized, and the pertinence, correctness and timeliness of the marketing checking can be improved.

The invention discloses a low-background spectrum unscrambling method based on a sodium iodide detector. The method comprises the following steps: (1) a gamma detector after energy calibration actually measures a radionuclide spectrum and a natural background spectrum, and noise reduction is carried out; (2) a deconvolution algorithm is adopted to process a gamma energy spectrum after noise reduction; (3) a peak searching algorithm carries out searching on all potential peak positions of the gamma energy spectrum after noise reduction, and a peak position list is acquired; and (4) the peak position list information and a nuclide library are combined to be together inputted to a fuzzy logic system, the system gives the peak position recognition confidence for any nuclide characteristic peakin the nuclide library, constraints are set to further adjust the peak position recognition confidence, and thus, a nuclide list and the nuclide recognition confidence are acquired. The low-background spectrum unscrambling method based on the sodium iodide detector has the advantages of accurate peak position reduction, remarkable improvement of energy resolution, decomposition of an overlapped peak, low error recognition rate, accurate background nuclide analysis and accurate low activity nuclide analysis, and can be used for nuclide recognition and activity calculation for radiation monitoring equipment such as a gated radiation monitor and a nuclide recognition instrument.

The invention relates to an expressway traffic information display method, device and system based on an intelligent lamp post. The method comprises the steps: collecting vehicle information, determining a road section for displaying expressway traffic information, interactively transmitting expressway traffic information, and tracking images of a vehicle and an adjacent vehicle; analyzing the visual field of a driver of the vehicle according to the tracked images of the vehicle and the adjacent vehicle, and displaying highway traffic information according to the visual field of the driver; evaluating the road condition in front of the vehicle; and displaying the highway traffic information according to whether the front road is abnormal or not. According to the invention, real-time traffic information guidance is provided for drivers for different vehicles through the intelligent lamp post; the intelligent lamp post cooperates with the guardrail screen and the ground sign display screen in the expressway section covered by the intelligent lamp post, so that traffic monitoring blind spots are perfected, drivers can obtain traffic information conveniently, the traffic accident rateis effectively reduced, and the traffic efficiency of the expressway is improved.

The embodiment of the invention discloses a driver-vehicle association processing method and device. The method comprises the following steps that: the first positioning information of each mobile terminal on a road surface and the second positioning information of each intersection are obtained, inter-object distances between the mobile terminals are calculated; clustering analysis is carried outon the inter-object distances, so that a plurality of mobile terminal classes can be obtained, and driver terminals in the mobile terminal classes are determined; the driving tracks of vehicles are generated according to the second positioning information and the first positioning information of each driver terminal; and the license plate information of each vehicle shot at each intersection is acquired, and the vehicles with the license plate information are associated on the basis of the driving tracks, so that driver-vehicle association is completed. According to the method and device, evidence acquisition is facilitated through the first positioning information; the driver terminals are recognized through clustering analysis; the intelligent analysis of the behaviors of the vehicles is achieved; judgment on suspicious vehicles, black operation vehicles and the like is completed; and matching is performed on the license plate information of each vehicle shot at each intersection, the driving tracks of the vehicles are applied, and therefore, accurate matching can be achieved, and accurate driver-vehicle association is realized.

The invention discloses front-end equipment in a video monitor system, a video monitor system, and a signal processing method in the front-end equipment. Moving objects in a monitored scene represented by digital video signals are detected and tracked at the same time of acquiring the digital video signals, and the tracking data is analyzed to obtain a result of whether or not to send an alarm, thereby achieving intelligent analysis while achieving video monitor. For the video monitor system and the front-end equipment, a moving object detection and tracking module and an intelligent video analysis module can be embedded in the hardware of the front-end equipment in the software manner so as to facilitate the function expansion and updating of the video monitor system..

The invention relates to an intelligent navigation device based on cloud computation and used for a scenic area. The intelligent navigation device comprises an intelligent entrance ticket bracelet and is characterized in that the navigation device further comprises a scenic spot access control system which is connected to a cloud data center, the cloud data center is connected with a scenic spot program list timetable module, a scenic area route planning module, a tourist car positioning and scheduling module, a scenic spot carrying capacity module and an intelligent terminal module, and the intelligent terminal module is connected with an electronic display terminal and an intelligent client terminal. By means of the intelligent navigation device, scenic spots and routes in the scenic area can be intelligently analyzed, tourists can play according to the routes analyzed by the cloud data center, time is saved, and jamming is avoided.

A system used or realizing intelligent analysis of computer hang-up is prepared as utilizing monitor module to store hardware and driving program as well as application software information of computer into databank of computer, utilizing search module to search out corresponding information in databank of computer according to information key word obtained from journal file generated at time of computer hang-up then to provide relevant settlement plan.

The invention relates to a semi-supervised neighbor propagation learning and multi-visual dictionary model-based intelligent video analysis method. The method includes the following steps that: key video frames are extracted based on a sample-and-hold strategy; the key frames are converted into a grayscale image, and the grayscale image is averagely segmented into a plurality of image blocks, and OM feature vectors are generated based on the sequence of the average brightness of the image blocks; a video sample is divided based on AP clustering, so that mutually exclusive video sub clusters can be formed; the category labels corresponding to each sub cluster are determined according to the video sub clusters obtained through the division of the AP clustering, and a multi-visual dictionary is constructed; the category label of a video to be detected is judged online according to the minimum distance judgment criterion; and closed-loop feedback adaptive reconfiguration learning is adopted to reconstruct a multi-visual dictionary adaptive to a new environment, so that the category label of the video to be detected can be re-judged. With the method of the invention adopted, the problem that efficiency and precision in key frame extraction cannot be taken into account simultaneously can be solved, and enhanced video features have very high robustness for approximate global linear change; and accurate and intelligent detection adaptive to video mode change can be realized.