218 results about "EXAMINATION ROOM" patented technology

The invention discloses a driving skill training method constructed based on a diversified virtual examination room, and relates to the technical field of data processing, and the method comprises the steps: constructing a system based on the diversified virtual examination room, constructing a virtual examination room scene to carry out the driving training of a training user, outputting a driving behavior data set in real time, and carrying out the scoring, and analyzing the data according to the driving score, generating a personalized training path in combination with historical data when the driving score does not reach the standard, and training the user to carry out training step by step according to the training path until a preset skill scoring target is achieved. The technical problems that in the prior art, a traditional driving training method cannot dynamically adjust a training path to meet the actual skill requirements of trainees, consequently, training content lacks pertinence and is low in efficiency are solved, the individuation and pertinence of driving skill training are improved, it is ensured that the training content is highly matched with the actual skill requirements of the trainees, and the driving skill training efficiency is improved. And the training efficiency and effect are improved.

The invention provides an examination room multi-source data fusion abnormal behavior intelligent analysis method and system, and relates to the technical field of artificial intelligence, and the method comprises the steps: collecting examination room video and audio data, and carrying out the multi-view skeleton point fusion and sound source positioning to extract features; constructing a hidden Markov model and kernel density estimation to carry out abnormal behavior identification; calculating a seat correlation degree based on a spatial weight coefficient and wavelet decomposition to identify multi-person cooperative cheating; and early warning information is pushed in real time. According to the invention, the cheating behavior identification accuracy is improved, and effective detection of multi-person cooperative cheating behaviors is realized.

The embodiment of the invention discloses an online examination behavior detection method based on edge calculation and multi-modal fusion. The method comprises the following steps: determining an initial group of suspected group cheating according to a cheating behavior co-occurrence condition of each time period in an examination room; constructing a reachable matrix by taking each target examinee in the initial crowd as a row and a column, and if the target examinees in any row and any column have visual reachability, setting the matrix element of the row and the column to be 1; rows or columns with all elements being empty are determined, and for each empty row or column, a neighborhood A in the examination room is delimited with the current target examinee as the center; different first weights are given to the examinees in the visual reachability neighborhood A, and second weights are given to the examinees according to the nearest reachable distances between the examinees in the neighborhood A and other target examinees in the reachability matrix; and enabling the examinee with the maximum product of the first weight and the second weight and the initial crowd to jointly form a final crowd suspected to cheat. According to the embodiment, the group cheating behavior can be automatically identified.

The invention provides a real-time examination room examinee abnormal behavior analysis method, system and device and a medium, and belongs to the technical field of examination room examinee visual recognition. A camera is used for collecting RTSP video streams in an examination room in real time; performing frame extraction processing on the high-density video stream through a preset frame interval; selecting a key frame from the continuous video frames after frame extraction to perform target detection so as to accurately position the spatial position of the examinee; performing examinee abnormal behavior analysis based on the video clip after frame extraction and the examinee position; drawing an abnormal behavior key frame and a video clip according to an abnormal behavior recognition result; manual secondary verification is carried out on an abnormal behavior recognition result, so that the recognition accuracy is ensured; the deep learning model reasoning process is accelerated by utilizing TPU hardware, and the real-time behavior analysis performance is optimized. According to the invention, behavior analysis can be carried out on examinees in an examination room in real time, and the efficiency and accuracy of abnormal behavior identification can be effectively improved.

The utility model relates to the technical field of radiation protection, and discloses an X-ray photography full-isolation radiation protection device, which comprises an X-ray photography full-isolation radiation protection device, a central beam limiting system, a beam limiting device position signal communication port, a detector height signal communication port, a peripheral shielding interlayer and an examination room. According to the X-ray photography full-isolation radiation protection device, automatic switching of the protection position and the protection state is completed in time, the shooting efficiency is not affected, and the staying and positioning time of a subject is not increased. The X-ray radiography full-isolation radiation protection device can provide a rapid, effective and accurate X-ray protection effect for DR equipment shooting, and examinees, accompanying family members and technicians do not need to wear protection equipment such as lead clothes, so that the probability that non-examined parts, especially gonads and the like, are exposed to direct X-ray irradiation and scattered ray irradiation is greatly reduced, and the X-ray radiography full-isolation radiation protection device is suitable for being used in X-ray radiography. Furthermore, effective guarantee is provided for the health of examinees and technicians, and important social benefits and popularization value are achieved.

The invention discloses an offline examination room abnormal behavior monitoring and detecting system based on multi-modal fusion, and relates to an examination room abnormal behavior detecting system, a data processing layer of the system runs on edge computing equipment, and pre-processing and feature extraction are carried out on multi-modal data. And the analysis decision-making layer adopts a graph neural network (GNN) to carry out dynamic weighted fusion on the multi-modal features, carries out time sequence analysis on fused feature vectors in combination with an LSTM model, and identifies abnormal behaviors (such as using electronic equipment and crossing over). And the system integration layer realizes data storage and user interaction through the cloud (Ali cloud OSS), so that invigilators can check abnormal behavior reports in real time. Through the multi-modal data fusion and deep learning technology, the problems that an existing examination room monitoring system depends on single-modal data and is high in misjudgment rate and insufficient in real-time performance are solved, and the examination room monitoring system has the advantages of being efficient, accurate and real-time and can be widely applied to various examination room monitoring scenes to ensure fairness and safety of examinations.

A monoplace hyperbaric chamber design to permit at least 2 ATR (about 30 psi relative) internal pressure which accommodates upright seating and, with stiffeners removed for transport, has dimensions to facilitate the chamber passing through a common door opening width of a doctor's examination room where the stiffeners are attached without disturbing a hermetic seal of the hyperbaric chamber.

The invention relates to the technical field of control management systems, in particular to an AI-based sports examination room system and a sports examination scoring method.The AI-based sports examination room system comprises a plurality of cameras and further comprises an area dividing unit, a track is divided into a plurality of unit recognition areas, and a starting area and a terminal area are divided by combining the distribution positions of a starting line and a terminal line of the track; the preparation identification unit is used for acquiring image data in different starting areas, analyzing and calculating to obtain a target starting line, and marking the starting area corresponding to the target starting line as a preparation area; the project confirmation unit is used for determining a plurality of to-be-determined terminal lines and to-be-determined end point areas corresponding to the preparation areas, analyzing the average speed of the testers passing through the to-be-determined end point areas and the average speed of the testers passing through the two unit identification areas before and after the to-be-determined end point areas, comparing and analyzing the speeds of the testers before and after passing through the to-be-determined terminal lines, and determining a target terminal line; and determining a test item based on the target finishing line and the target starting line.

The invention discloses an offline examination auxiliary system, and belongs to the technical field of offline examination auxiliary equipment, and the system comprises an examination room camera which is used for carrying out the video shooting of an examination room; the acquisition module is used for acquiring examinee registration information and examination requirement information; the detection module is used for performing examination room seat detection on the video key frame in the examination preparation stage and performing examinee face detection and recognition on the video key frame in the examination entrance stage; the processing module is used for arranging examination room seats and generating examination information according to the examinee registration information, the examination requirement information, the detected seats and / or the detected and recognized face information, or checking examinees in an examination entering stage and generating examinee checking results; and the sending module is used for sending the examination information and the examinee checking result generated by the processing module to the invigilator terminal and / or the examinee terminal according to the set requirement at the set time. The method can reduce the manual dependence in the examination process, and guarantees the smooth completion of the examination.

Disclosed are a collective abnormal behavior analysis method and device based on dynamic topology, including acquiring examination monitoring video data of an examination room; selecting key frames from examination frame data, performing face recognition on the key frames in sequence, and labeling the examinee information on the key frames; constructing skeletal topology for each examinee, and continuously monitoring the skeletal topology and the examination monitoring video data; recording suspicious postures of each skeletal topology in sequence, and obtaining an actual spacing distance between skeletal topologies of each of the suspicious postures based on coordinate information of the skeletal topology with suspicious posture in the examination monitoring video data; taking the skeletal topologies of two suspicious postures corresponding to the actual spacing distance as abnormal behavior skeletons, and outputting the examinee information labeled in the abnormal behavior skeletons to complete the analysis of collective abnormal behavior.

The invention provides an examination room digital twinning and intelligent identification system based on a visual large model, and the system comprises the steps: carrying out the digital twinning mapping through a digital twinning mapping module, and obtaining a digital twinning virtual examination room; object behavior actions in the digital twin virtual examination room are captured through a violation judgment module, and an examination room monitoring array is constructed; extracting behavior constraint features of the digital twin virtual examination room based on the examination room monitoring array, and scoring the behavior constraint features through machine learning; when the behavior constraint score is lower than a preset threshold value, the object behavior action is compared with a preset illegal behavior standard, and illegal behavior judgment is achieved; after the violation recording and archiving module judges that violation information exists, corresponding violation video clips are returned to the system interaction interface, and the violation video clips are automatically uploaded to the cloud storage center for archiving, so that abnormal recognition and evidence retention of examinee behaviors are realized, the examination safety is improved, and remote examination room situation comprehensive control is realized.

The invention relates to the technical field of medical instruments, and discloses a disinfection device for a reproductive medicine examination room, which comprises a flowing gas heating mechanism and a rotary reciprocating shaking mechanism, a lower movable disc which is positioned in the vertical disinfection barrel and can rotate, an upper movable disc which is positioned right above the lower movable disc and can generate a longitudinal reciprocating motion effect, and a storage movable plate which longitudinally moves along with the upper movable disc and can support an instrument are arranged in the vertical disinfection barrel. According to the disinfection device for the reproductive medicine examination room, an instrument is effectively disinfected through disinfection gas, the disinfection gas is gas and has the rapid movement and permeation functions, in addition, the instrument can shake in the disinfection process through the device, the instrument can generate a movement gap through shaking, and therefore the instrument can be disinfected conveniently. And the disinfection gas can generate a flowing disinfection effect along the whole surface of the instrument, so that the disinfection range of the instrument is expanded, and the infection risk of the instrument in the subsequent use process is reduced.

An embodiment of the present invention discloses an online examination behavior detection method based on edge computing and multimodal fusion. Among them, the method includes: determining an initial population suspected of group cheating according to the co-occurrence of cheating behaviors in each time period in the examination room; constructing a reachability matrix with each target candidate in the initial population as rows and columns, and setting the matrix element of the row and column to 1 if any target candidate in any row and any column has visual reachability; determining the rows or columns with all elements empty, and for each empty row or column respectively: defining a neighborhood A in the examination room with the current target candidate as the center; assigning different first weights to each candidate in the neighborhood A according to visual reachability, and assigning second weights to each candidate according to the nearest reachable distance between each candidate in the neighborhood A and other target candidates in the reachability matrix; the candidate with the largest product of the first weight and the second weight and the initial population together constitute the final population suspected of group cheating. This embodiment can automatically identify group cheating behaviors.

The invention provides an examination room abnormal behavior detection method and system based on time sequence key points, and belongs to the technical field of human body abnormal behavior detection. The method comprises the following steps: acquiring an examinee image sequence in an examination room video, and extracting time sequence key point data sequence information; the extracted information is input into a trained Transform model, and a single-person feature vector of the examinee is obtained; performing single-person abnormal behavior prediction on the single-person feature vector by using a classifier; and according to a prediction result, constructing a graph structure by taking the single-person feature vector as a vertex and taking the examination room seating table as a topological structure, inputting the graph structure into a graph neural network, and judging whether an abnormal association behavior exists between the examinees in the specific seating relationship or not. The subtle action change behavior characteristics of the examinee can be more accurately captured and recognized, and the detection accuracy is improved. Meanwhile, potential collaborative abnormal behaviors among the examinees can be mined based on analysis of a graph structure, the accuracy of overall abnormal behavior detection is further improved, and the workload of invigilators is relieved.

This invention discloses an end-to-end examination behavior analysis method and system, comprising a video input management module, a video decoding module, an image preprocessing module, a raw frame prediction queue, a raw frame queue, an AI module, an analysis result recording module, and an abnormal event video generation module. It utilizes an end-to-end AI model training and inference scheme, enabling efficient training using large amounts of historical data. In practice, it offers fast processing speed and high efficiency. The end-to-end AI model takes continuous video frames as input and outputs bounding boxes indicating suspected violations after inference. In the post-processing section, the model output undergoes spatiotemporal correlation and filtering to finally generate spatiotemporal location information of suspected violations. It exhibits good scene adaptability; when new scenes are needed or new actions to be identified are added, only new training data needs to be added and retrained to expand the algorithm, saving manpower and improving efficiency.

The present invention relates to an ophthalmology practice with an examination room in which at least one table with eye diagnostic devices arranged thereon and a rotatable and height-adjustable examination chair are arranged.According to the invention, either the table is round or ring-shaped in plan view, wherein the table is rotatable or has a rotatable table top, at least three of the eye diagnostic devices are arranged at a distance from one another on or at an outer edge region of the table, and the examination chair is releasably fixed at an examination position relative to the outer edge region of the table; or the table is arc-shaped in plan view, is fixed at a table position in the examination room and is arranged around the examination chair; and at least three of the eye diagnostic devices are arranged at a distance from one another on or at an inner edge region of the table, wherein at least one of the eye diagnostic devices has a sensor system that is connected to a movement control of the table and / or the examination chair.

The invention discloses an invigilation personnel matching management system based on artificial intelligence. The system comprises an invigilation data acquisition module, an examination room candidate invigilation personnel preliminary screening module, a local candidate invigilation personnel screening module and a global invigilation personnel scheduling optimization module. The invention relates to the technical field of invigilation personnel data processing, innovatively provides a multi-level candidate personnel screening method, and improves the accuracy and flexibility of invigilation personnel matching. A constraint dynamic setting method is provided, and the flexibility of invigilator scheduling rule modeling is improved; an improved graph neural network model construction method for invigilator and examination room matching evaluation is provided, and a more accurate and reliable invigilator and examination room adaptation degree evaluation result is achieved; the improved particle swarm optimization method for the global invigilator scheduling task is provided, and the intelligence and automation degree of the invigilator matching process is effectively enhanced.

The utility model relates to the technical field of heat supply pipe detection, and discloses a heat supply pipeline leakage monitoring device. The objective of the utility model is to solve the technical problems of high manual inspection cost, untimely water leakage point discovery, insufficient detection data accuracy and lack of remote monitoring capability in the prior art. The device comprises a temperature sensor and a liquid level sensor, the detection signal output end is connected with the microcontroller through the signal processing circuit so as to collect temperature and liquid level data of the sensing module, and the microcontroller is connected with the application module through the wireless transmission module; the application module comprises a data processing part and a display interaction part, the data processing part comprises a computer provided with data processing software, and the display interaction part comprises a display screen arranged in the examination room and mobile electronic equipment provided with a client. The system can monitor whether the pipeline leaks or not, reduces energy loss, reduces inspection cost, and is efficient in early warning, high in detection speed and high in precision.

The invention discloses a training method of an attention estimation model and an examination room behavior monitoring method. The examination room behavior monitoring method comprises the following steps: acquiring a head key point, a neck key point, a right shoulder key point and a left shoulder key point of an examinee extracted from a to-be-analyzed image of an examination room monitoring video and an image block intercepted by using a human body detection frame; inputting the key points and the used image blocks into a pre-trained attention estimation model to obtain attention orientation vector estimation values of the examinees; obtaining a target attention orientation vector range; and when the attention orientation vector estimation value of the examinee is not within the target attention orientation vector range, it is judged that the examinee may have a turn-around behavior. According to the method, the requirement for face information is abandoned, and the corresponding attention orientation estimation model is obtained through training of a deep learning regression algorithm from main human body key points. And judging whether the examinee has an unreasonable turn-around behavior or not in cooperation with a use strategy of a specific examination room monitoring scene.

The invention relates to a driver examination room inspection method and system. The method comprises the following steps: before an examination, obtaining examinee examination information and record information of an examination room and an examination vehicle from a driver examination management system; based on the examination table and examination car random distribution rule, whether the number of the started examination table terminals and examination cars meets the examination starting requirement is inspected; inspecting the starting state and the running state of the examination room service equipment; performing safety inspection on the examination table terminal; performing business consistency and service state inspection on the examination car terminal; in the examination process, software and hardware environment change inspection is carried out on part of the in-examination examination table terminal and the in-examination examination vehicle terminal; after the examination is finished, various inspection results before examination, during examination and after examination are uploaded to a driver business management information system. The safety, the stability and the fairness of the examination system are remarkably improved through inspection in three stages, namely, before examination, during examination and after examination.

The present invention relates to an apparatus and method for automatically managing a medical procedure for an outpatient and, more particularly, the apparatus comprising a communication interface, a memory, and a processor operably connected to the communication interface and the memory, wherein the processor is configured to: when it is detected that a patient has entered a preset area, confirm the arrival of the patient and add the patient to a list; when the patient is within a predetermined time from a predicted medical treatment time or when the patient's position in a medical treatment order falls within a predetermined range, obtain the location of the patient's terminal; when the obtained location of the patient's terminal is outside a predetermined radius, request standby for medical treatment; and when it is detected that the patient's turn in the medical treatment order has come and the patient has entered an examination room, request medical staff to perform an identity verification procedure.

The utility model relates to the field of medical examination vehicles, in particular to a 5G mobile intelligent orthopaedic medical vehicle which comprises a vehicle body, a diagnosis inquiry area, a DR examination room, a physical examination area, a treatment area and a multifunctional examination room are sequentially arranged behind a cab in the vehicle body from front to back, and a traction bed examination room and a conventional treatment room are arranged in the treatment area side by side; an intelligent system is further carried on the vehicle and comprises a vehicle-mounted 5G router, a desktop computer, an intelligent central control system, an identity authentication device, a video monitoring system, a remote communication device, a temperature regulation and control system, an intelligent temperature measuring device, a disinfection system and a lighting system, and the vehicle-mounted 5G router is connected with the cloud platform. The system carries orthopedic medical resources to realize quick response to emergency situations, and diagnosis and treatment can be carried out at the first time. The medical vehicle is reasonably provided with five functional areas and is provided with an intelligent system, data and a cloud platform communicate with each other, the structure is compact, layout is reasonable, and accurate and efficient diagnosis and treatment are achieved.

The present invention relates to the technical fields of intelligent education devices and examination management, and particularly to an examination seat arrangement method and system based on an intelligent examination desk. The method includes: collecting environmental data through the intelligent examination desk, and generating an environmental feature matrix in combination with implicit perception technology; dividing the examination room area based on a quantum dot distribution model, and optimizing seat allocation through reinforcement learning to generate optimized seat allocation data; using a multimodal verification module to complete candidate identity verification, binding the verification data with the optimized seat allocation data, unlocking the examination interface and loading examination tasks. The present invention effectively improves the fairness and intelligent level of examination seat allocation, realizes the preferential allocation of candidates with special needs and the dynamic management of the examination process, and has remarkable reliability and convenience.

The invention discloses a motorcycle collision pile rod detection device which comprises a magnet which is arranged under the ground of an examination room and embedded in the ground. The stake rod assembly is arranged over the magnet, a distance exists between the stake rod assembly and the magnet, the stake rod assembly is installed in an examination room and used for generating the posture variation after the stake rod assembly collides with the motorcycle and detecting the posture variation, and the magnet is used for recovering the posture of the stake rod assembly through magnetic field attraction. During an examination, a student controls a motor vehicle, after the stake rod is collided, the stake rod assembly is subjected to the effect of the magnet, and the stake rod assembly can be automatically restored to the initial position, so that the workload of invigilators is reduced, and the examination efficiency is improved. And automatic detection of pile rod collision in a pile examination project can be realized without manual participation. The invention further discloses a detection method based on the device for detecting the collision between the motorcycle and the pile rod.

The invention discloses an intelligent seat arrangement control method, and relates to the field of smart classrooms, and the method comprises the steps: obtaining the seat distribution information of a target examination room; according to the seat sub-distribution information of each group and a target seat arrangement scheme, determining the number of people capable of being arranged in each group under different target seat arrangement schemes; based on the number of people capable of being arranged in each group of all groups of different target seat arrangement schemes, determining the number of people capable of being arranged in the target examination room under the different target seat arrangement schemes; obtaining a target examination number; determining examinee position arrangement information according to the target examination number of people and arrangeable number of people in the target examination room under different target seat arrangement schemes; and sending the examinee position arrangement information to a target terminal. According to the invention, through systematic processing flow and clear algorithm design, automation, intelligentization and visualization of examination seat arrangement work are successfully realized, and the system has wide application prospect and practical value.

The utility model provides an examination room uses answer sheet distribution device relates to distribution device technical field, including the placement box, is equipped with the distribution groove on both sides upper end in the inside of placement box, the inside of distribution groove installs respectively with adjusting mechanism, the inside lower extreme of placement box installs second electric push rod, the output of second electric push rod installs weight sensor, the upper end of weight sensor installs the placement board, the placement board swing installation is in the inside of placement box. The utility model discloses through adjusting mechanism control baffle angle, accurate limit the interval between baffle and distribution groove, cooperate the excess answer sheet of protruding block block, ensure that only push out an answer sheet, avoid multiple, jam and so on, realize the accurate distribution of automation, greatly shorten the time, especially under the scene of many examination rooms synchronous examination, the workload of invigilator is reduced significantly, reduces the occupation of invigilation resource, avoids the influence of the test rhythm of examinee because of artificial distribution time -consuming too long.

The invention discloses a video operation and maintenance analysis system based on artificial intelligence face capture, which relates to the field of data processing and comprises a verification layer, a monitoring layer and a warning layer. The examinee faces in the same examination room are globally collected through the verification layer, the verification layer synchronizes the examinee faces in the obtained examinee identity information and compares the examinee faces with the collected examinee face images so as to complete examinee face verification, the monitoring layer collects examination room images in real time, the faces of all examinees in the examination room images are captured, and the examinee face verification is completed. According to the method, the face of the examinee in the same examination room can be globally collected and compared with the face image in the identity information of the examinee for verification, after the examinee sits according to the seat number, the collected face image is segmented and matched with the identity information for verification, and the face space position transformation form of the examinee is analyzed. The identity of the examinee can be accurately identified, cheating behaviors such as an alternative examination are effectively prevented, the examination room order is maintained, fairness and justice of the examination are ensured, and a solid guarantee is provided for smooth proceeding of the examination.

The present invention discloses a standardized examination room intelligent management system and method based on artificial intelligence, belonging to the field of artificial intelligence technology. It includes: obtaining a target examination room, which includes a number of monitoring devices and examination room seats, obtaining each monitoring device, and obtaining a characteristic examination room seat corresponding to the monitoring device; obtaining a monitoring combination, and determining a correlation coefficient corresponding to the monitoring combination; using the monitoring device corresponding to the picture being displayed on the monitoring large screen as the target device, and determining the picture display duration of the target device; determining the monitoring device corresponding to the next picture display of the monitoring large screen as the next monitoring device, and determining the picture display duration of the next monitoring device. According to the actual situation of the target examination room, the present invention analyzes the characteristic examination room seats corresponding to each monitoring device in the target examination room, which not only effectively improves the efficiency of monitoring screen switching, but also reasonably sets the picture display sequence and display duration of the monitoring device.

The invention relates to an intelligent online patrol comprehensive management platform, and belongs to the technical field of intelligent monitoring and management. The platform adopts a multi-layer distributed architecture and comprises a data acquisition layer, a transmission layer, a platform layer and an application layer. The platform layer integrates a video resource unified access module, an artificial intelligence behavior analysis module, a patrol task scheduling engine, a multi-stage patrol management module and an early warning disposal closed-loop management module. Multi-source video streams are integrated through a standard protocol, video streams of key areas such as examination rooms and test paper storage rooms are analyzed in real time by using a deep learning algorithm, and illegal behaviors such as abnormal number of people and going out with articles are automatically identified and intelligently early warned. Meanwhile, the system supports multi-stage collaborative patrol and disposal process closed-loop management, full-process automation and intelligentization from problem discovery, early warning pushing, task disposal to result feedback are achieved, the supervision efficiency, accuracy and response speed of examination patrol are remarkably improved, and manual dependence is reduced.