174 results about "EXAMINATION ROOM" patented technology

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 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 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.

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 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 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.

The invention discloses a sports test management system based on artificial intelligence, and relates to the technical field of test management, the sports test management system comprises a data acquisition unit, a data processing unit and an application service unit, the data acquisition unit is used for acquiring data during a test, performing real-time video stream analysis by adopting a YOLOv8 algorithm after the acquisition is completed, and transmitting the data to the application service unit; and during acquisition, actions of examinees are captured through a camera, and target detection and attitude tracking are completed in combination with a machine vision technology. The dynamic state of an examination room is detected in real time through full-process intelligent invigilation and a YOLOv8 algorithm, target tracking and identity verification under the scene that multiple persons are examined at the same time are supported, the manual invigilation cost is reduced, automatic scoring and feedback are achieved, scoring is decomposed through actions, the take-off angle, the air posture and the landing distance are captured through YOLOv8, the score is calculated in combination with a physical model, and the intelligent invigilation effect is achieved. And generating examination scores in real time.

1. Name of the product in this design: Multifunctional Integrated Examination Room Equipment (Ronglifang). 2. Purpose of this design: It is used for a portable, mobile, standardized integrated examination room equipment box, which has functions such as candidate identity verification, online monitoring, cheating prevention, electronic clock, broadcasting system, and examination room instruction broadcasting. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key features: the front view. 5. The right view has already been shown in the perspective drawing, so the right view is omitted.

This invention relates to the field of medical information technology and scheduling, and discloses a method for scheduling appointments based on medical ultrasound department data. The method addresses the hidden conflict of existing systems neglecting the reprocessing of intracavitary probes, leading to idle examination rooms but no available probes, and the time drift caused by continuous high-load scanning by operators. This solution collects patient requests and extracts probe status, estimating the expected time to offset individual differences; reads historical probe reprocessing events to obtain the processing time including the cleaning to storage and release cycle; combines the above time parameters to extrapolate the actual available time for each candidate appointment; further, it calculates the comprehensive cost of the candidate appointments based on historical delay results, selects the scheme with the minimum cost for dynamic scheduling, and corrects the historical average based on measured data in a closed-loop manner. This invention effectively alleviates queuing deadlock and improves the accuracy of resource scheduling in ultrasound departments.

1. The name of the design product: signal shield. 2. The use of the design product: for shielding or interfering with various communication signals in the examination room. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view 1.

The application discloses a kind of cloud examination room control method, device, equipment and storage medium, the method includes: determining and the same target test question of pre-set standard test question difficulty and the content different target test question, and target test paper is generated based on the target test question;Monitor the behavior state when examinee answers the target test paper;According to the behavior state, it is judged whether the examinee exists cheating abnormal behavior, and according to the judgment result and the answer condition of the examinee answering the target test paper, control is carried out to cloud examination room.Through the above-mentioned mode, target test question is determined and target test paper is generated based on target test question, the behavior state when examinee answers is detected and it is judged whether there is cheating abnormal behavior, and then according to the judgment result and the answer condition control, compared with the existing examination room control method, the above-mentioned mode can accurately judge the behavior of suspected cheating in examination room, and can generate the test paper of different content and the same difficulty, further ensure the fairness of examination.

The invention provides a detection method for identifying abnormal change of the number of people in an examination room based on examinee positions, and relates to the technical field of computer vision processing. The detection method comprises the following steps: performing model training based on an examination room historical monitoring video to obtain an examination room examinee position detection model, generating an examination room state diagram based on a to-be-detected examination room monitoring video, obtaining the number and positioning of examinees in the examination room state diagram based on the model, and establishing an examinee sequence; constructing a reference examinee sequence, and generating a to-be-detected feature vector containing the number of examinees leaving the examination room in each time period based on the reference examinee sequence; and acquiring a feature vector data set of the change of the number of people normally leaving the examination room based on the historical monitoring video of the examination room, calculating the mahalanobis distance between the to-be-detected feature vector and the centroid of the feature vector data set, and judging that the to-be-detected examination room is abnormal when the mahalanobis distance is greater than the threshold value. By implementing the technical scheme provided by the invention, multi-person cheating behaviors except for examination room monitoring can be distinguished in an assisting manner.

The application discloses an examination room abnormal behavior detection method based on an improved YOLOv7 model, comprising the following steps: S1, frame processing is performed on an existing examination room monitoring video to obtain examination room picture data; S2, the examination room picture data are sequentially preprocessed and labeled to obtain an examination room abnormal behavior data set; S3, an improved YOLOv7 network model is constructed, an activation function SiLU is replaced by FReLU, a Gn-ASPPCSPC module is used to replace an ASPPCSPC module, a Gn-MP module is used to replace an MP module, and a SIoU loss function is used; S4, the improved YOLOv7 model is trained by using the examination room abnormal behavior data set, and an optimal performance model is obtained after training; and S5, the optimal performance model is used to identify newly obtained examination room pictures to detect abnormal behaviors appearing in the examination room. The detection method solves the problems of the original YOLOv7 network model, such as lack of ability to capture feature space correlation and inaccurate target positioning in a complex background.

The present invention provides a supervision method, device, storage medium and electronic device for preventing cheating in examinations. The supervision method for preventing cheating in examinations includes: pre-acquiring reference photos of each candidate assigned seats in a target examination room, constructing a first mapping relationship between the reference photos of the candidates and the candidate position information of the candidates, and constructing a second mapping relationship between the acquisition parameters of a camera and the position information; collecting candidate photos in the target examination room, querying the second mapping relationship according to the current acquisition parameters for the current acquisition, and obtaining the acquisition position information mapped by the current acquisition parameters; querying the first mapping relationship and obtaining the candidate reference photos corresponding to the candidate position information mapped by the acquisition position information; and supervising the target examination room based on the candidate photos and the candidate reference photos. The supervision intensity of online examinations can be improved.

The invention discloses a working method of a hospital transportation system, and belongs to the technical field of medical information. The medical advice is issued through the his system, and the transportation work order is created in the hospital transportation system according to the type of the medical advice; then, the system automatically sends the work orders according to teams and regions, a transporter receives the work orders according to the shifts, and the transporter transports the patients to an examination room according to the positions of the patients in the order receiving information and examination items on the work orders; after the patient arrives, registration is completed through an appointment registration system; when the examination is finished, the examination system can send an examination completion prompt to a hospital transportation system, a transporter sends the patient to the next examination room, execution is carried out circularly until all examination items on the work order are completed, finally the patient is sent back to a ward, meanwhile, the transportation system is strongly associated with a his nurse station system, and it is guaranteed that the patient is conveyed in a closed-loop mode in the whole process. Through docking with each system of the hospital, the medical experience of the patient and the high efficiency and specialty of hospital transportation are effectively improved.