178 results about "Person location" patented technology

The invention provides a lightweight AI personnel perception method and system based on a millimeter wave radar, and relates to the technical field of personnel perception, and the method comprises the steps: carrying out the phase compensation, amplitude calibration and bidirectional combined filtering processing of a millimeter wave echo signal, and constructing three-dimensional space point cloud data. Then, constructing a spatial distribution matrix based on the point cloud data, calculating the center position of a point cloud cluster, establishing an adaptive sampling radius to extract point cloud features, and calculating a motion vector and attitude parameters; and finally, inputting the motion vector and the attitude parameter into a double threshold judgment module, judging whether a person exists in the target area, generating a person position thermodynamic diagram based on the center position of the point cloud cluster, and outputting a person perception result. According to the method, the calculation complexity is reduced, the real-time performance and accuracy of personnel perception are improved, and the method is suitable for smart home, security monitoring and other scenes.

The invention relates to a bridge crane operation dangerous area personnel intrusion detection method and system, and the method comprises the steps: obtaining the real-time position and speed data of a hoisted object through a sensor, analyzing the motion trail of the hoisted object through a deep learning algorithm, and obtaining the prediction result of the motion trail of the hoisted object; calculating a dangerous area boundary by adopting a dynamic model according to a hoisting object motion trail prediction result in combination with load mass and rope length data, and determining a dynamic dangerous area range; acquiring image data of an operation area through an image acquisition device, and identifying personnel positions in the image to obtain personnel position data; and when it is judged that the personnel enter the dynamic dangerous area range according to the personnel position data, an early warning signal is generated, a three-dimensional visualization technology is adopted to superpose the early warning signal to the field real-time image, visual early warning information is obtained, and the visual early warning information is displayed through a display device. According to the invention, dynamic and accurate prevention and control of the dangerous area are realized through multi-dimensional technology fusion.

The invention provides a real-time energy-saving control method and device for a central air conditioner and a readable storage medium. The method comprises the steps that real-time position information of personnel in an area where the central air conditioner acts is obtained; according to the real-time position information of the personnel, the number of the personnel in each sub-area in the area where the central air conditioner acts is determined, and each sub-area correspondingly has at least one central air conditioner air outlet; central air conditioner control parameters of the corresponding sub-areas are determined according to the number of people in each sub-area; and the movement information of the personnel is obtained in real time, and the central air conditioner control parameters of all the sub-areas are adjusted in real time based on the movement information of the personnel. An intelligent air conditioner control strategy is adopted, the air speed of the air conditioner is intelligently adjusted according to the position of the person and motion prediction, the dynamic control method can optimize energy consumption, and meanwhile the comfort degree of the environment is kept.

The invention relates to the technical field of intelligent lighting control, in particular to an LED lamp energy-saving control method and system, and the method comprises the steps: obtaining environment data and user data; constructing a scene knowledge graph, and pre-storing illumination parameters of different scenes; performing standardization processing on the environment data and the user data, and obtaining a state vector in combination with the scene knowledge graph; inputting the state vector into a three-dimensional comfort level model to calculate a comprehensive comfort level score; if the comprehensive comfort level score is lower than a target threshold value, an illumination adjustment strategy is output through a dual-network illumination adjustment agent, the LED lamp is adjusted according to the illumination adjustment strategy, and the illumination adjustment strategy comprises light intensity adjustment, color temperature adjustment and light beam angle adjustment; and if the comprehensive comfort level score is higher than a target threshold value, lightweight light intensity gradient optimization is carried out, and the light intensity of the LED lamp is dynamically adjusted according to the position of the person. Therefore, the problems of insufficient environmental adaptability, lack of comfort consideration and the like in the prior art are solved.

The invention relates to the technical field of image recognition, in particular to a specific target person behavior recognition method fusing a camera and a UWBAOA base station, which comprises the following steps: based on target person position data of the camera and the UWBAOA base station, the target person position data comprises node information of a starting point, a transfer point, speed change and a stay position in a target person movement track; motion features are extracted, the transfer trend of the nodes is analyzed, the feature membership degree of each behavior node is obtained in combination with motion intensity data, and a fuzzy category affiliation result is generated by sorting and classifying the feature membership values. According to the method, the motion trail of the target person is analyzed, node information such as the starting point, the transfer point, the speed change and the stop position in the motion path is divided into a plurality of segments, and the fuzzy category affiliation result is generated through membership calculation and sorting, so that deep classification of the behavior pattern of the target person is formed; and the accuracy of behavior recognition is remarkably improved.

The invention provides a production park personnel positioning method and system, and the method comprises the steps: training a personnel behavior model through obtaining the historical motion track and historical behavior data of personnel in a production park; acquiring historical environment dynamic change data in the production park, and training an environment prediction model; the method comprises the following steps: acquiring multi-source data through each sensor, and preprocessing the multi-source data, the multi-source data comprising Wi-Fi signal strength indication data for representing position information of personnel in a production park, radio frequency data, visual data and inertial measurement data; according to a Kalman filtering algorithm, fusing the preprocessed multi-source data to obtain a first position; and calculating the position probability distribution of the personnel in the production park by adopting a Bayesian positioning algorithm in combination with the first position and the output results of the personnel behavior model and the environment prediction model, and determining the target position, thereby effectively realizing the accurate and real-time positioning of the personnel in the production park in the complex environment.

The invention relates to the technical field of mine monitoring, and provides an intelligent mine safety monitoring system and method, and the system comprises a path network modeling device, a multi-source risk monitoring device, a personnel positioning and tracking device, a dynamic path updating device, and an intelligent evacuation guiding device. When any path risk level exceeds a preset safety threshold value, triggering an emergency evacuation instruction: calculating and generating a personalized optimal evacuation path for each person based on the currently updated three-dimensional topology model and the person position information; outputting evacuation information; the evacuation information comprises an emergency evacuation alarm of a whole mine broadcast level; and a real-time dynamic pointing instruction facing each node, the pointing instruction being generated according to the personalized optimal evacuation path and being presented through a physical indication device deployed at the node or a terminal device carried by a person. According to the technical scheme disclosed by the invention, workers in the mine can be timely guided to be evacuated.

The invention provides a fence crossing behavior identification method and apparatus, a storage medium and an electronic device. The method comprises the steps of obtaining video data including image data of a plurality of workers; detecting a target person in the video data by adopting a Center Net network, and obtaining a detection frame representing the position of the target person in the next frame; predicting the position of the target person at the next moment according to the current frame image of the video data by adopting a self-adaptive dynamic Kalman filtering algorithm to obtain a prediction frame; and in combination with the detection frame and the prediction frame, obtaining a target position frame of the target person at the next moment, and determining that the target person has a fence crossing behavior under the condition that the target position frame and the fence marking area at least partially coincide. According to the method, the recognition cost is reduced based on deep learning, the working efficiency is improved, the behavior of crossing the fence can be strictly prevented, meanwhile, a more advanced detection strategy is adopted, the calculated amount is greatly reduced, a motion prediction module is added, and the early warning function is achieved.

The invention relates to the technical field of Internet of Things, in particular to a dynamic personnel positioning and monitoring method based on an Internet of Things laboratory, which comprises the following steps of: performing high-precision real-time tracking and positioning on laboratory personnel by adopting a high-precision positioning technology and combining a laboratory layout; processing video data monitored in the laboratory by using a deep learning algorithm, identifying actions of laboratory personnel, and analyzing a behavior pattern based on a time sequence; environmental parameters in the laboratory are monitored in real time, receipts are collected in a unified mode through the Internet of Things gateway, and the receipts are uploaded to the cloud server after being preliminarily processed through edge calculation. By integrating a high-precision positioning technology and a deep learning algorithm, the scheme realizes real-time tracking positioning and behavior recognition of laboratory personnel. Therefore, the accuracy and efficiency of laboratory personnel management are improved, and potential safety hazards can be found and dealt with in time. The high-precision positioning technology ensures the accuracy and the real-time performance of the personnel position.

The invention provides a man-machine interaction safety dynamic early warning method based on digital twinning and behavior prediction, and the method comprises the steps: S1, collecting the real-time data of a working site through a sensing layer, and enabling the data to comprise the personnel position, equipment state and environment information; s2, constructing a digital twin model based on the acquired data, wherein the model maps the dynamic state of a working site in real time; s3, generating a personnel behavior track and an equipment action range through a prediction algorithm, and calculating a dynamic risk field to evaluate space-time conflicts; s4, according to the risk value of the dynamic risk field, triggering a multi-stage early warning mechanism to reduce the risk of the operation field; and S5, displaying the real-time state and risk information in the digital twinborn model through a visual interface. According to the invention, through deep fusion of digital twinning and dynamic risk prediction, real-time monitoring and accurate prevention and control of the safety risk of the operation site are realized, and the safety management efficiency and the operation safety are greatly improved.

The invention discloses an electric power personnel illegal behavior identification method and system based on multi-frame multi-level joint discrimination, which is applied to the technical field of electric power operation safety supervision, and comprises the following steps: detecting the positions of all personnel in each frame of image in a video stream, adopting a ByteTrack algorithm as a core tracker, introducing a score grading matching strategy, and carrying out classification matching on the positions of all personnel in each frame of image in the video stream; taking the weighted sum of the spatial consistency and appearance feature similarity of the new detection frame as a final association degree quantity, distributing a unique identity code for a successfully associated personnel target, and recording track information in continuous frames; performing illegal behavior classification and illegal article detection on each frame of personnel area image; and calculating a joint confidence score of a frame where the personnel region image with the behavior category and the article category having a logic correspondence relationship is located, counting the number of frames exceeding a preset joint confidence threshold in each power personnel trajectory, and calculating an illegal behavior existence rate to judge an illegal behavior. According to the invention, the illegal behavior identification precision of the power personnel is effectively improved.

The invention provides a method, a system and equipment for positioning global personnel of a building based on digital twinning. The method comprises the following steps: acquiring video data shot by each camera in a multi-camera system; obtaining a mapping relation among the world coordinates, the pixel coordinates and the camera parameters; key point detection is carried out on personnel in the video to obtain personnel pixel coordinates; establishing a conversion relation between each camera coordinate system and a global world coordinate system based on multi-camera attitude transfer, and unifying personnel positions in the multiple cameras to the global world coordinate system; performing matching optimization on the same person observed by different cameras in the global world coordinate system based on distance constraint and epipolar constraint; finally, multi-source information fusion and personnel position and quantity perception under a global perspective are realized. According to the invention, the information shot by a plurality of monitoring cameras can be fused, the digital twinning technology is combined to realize the intelligent perception of the position and number information of people in the building scene, and the precision and real-time performance of crowd monitoring are improved.

The invention discloses a TDOA-based Chan-Taylor underground personnel target positioning method, system and device, and the method comprises the steps: building a reference coordinate system, and deploying N base stations and a target node; a TDOA positioning model is established, and the TDOA positioning model takes one base station as a reference base station, takes the positions of the other two base stations as focuses and takes a distance difference as a long axis; preliminarily estimating the position of an underground target person through a Chan algorithm; based on a preliminary estimation result, estimating the position of the underground personnel by using an improved Chan-Taylor weighting algorithm; an estimation result of the Chan-Taylor weighting algorithm is used as an observed quantity, and a Kalman filter is used for filtering; inputting the filtering result into a target function of a TDOA positioning model, and when the target function is smaller than a preset threshold value, outputting the result as an optimal position estimation value; compared with a traditional method, the method has higher positioning precision and lower calculation complexity, a good positioning effect is achieved, and high practicability and popularization value are achieved.

The invention relates to the technical field of field investigation, in particular to a land field investigation system. The method comprises the following steps: firstly, acquiring the position of an investigator through a positioning module, and then calling peripheral sampling point information through a data retrieval module; the user interface module generates a visual map, and the survey auxiliary module presents sample point features on the map and assists in judging the terrain; the sampling point state management module updates the sampling point state according to the comprehensive information; and finally, a local database stores survey data, and a data synchronization module ensures real-time synchronization with a remote server, so that the survey efficiency and accuracy are improved, and flexible adaptation and multi-person cooperation in a complex environment are realized.

The invention relates to the technical field of elevators, in particular to a quick positioning and information interaction system for elevator emergency rescue, which comprises a personnel detection module, a fault detection and judgment module, a quick positioning module, an information interaction module and a paperless operation module, the personnel detection module and the rapid positioning module work cooperatively, so that rescue personnel can rapidly determine the position of a trapped person and plan an optimal rescue route, the rescue response time is greatly shortened, the pain and danger of the trapped person are reduced, the information interaction module realizes multi-party real-time communication, accurate rescue instruction transmission and reasonable resource allocation are guaranteed, and the rescue efficiency is improved. And the fault detection and judgment module effectively supervises the maintenance process, false maintenance is avoided, it is ensured that the elevator reaches the safe operation standard after being maintained, secondary faults are prevented, and the follow-up safety of elevator passengers is guaranteed.

The invention discloses an intelligent monitoring system based on computer vision, and relates to the technical field of intelligent monitoring, and the system comprises the following components: an image collection module which collects the image and video data of a person in a monitoring area in real time through a high-precision camera, and the image and video data comprises facial expression details, body movements and person position relation information; according to the method, based on multi-dimensional data such as group member interaction behaviors and position relations, micro-expressions and behavior analysis results are combined, group behavior relations are modeled, the overall emotional atmosphere of a group can be perceived, the group behavior trend can be accurately predicted, and meanwhile, the group behavior analysis accuracy is improved. The early warning and processing module can generate an early warning signal in time according to a preset rule and send the early warning signal to a specified terminal device, thereby making up for the deficiency of an existing monitoring system in the aspect of group behavior trend prediction, enabling monitoring personnel to take measures in advance and deal with possible safety problems in time, and improving the monitoring efficiency. And the practicability and the emergency processing capability of the monitoring system are greatly enhanced.

To provide a person counting system, a method and a program which accurately calculate persons existing in a predetermined space.SOLUTION: A processor 101 of a person counting system 1 configured by comprising a person counting device 10 comprises: an image acquisition unit 11 which acquires a plurality of images picked up by each of a plurality of cameras which pick up a space; a person detection unit 13 which detects persons from each of the images; a position information acquisition unit 14 which acquires position information showing positions in the space of the detected persons; a determination unit 16 which determines that a first person detected from a first image picked up by a first camera and a second person detected from a second image picked up in the same timing by a second camera are the same person when distance between the position information of the first person and the position information of the second person is equal to or less than a given threshold; a counting unit 17 which counts the number of persons detected from the images by considering the persons determined to be the same as one; and an output unit 18 which outputs the counted number of persons.SELECTED DRAWING: Figure 1

The invention discloses a construction site management system based on an intelligent supervision APP, and the system comprises a region division module which is used for calibrating a dangerous operation point on obtained topographic information of a construction region topographic map, and setting a dangerous operation region and a monitoring region in a construction region according to the topographic information, and relates to the technical field of construction management. Whether a person intends to enter a suspicious person in a dangerous operation area or not can be predicted according to the position and the walking dynamic state of the person, the working point position of the suspicious person is obtained for follow-up relevant deployment and control, the problem that unrelated constructors mistakenly enter the dangerous operation area to cause safety accidents is avoided, and the safety prevention and control effect is improved; and normative safety management of a construction site is realized.

The invention relates to the technical field of elevators, in particular to an elevator fault accurate detection and early warning system based on an edge computing gateway, which comprises a data acquisition module, a data transmission module, a fault detection module, a fault early warning module, a maintenance management module, a data analysis module and a platform interaction module. Through the real-time monitoring and fault pre-judging functions of the edge computing gateway, various potential safety hazards in the elevator running process can be found in time, early warning can be given out in advance, maintenance personnel can handle faults before the faults occur, the elevator fault rate is effectively reduced, safety accidents are reduced, the life safety of elevator taking personnel is guaranteed, and the service life of the elevator taking personnel is prolonged. Rescue workers are helped to quickly locate the position of the trapped person and accurately judge the fault reason, the rescue efficiency is improved, and panic and danger of the trapped person are reduced to the maximum extent.

The invention provides a man-hour determination method and device in a flexible operation scene, and belongs to the technical field of man-hour determination, and the method comprises the steps: obtaining an operation region video collected based on a collection device, and recognizing task personnel in the operation region video and the personnel positions of the task personnel; when the task worker is matched with the task worker, determining a target operation area in the operation area based on the worker position and the duration of the task worker in the worker position; and determining the video duration of the task personnel meeting the man-hour counting condition in the target operation area, and taking the video duration as the operation man-hour of the task personnel. According to the method, the target operation areas of different tasks can be determined in the flexible operation scene, and then the working hours of the target operation areas are counted, so that the working hours of task personnel under different tasks can be obtained, and the accuracy of the determined working hours under the flexible operation scene is improved.

The present invention discloses a Bluetooth positioning-driven factory personnel tracking and management method and system, relating to the field of personnel tracking technology. The method comprises: when a Bluetooth device worn by a factory worker is disconnected, recording the spatial location at the time of disconnection and automatically tracking the worker's movement trajectory; when the Bluetooth is reconnected, processing the movement data during the disconnection period and generating a coordinate sequence through the Bluetooth blind spot positioning network, thereby achieving accurate tracking and management of the worker's location during the disconnection period. This method solves the technical problem of existing Bluetooth-based factory personnel real-time positioning systems being unable to continuously and accurately track the worker's location during Bluetooth disconnection, achieving the technical effect of continuously and accurately tracking the worker's location during Bluetooth disconnection.

A system includes non-transitory computer-readable storage media configured to store instructions and processors communicatively coupled to the non-transitory computer-readable storage media. The processors may execute instructions, which may cause the system to perform operations. The operations may include obtaining first data associated with a person location, where the first data may be a subset of a collection of person location data. The operations may also include obtaining second data associated with one or more displays in a venue, where the second data may be a subset of a collection of display data. The operations may further include determining a first weight corresponding to the first data relative to the collection of person location data and a second weight corresponding to the second data relative to the collection of display data. The operations may also include obtaining an estimate of the viewership data using the first data and the second data.

The invention provides a trapped person position state analysis method and system, and relates to the field of data processing. According to the method, building structure distribution, conductive fluid flow channels and metal component distribution in a disaster target area are constructed to form a background entropy flow ground state, and noise intensity probability distribution, a channel joint fluctuation relation and a time stability index are counted to generate a background entropy flow field. In the search and rescue stage, a background entropy flow field is converted into a controlled mode through active disturbance, multi-physical channel noise responses before and after disturbance are collected through a multi-field passive sensor network, and a multi-dimensional local entropy response vector is constructed. And combining the consistency, directivity and duration of the multi-noise channel to identify an initial suspected region and extract an entropy anomaly core region, finally inferring metabolic activity and posture limitation conditions according to a local entropy response cooperative relationship in different disturbance modes, and outputting a position state result of the trapped person. By implementing the technical scheme provided by the invention, the position state of the trapped person can be accurately identified.

The present invention provides a lightweight AI personnel perception method and system based on millimeter-wave radar, which relates to the technical field of personnel perception. It includes constructing three-dimensional spatial point cloud data by performing phase compensation, amplitude calibration, and bidirectional joint filtering on millimeter-wave echo signals. Then, based on the point cloud data, a spatial distribution matrix is constructed, the center position of the point cloud cluster is calculated, and an adaptive sampling radius is established to extract point cloud features, and the motion vector and attitude parameters are calculated. Finally, the motion vector and attitude parameters are input into a dual-threshold decision module to determine whether there are personnel in the target area, and a personnel position heat map is generated based on the center position of the point cloud cluster to output the personnel perception result. The present invention reduces the computational complexity, improves the real-time performance and accuracy of personnel perception, and is applicable to scenarios such as smart homes and security monitoring.

A management system (100) for managing the state of an object and the environment in an indoor monitoring space (1) comprises: an environment measurement means for measuring a gas environment within the space; a person measurement means for measuring a person present in the space; a position measurement means for measuring the position of an object moving within the space; an apparatus state measurement means for measuring the operation state of an apparatus within the space; a spatial state calculation unit for calculating the spatial state within the space from the measured gas environment data and the measured person data; a position information management unit for managing the position information pertaining to the object in accordance with the measured position data of the object; an apparatus state management unit for managing the operation state of the apparatus in accordance with the operation data of the apparatus; and a display control unit that superimposes the spatial state, the position information pertaining to the object, and the operation state of the apparatus on an image indicating the shape of the monitoring space (1), and displays the superimposed image on a display means.

The present invention relates to the technical field of rescue management, and discloses a task management system and method for underground emergency rescue, including an underground monitoring unit, a data acquisition unit, a communication unit, a central processing unit, and an information display unit; the present invention can determine the safe rescue time according to underground environmental parameters and personnel position information, provide a clear target for the rescue operation, and can also analyze the dispatch value of rescue personnel for reasonable allocation, analyze the underground environmental parameters with multiple attributes and consider time changes, and preset weight coefficients to determine the degree of urgency, so as to make the rescue more accurate; the central processing unit scientifically analyzes data, and the information display unit intuitively presents information, providing a basis for the rescue plan, reasonably allocating rescue resources, comprehensively considering the indicators of rescue personnel, avoiding waste and excessive use, giving priority to emergency tasks, ensuring rescue safety, real-time monitoring of the underground environment to provide early warning, and reasonably allocating tasks to avoid excessive fatigue and high risks of personnel.

We provide the system. [Solution] A means for acquiring video data and analyzing the location of workers within the office, A means for designing the optimal traffic flow based on the above analysis results, A means of outputting the designed movement flow information, A system that includes this.

The invention belongs to the technical field of mode recognition and artificial intelligence application, and particularly discloses a dangerous area personnel climbing behavior recognition method, a storage medium and a terminal, and the method comprises the following steps: S1, constructing a human body target detection data set; s2, training a human body target detection algorithm; s3, constructing a personnel climbing behavior classification data set; s4, training a personnel climbing behavior classification algorithm; s5, configuring a personnel climbing behavior identification area; s6, obtaining the position information of the personnel; s7, comparing personnel position information; and S8, classifying the personnel body area image blocks appearing in the personnel climbing behavior recognition area through a trained personnel climbing behavior classification algorithm, and judging whether a personnel climbing behavior exists or not. The method has the beneficial effects that the image data can be processed and analyzed through the image recognition technology to obtain the personnel behavior information in the image data, so that the realization of personnel climbing behavior recognition becomes reality, and the safety risk caused by the personnel climbing behavior in a dangerous area is reduced.

The present invention discloses a method and system for counting people entering and leaving, the method comprising receiving a video frame to be detected of a target area acquired by an image acquisition device; using a target detection model to acquire personnel information in the video frame to be detected, the personnel information including the position of the personnel and the entry and exit status of the personnel; and judging whether the position of the personnel is located at a preset counting position. The method does not rely on a tracking model, but uses a target detection model to detect the head of a person in real time, thereby realizing real-time classification of the entry and exit information of the personnel. An electronic bar for counting the number of people entering and an electronic bar for counting the number of people leaving are set, and the number of people entering and leaving is counted respectively by using the method of people breaking into the electronic bar. Real-time statistics can be realized on an embedded device, and scenes with a large number of people entering and leaving can be handled, and the counting speed will hardly decrease. Scenes with complex backgrounds can be handled, and it is not easy to misjudge or miss.