A real-time tracking method for campus visual security positioning based on multi-sensor integration

Abstract

The present invention relates to the field of positioning and tracking technology, and in particular to a multi-sensor integrated real-time tracking method for visual security positioning in a park. The method comprises: in response to a temporary object entering the park, obtaining the temporary object's access information and action information; inputting the access information into a digital twin model of the park to generate several candidate action routes and corresponding action nodes; determining a stage action route based on the temporary object's action information and each candidate action route, and determining path labels for the stage action route, including concentrated path labels and discrete path labels; and determining an update method for the park digital twin model for the temporary object within the stage action route based on the path labels of the stage action route. The present invention can reduce the amount of data processing required to update the park digital twin model and improve the accuracy and efficiency of positioning and tracking.

Description

Technical Field

[0001] The present invention relates to the field of positioning and tracking technology, and in particular to a multi-sensor integrated park visual security positioning and real-time tracking method. Background Art

[0002] As an important carrier for the application of industrial Internet platforms, the park is characterized by industrial agglomeration and rich scenarios. With the development of technologies such as the Internet of Things and artificial intelligence, the digital twin of the park has become an important direction for digital transformation and management.

[0003] Currently, a wide variety of industrial parks, service parks, and logistics park projects are emerging one after another. As parks continue to expand in scale and become increasingly complex in their functions, the requirements for park security management and efficient operations are also increasing. Traditional security management methods rely primarily on manual patrols and fixed-point monitoring, which have limitations such as blind spots, delayed responses, and an inability to fully grasp park dynamics in real time. Digital twin technology, as an emerging digital approach, enables real-time monitoring, dynamic analysis, and intelligent management of parks by constructing virtual digital models that correspond to the actual park. The integration of multi-sensor technology can obtain more comprehensive and accurate park data, providing rich information support for the digital twin model, thereby improving the park's security management level and operational efficiency.

[0004] However, the high mobility and complex identities of temporary park entrants pose potential risks to park security. If the park's digital twin model is not updated promptly, it will become inconsistent with actual conditions, affecting the accuracy of positioning and tracking. Furthermore, the park's digital twin model is large in scale, and updating the model to track and locate temporary park entrants requires a significant amount of data processing, resulting in relatively low positioning and tracking efficiency. Summary of the Invention

[0005] To this end, the present invention provides a real-time tracking method for visual security positioning of a park that integrates multiple sensors, so as to overcome the problems of low accuracy and efficiency in the positioning and tracking of temporary personnel entering the park in the existing technology, as well as the large amount of data processing required to update the digital twin model of the park.

[0006] To achieve the above objectives, the present invention provides a multi-sensor integrated campus visual security positioning and real-time tracking method, comprising:

[0007] In response to a temporary object entering the park, obtaining access information and action information of the temporary object, wherein the access information includes identity information, destination, authority information, and historical access information of the temporary object, and the action information includes action mode, action tendency, and action speed;

[0008] Inputting the access information into the digital twin model of the park to generate a number of candidate action routes and corresponding action nodes, wherein each candidate action route includes a number of action nodes, and the end point of each candidate action route is the destination of the temporary object;

[0009] Determining a stage action route based on the action information of the temporary object and each of the candidate action routes, and determining a path label of the stage action route, including a concentrated path label and a discrete path label;

[0010] Determining an update method of the digital twin model of the park where the temporary object is in the stage action route based on the path label of the stage action route includes:

[0011] If the path label of the stage action route is a path concentration label, predicting the action trajectory of the temporary object on the stage action route to update the campus digital twin model for the temporary object;

[0012] If the path label of the stage action route is a discrete path label, the real-time action trajectory of the temporary object on the stage action route is obtained to update the campus digital twin model for the temporary object.

[0013] Furthermore, the phased action plan is determined, including:

[0014] Screening each of the candidate action routes based on the action mode of the temporary object to obtain a number of optional action routes;

[0015] Splitting each optional action route based on the action nodes on each optional action route to obtain a plurality of alternative stage action routes;

[0016] The stage action route is determined based on the association degree between the action information of the temporary object and the starting action node of each candidate stage action route.

[0017] Furthermore, determining the path label of the action route of the stage includes:

[0018] Retrieving historical path data corresponding to the stage action route, and determining a path label for the stage action route based on similarity between the historical path data;

[0019] The historical path data includes the historical action paths of several objects on the action route of the stage.

[0020] Furthermore, the path label of the stage action route is determined based on the similarity of each historical path data, wherein,

[0021] If the similarity of each of the historical path data is greater than a preset similarity, determining the path label of the action route of the stage as a path concentration label;

[0022] If the similarity of each of the historical path data is less than or equal to a preset similarity, the path label of the stage action route is determined to be a discrete path label.

[0023] Furthermore, predicting the movement trajectory of the temporary object on the movement route of the stage includes:

[0024] Obtaining basic momentum information of the temporary object at the starting point of the action route of the stage;

[0025] determining a predicted motion trajectory of the temporary object in the motion route of the stage based on the basic momentum information;

[0026] The campus digital twin model for the temporary object is updated based on the predicted motion trajectory.

[0027] Furthermore, obtaining the real-time movement trajectory of the temporary object on the movement route of the stage includes:

[0028] Acquiring real-time momentum information of the temporary object in the action route of the stage;

[0029] determining a real-time motion trajectory of the temporary object in the stage motion route based on the real-time momentum information;

[0030] The campus digital twin model for the temporary object is updated based on the real-time action trajectory.

[0031] Furthermore, it also includes:

[0032] Determining a feasible area based on the route range of the action route for the stage;

[0033] Based on the area identifier corresponding to the feasible area and the permission information of the temporary object, it is determined whether a danger warning is triggered. If a danger warning is triggered, a warning message is issued and the digital twin model of the park is updated.

[0034] Furthermore, determining whether to trigger a danger warning based on the area identifier corresponding to the feasible area and the permission information of the temporary object includes:

[0035] determining a plurality of reachable areas of the temporary object based on the permission information of the temporary object;

[0036] Whether to trigger a danger warning is determined based on a comparison result of the area identifier corresponding to each of the reachable areas and the area identifier corresponding to the feasible area.

[0037] Furthermore, the access information is input into the digital twin model of the park to generate several candidate action routes and corresponding action nodes, including:

[0038] Inputting the access information into the digital twin model of the park to generate several candidate action routes;

[0039] Evaluate each of the candidate action routes based on a preset evaluation index to determine a number of candidate action routes;

[0040] The corresponding action node is determined based on the sensor coverage range in each candidate action route.

[0041] Furthermore, the stage action route is determined based on the association degree between the action information of the temporary object and the starting action node of each candidate stage action route, wherein:

[0042] If the maximum correlation degree between the action information of the temporary object and the starting action node of each of the candidate stage action routes is greater than a preset correlation degree, the candidate stage action route corresponding to the maximum correlation degree is determined as the stage action route.

[0043] Compared with the prior art, the present invention has the beneficial effect of utilizing the access information of temporary objects to input into the campus digital twin model to generate candidate action routes, thereby improving the rationality and feasibility of route planning. By combining the temporary object's action information with the candidate action routes to determine the stage action route and determining the path label of the stage action route, a basis is provided for subsequently determining the model update method, thereby improving the accuracy and efficiency of positioning and tracking. The update method of the campus digital twin model for the temporary object in the stage action route is determined based on the path label of the stage action route, thereby improving the pertinence and efficiency of the model update and enabling the campus digital twin model to more accurately reflect the motion state of the temporary object. A concentrated path label indicates that the action path is relatively concentrated in the stage action route, allowing for predictive analysis of the temporary object's action trajectory. Updating the campus digital twin model for the temporary object based on the basic momentum information at the starting point of the stage action route can reduce data processing and improve the efficiency of positioning and tracking. A discrete path label indicates that the action path is relatively dispersed in the stage action route, making it difficult to determine the specific action trajectory of the temporary object. Updating the campus digital twin model for the temporary object based on the basic momentum information can improve the accuracy of positioning and tracking.

[0044] Furthermore, the present invention screens candidate action routes based on the temporary object's mode of action to obtain several optional action routes. Different modes of action have different requirements for routes. For example, when walking, it is suitable to choose a route with flat roads and wide pedestrian walkways; when driving, it is necessary to consider the width of the road, whether motor vehicles are allowed to pass, and the location of the parking lot. By screening based on the mode of action, candidate action routes that do not meet the mode of action can be quickly eliminated, which improves the pertinence of subsequent route planning, ensures that the selected route is fundamentally adapted to the movement characteristics of the temporary object, and avoids planning an inaccessible route. The optional action routes are split based on the action nodes, and the long route is decomposed into multiple short alternative stage action routes, making the route planning more refined and each alternative stage action route more independent and controllable, which facilitates the subsequent accurate matching and analysis of the specific action information of the temporary object. The stage action route is determined based on the degree of correlation between the action information and the starting action node. By analyzing the degree of correlation between the action information of the temporary object and the starting action node of the alternative stage action route, the route that best meets the current status and expectations of the temporary object can be selected. Positioning and tracking are performed based on the accurate starting point and associated action information. The digital twin model of the park can more accurately update the position and status of temporary objects, thereby improving the accuracy of positioning and tracking.

[0045] Furthermore, the present invention determines the path label of the stage action route based on the similarity of each historical path data through the historical path data corresponding to the stage action route, which can improve the accuracy of the path label, adapt to the dynamic changes of personnel in the park, and optimize the update strategy of the park digital twin model.

[0046] Furthermore, the present invention obtains the basic momentum information of the temporary object and determines the predicted motion trajectory of the temporary object in the stage action route based on the basic momentum information. The basic momentum information reflects the motion state of the temporary object at the starting node of the stage action route. The predicted motion trajectory is determined to update the digital twin model of the park, which can enable the digital twin model of the park to more accurately simulate the motion of the temporary object on the stage action route, improve the accuracy of positioning and tracking, and reduce the amount of data processing.

[0047] Furthermore, the present invention obtains real-time momentum information of the temporary object and determines the real-time movement trajectory of the temporary object in the stage action route based on the real-time momentum information. The real-time momentum information reflects the real-time motion state of the temporary object in the stage action route. The real-time movement trajectory is determined to update the digital twin model of the park, so that the digital twin model of the park is synchronized with the movement of the temporary object, thereby improving the accuracy of positioning and tracking.

[0048] Furthermore, the present invention determines the feasible area based on the stage action route, and combines the area identification and temporary object permission information to determine the danger warning and update the digital twin model of the park. It can clearly define the scope of temporary objects' allowed activities, and make judgments based on the area identification and permission information. It can effectively prevent temporary objects from entering dangerous areas that they are not authorized to enter. Once a temporary object is found to enter such an area, a danger warning will be triggered immediately and a message will be issued to remind relevant personnel to take measures, thereby improving the safety level of the park. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 This is a flow chart of a method for real-time tracking of visual security positioning in a park integrating multiple sensors according to an embodiment of the present invention;

[0050] Figure 2 A schematic diagram of a process for generating candidate action routes and corresponding action nodes for an embodiment of the present invention;

[0051] Figure 3 A schematic diagram of a process for determining a stage action route according to an embodiment of the present invention;

[0052] Figure 4 This is a logical judgment diagram for determining the path labels of the stage action route according to an embodiment of the present invention. DETAILED DESCRIPTION

[0053] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are merely used to explain the present invention and are not intended to limit the present invention.

[0054] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0055] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside", and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0056] Furthermore, it should be noted that, in the description of the present invention, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed connections, detachable connections, or integral connections; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; and internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0057] See also Figure 1 As shown in FIG, which is a flow chart of a method for real-time tracking of a visual safety positioning of a campus by integrating multiple sensors according to an embodiment of the present invention; an embodiment of the present invention provides a method for real-time tracking of visual safety positioning of a campus by integrating multiple sensors, comprising:

[0058] Step S1, in response to a temporary object entering the park, obtaining access information and action information of the temporary object, wherein the access information includes identity information, destination, authority information, and historical access information of the temporary object, and the action information includes action mode, action tendency, and action speed;

[0059] In implementation, identity verification devices, such as ID card readers and facial recognition cameras, can be installed at park entrances. When a temporary visitor enters the park, the ID card reader reads the identity information stored in the ID card chip, including basic information such as name, ID number, and gender. The facial recognition camera captures the temporary visitor's facial image and compares it with a database of registered faces to confirm their identity. If the temporary visitor is new, their facial features are recorded and linked to other information collected later. For temporary visitors who make online reservations to enter the park, their identity information is collected in advance in the reservation system. Upon entry, their identity is confirmed through methods such as scanning a QR code or SMS verification code, and the reservation information is matched with their actual entry. If a temporary visitor makes an online reservation, a mandatory destination option is set in the reservation system. The destination can be selected from a list of pre-set locations in the park, such as specific office buildings, conference rooms, and warehouses. When checking in at the park entrance, staff will ask the temporary visitor their destination and accurately record it. Permission rules can be pre-set based on the temporary visitor's purpose of visit and identity type. For example, maintenance personnel may be granted access to equipment rooms and related maintenance areas, while visitors may only be allowed access to designated reception areas and public passages. It is understandable that the historical access information includes the access information and movement routes of the temporary object when entering the park in the past.

[0060] During implementation, when registering to enter the park, temporary visitors can be directly asked about their mode of movement, such as walking, driving, cycling, or taking the park shuttle bus, and the information can be recorded. Temporary visitors can be asked to choose from relevant questions or options to understand their behavioral tendencies, such as whether they are in a hurry (options such as "very anxious, hope to reach the destination as soon as possible" or "not anxious, have plenty of time"), whether they are willing to visit the park ("yes, I want to visit the park by the way" or "no, my main purpose is to do business"), etc. Preliminary predictive analysis can also be conducted based on the temporary visitor's identity and purpose of visit. For example, business visitors may prefer to reach the destination quickly, while tourists may prefer to visit and sightsee. Alternatively, the temporary visitor's behavioral tendencies and speed can be obtained through motion sensors, infrared sensors, monitoring equipment, etc.

[0061] Step S2: inputting the access information into the digital twin model of the park to generate a number of candidate action routes and corresponding action nodes, wherein each candidate action route includes a number of action nodes, and the end point of each candidate action route is the destination of the temporary object;

[0062] See also Figure 2 As shown in FIG, it is a flow chart of generating candidate action routes and corresponding action nodes according to an embodiment of the present invention; specifically, in step S2, the access information is input into the digital twin model of the park to generate several candidate action routes and corresponding action nodes, including:

[0063] Step S21: input the access information into the digital twin model of the park to generate several action routes to be selected;

[0064] Step S22, evaluating each of the candidate action routes based on a preset evaluation index to determine a number of candidate action routes;

[0065] Step S23: determining a corresponding action node based on the sensor coverage in each candidate action route.

[0066] During implementation, the access information obtained is converted into a format that can be recognized by the digital twin model of the park, such as digitally encoding the text information, starting the digital twin model of the park, and loading high-precision park geographic information data, including building layout, road direction, entrance and exit locations, etc. At the same time, the path planning algorithm module of the model is loaded to prepare for the generation of candidate action routes. Path planning algorithms such as the Dijkstra algorithm or the A* algorithm are used to fully consider the actual situation in the park, such as the road capacity (whether it is a one-way street, road width restrictions, etc.), building obstructions and other factors. With the current position of the temporary object as the starting point and the destination coordinates as the end point, several feasible paths are calculated as candidate action routes.

[0067] It is understandable that the actual implementers can set preset evaluation indicators based on actual conditions, such as route length, travel time, degree of fit with action tendencies, etc., assign corresponding weights to each preset evaluation indicator, and score each candidate action route according to each preset evaluation indicator (the route length, travel time, and degree of fit with action tendencies of each candidate action route can be ranked, with the longest route length, shortest travel time, and highest degree of fit being given full marks, and the shortest route length, longest travel time, and lowest degree of fit being given 0 points, and the scores are set based on the corresponding gaps), and a comprehensive score is calculated based on the weight, and each candidate action route is ranked according to the comprehensive score, and several candidate action routes with higher comprehensive scores (for example, greater than the preset score, the preset score can be set to 0.8 to 0.9 times the total score) are selected as candidate action routes. For example: based on a full score of 100, the route length has a weight of 0.2, the travel time has a weight of 0.3, and the degree of fit with the action tendency has a weight of 0.5. The preset score is 80. The selected action route 1: route length 80 points, travel time 70 points, and the degree of fit with the action tendency is 80 points. The selected action route 2: route length 70 points, travel time 70 points, and the degree of fit with the action tendency is 90 points. The selected action route 3: route length 60 points, travel time 80 points points, and the degree of fit with the action tendency is 90 points, then the comprehensive score of the alternative action route 1 is: 80×0.2+70×0.3+80×0.5=77, the comprehensive score of the alternative action route 2 is: 70×0.2+70×0.3+90×0.5=87, the comprehensive score of the alternative action route 3 is: 60×0.2+80×0.3+90×0.5=81, and the preset score is 80, then the alternative action route 2 and the alternative action route 3 will be taken as candidate action routes.

[0068] It is understood that sensors include all sensors monitoring candidate action routes, such as monitoring equipment, positioning sensors, and environmental sensors. Setting action nodes at the edges of overlapping sensor coverage can meet the need for real-time monitoring of temporary object movement without overcrowding, which would otherwise burden data processing. Each action node is uniquely identified and its coordinate location in the campus digital twin model, the candidate action route number, and the corresponding sensor information are recorded.

[0069] Step S3, determining a stage action route based on the action information of the temporary object and each of the candidate action routes, and determining a path label of the stage action route, including a concentrated path label and a discrete path label;

[0070] See also Figure 3 , which is a schematic diagram of a process for determining a stage action route according to an embodiment of the present invention; specifically, in step S3, determining the stage action route includes:

[0071] Step S31, screening the candidate action routes based on the action mode of the temporary object to obtain several optional action routes;

[0072] In implementation, different modes of action have different requirements for routes. For example, when walking, it is suitable to choose routes with flat roads and wide pedestrian walkways; when driving, it is necessary to consider the width of the road, whether motor vehicles are allowed to pass, and the location of the parking lot. By screening based on the mode of action, candidate routes that do not meet the mode of action can be quickly eliminated, reducing the subsequent data processing volume.

[0073] Step S32, splitting each optional action route based on the action nodes on each optional action route to obtain a plurality of alternative stage action routes;

[0074] Step S33 : determining a stage action route based on the association degree between the action information of the temporary object and the starting action node of each candidate stage action route.

[0075] In implementation, a training dataset is constructed based on the action information of each object in historical data and the corresponding alternative phase action routes. The neural network model is trained based on this training dataset, and the corresponding degree of association is output. Alternatively, the action information of temporary objects is used as data points in a vector space, and the starting action nodes of different alternative phase action routes are used as different categories. The support vector machine learns to find a hyperplane that best distinguishes these categories. The distance between the action information data point and the hyperplane, as well as the category it belongs to, can reflect its degree of association with each starting action node. For example, if an action information data point is close to the category region representing a starting action node and far from the hyperplane, it indicates that the action information has a high degree of association with the starting action node.

[0076] Specifically, the stage action route is determined based on the association degree between the action information of the temporary object and the starting action node of each candidate stage action route, wherein:

[0077] If the maximum correlation degree between the action information of the temporary object and the starting action node of each of the candidate stage action routes is greater than a preset correlation degree, the candidate stage action route corresponding to the maximum correlation degree is determined as the stage action route.

[0078] It is understood that a correlation analysis can be performed between the action information of the temporary object and the starting action nodes of each alternative stage action route, and the corresponding correlation coefficient can be calculated (for example, based on the Pearson correlation coefficient, mutual information, etc.), which is used as the degree of association between the action information of the temporary object and the starting action nodes of each alternative stage action route. The respective correlation degrees are sorted. If the maximum degree of association between the action information of the temporary object and the starting action nodes of each alternative stage action route is less than or equal to the preset degree of association, the action node closest to the temporary object is used as the starting point of the stage action route. If the maximum degree of association is greater than the preset degree of association, it means that the action information of the temporary object has a relatively high degree of association with the starting action nodes of each alternative stage action route, and the alternative stage action route corresponding to the maximum degree of association is determined as the stage action route. It is understood that the actual implementation personnel can set the preset degree of association based on actual conditions. The preset degree of association is inversely proportional to the distance between the temporary object and the destination. Preferably, the preset degree of association is set in the range of 0.7 to 0.85.

[0079] See also Figure 4 As shown, it is a logical judgment diagram for determining the path label of the stage action route according to an embodiment of the present invention; specifically, determining the path label of the stage action route includes:

[0080] Retrieving historical path data corresponding to the stage action route, and determining a path label for the stage action route based on similarity between the historical path data;

[0081] The historical path data includes the historical action paths of several objects on the action route of the stage.

[0082] It is understandable that during the actual movement of temporary objects, they may encounter some obstacles (such as road construction fences, temporarily piled items, traffic congestion, dense crowds, weather influences, etc.), resulting in the movement path not being a straight line, but changing the movement path during the stage movement route.

[0083] In implementation, the starting point of the stage action route is taken as the origin, the extension direction of the stage action route from the starting point to the end point is the horizontal coordinate, and the vertical coordinate is the direction perpendicular to the horizontal coordinate on the ground. The coordinate points corresponding to several different horizontal coordinates on the historical action path can be obtained, for example, historical action path 1: Y1, Y2, ..., Y j ,…,Y m , historical action path 2: E1, E2, …, E j ,…,E m , where j = 1, 2, ..., m; Y j is the ordinate corresponding to the jth horizontal coordinate on the historical action path 1, E jis the ordinate corresponding to the jth horizontal coordinate on the historical action path 2, then the similarity between the historical action path 1 and the historical action path 2 is MP = sqrt(∑ m j＝1 (Y j -E j ) 2 ), sqrt() is a preset square root determination function. It is understandable that the similarity of each historical path data can be determined by taking the mean of the similarities between any two historical path data on the stage action route.

[0084] Specifically, the path label of the stage action route is determined based on the similarity of each historical path data, wherein:

[0085] If the similarity of each of the historical path data is greater than a preset similarity, determining the path label of the action route of the stage as a path concentration label;

[0086] If the similarity of each of the historical path data is less than or equal to a preset similarity, the path label of the stage action route is determined to be a discrete path label.

[0087] It is understandable that the similarity of the historical path data is determined based on the degree of overlap of the historical action paths of each object on the stage action route, and the specific calculation method is not limited.

[0088] In implementation, if the similarity between the historical path data is greater than a preset similarity, it indicates that the historical path data for the stage's action route are relatively consistent, with few or no obstacles, allowing each object to move in a straight line along the stage's action route without requiring detours. The path label for the stage's action route is then determined to be a concentrated path label. If the similarity between the historical path data is less than or equal to the preset similarity, it indicates that the historical path data for the stage's action route are inconsistent, with the possibility of obstacles. This prevents each object from moving in a straight line along the stage's action route and requires detours. The path label for the stage's action route is then determined to be a discrete path label.

[0089] The present invention determines the path label of the stage action route based on the similarity of each historical path data through the historical path data corresponding to the stage action route. It can improve the accuracy of the path label, adapt to the dynamic changes of personnel in the park, and optimize the update strategy of the park digital twin model.

[0090] The present invention screens candidate action routes based on the temporary object's movement patterns to obtain several optional action routes. Different movement patterns have different route requirements. For example, walking is suitable for routes with flat roads and wide pedestrian walkways; driving requires consideration of road width, whether motor vehicles are allowed, and parking lot locations. By screening based on movement patterns, candidate action routes that do not meet the movement patterns can be quickly eliminated, improving the targeted nature of subsequent route planning and ensuring that the selected route fundamentally adapts to the temporary object's movement characteristics, avoiding the planning of inaccessible routes. The present invention splits the optional action routes based on movement nodes, breaking down long routes into multiple shorter alternative stage action routes. This makes route planning more refined, and each alternative stage action route is more independent and controllable, facilitating subsequent precise matching and analysis of the temporary object's specific movement information. Stage action routes are determined based on the degree of correlation between movement information and the starting movement node. By analyzing the correlation between the temporary object's movement information and the starting movement node of the alternative stage action routes, the route that best matches the temporary object's current state and expectations can be selected. Positioning and tracking are performed based on accurate starting points and associated movement information. The campus digital twin model can more accurately update the position and state of temporary objects, improving the accuracy of positioning and tracking.

[0091] Step S4, determining the update method of the digital twin model of the park where the temporary object is in the stage action route based on the path label of the stage action route, including:

[0092] If the path label of the stage action route is a path concentration label, predicting the action trajectory of the temporary object on the stage action route to update the campus digital twin model for the temporary object;

[0093] If the path label of the stage action route is a discrete path label, the real-time action trajectory of the temporary object on the stage action route is obtained to update the campus digital twin model for the temporary object.

[0094] Specifically, predicting the movement trajectory of the temporary object on the movement route of the stage includes:

[0095] Step S41, obtaining basic momentum information of the temporary object at the starting point of the action route of the stage;

[0096] Step S42, determining a predicted motion trajectory of the temporary object in the motion route of the stage based on the basic momentum information;

[0097] Step S43: updating the campus digital twin model for the temporary object based on the predicted motion trajectory.

[0098] In implementation, the momentum information includes the position coordinates, moving direction and moving speed of the temporary object, and the basic momentum information is the position coordinates, moving direction and moving speed of the temporary object at the starting point of the stage action route.

[0099] In some possible implementations, when predicting the motion trajectory based on the basic momentum information, the current position coordinates of the temporary object are used as the trajectory starting point, the moving direction is used as the trajectory direction, and the trajectory is continuously extended at the corresponding moving speed to obtain the predicted motion trajectory.

[0100] In some possible implementations, the basic momentum information of temporary objects can be detected based on sensors set on the stage action route, and the basic momentum information can be input into the trajectory prediction model to obtain the predicted action trajectory output by the trajectory prediction model. It can be understood that a basic training data set can be constructed based on the basic momentum information and action trajectory of objects in the action path corresponding to the path set labels in the historical data, and the initial neural network model is trained based on the basic training data set to obtain the trajectory prediction model. It should be noted that those skilled in the art know that any prediction model in the prior art that can predict the action trajectory falls within the scope of protection of the present invention and will not be repeated here.

[0101] It can be understood that in the digital twin model of the park, the corresponding virtual entity is found through the identity identification of the temporary object. The virtual entity should have momentum information corresponding to the temporary object in reality. According to the predicted action trajectory, the position information of the virtual entity in the digital twin model is updated, and the predicted position coordinates at different time points are assigned to the virtual entity so that its position in the model is consistent with the predicted action trajectory. At the same time, the speed and direction information of the virtual entity is updated to match the predicted motion state.

[0102] Specifically, based on the predicted action trajectory, the predicted arrival time of the temporary object at the end of the stage action route is determined, and the real-time arrival time of the temporary object is compared with the predicted arrival time. If the difference between the real-time arrival time and the predicted arrival time is greater than the preset time length, an early warning prompt is issued.

[0103] During implementation, if the temporary object has arrived at / passed the end point of the stage action route when the predicted arrival time is reached, no warning prompt will be issued. If the temporary object has not reached the end point of the stage action route when the predicted arrival time is reached, the timing will start until the recorded time (the difference between the real-time arrival time and the predicted arrival time is large) is greater than the preset time, then a warning prompt will be issued.

[0104] It is understandable that the actual implementation personnel can set the preset duration based on the actual situation. Preferably, the preset market value range is set to 10 minutes to 20 minutes.

[0105] The present invention obtains the basic momentum information of the temporary object and determines the predicted motion trajectory of the temporary object in the stage action route based on the basic momentum information. The basic momentum information reflects the motion state of the temporary object at the starting node of the stage action route. The predicted motion trajectory is determined to update the digital twin model of the park, which can enable the digital twin model of the park to more accurately simulate the motion of the temporary object on the stage action route, improve the accuracy of positioning and tracking, and reduce the amount of data processing.

[0106] Specifically, in step S4, obtaining the real-time movement trajectory of the temporary object on the movement route of the stage includes:

[0107] Step S44, obtaining real-time momentum information of the temporary object in the action route of the stage;

[0108] Step S45, determining the real-time movement trajectory of the temporary object in the stage movement route based on the real-time momentum information;

[0109] Step S46: Update the campus digital twin model for the temporary object based on the real-time action trajectory.

[0110] In implementation, the real-time momentum information is the position coordinates, moving direction, and moving speed of the temporary object obtained in real time along the stage action route.

[0111] In implementation, the real-time momentum information of the temporary object can be detected in real time by sensors installed along the staged movement route. Based on this real-time momentum information, the temporary object's position can be calculated in real time. Continuous position information can be connected to form the real-time movement trajectory of the temporary object along the staged movement route. Position information can be recorded in a time series format, and each position point can be connected in chronological order to obtain the real-time movement trajectory. The latest position information in the real-time movement trajectory is updated to the virtual entity in the digital twin model, ensuring that the virtual entity's position is synchronized with the actual position of the temporary object.

[0112] It can be understood that when determining the real-time movement trajectory of the temporary object in the stage movement route based on the real-time momentum information, the real-time position coordinates, moving direction and moving speed of the temporary object on the stage movement route are connected in chronological order to form a real-time movement trajectory.

[0113] The present invention obtains the real-time momentum information of the temporary object and determines the real-time movement trajectory of the temporary object in the stage action route based on the real-time momentum information. The real-time momentum information reflects the real-time motion state of the temporary object in the stage action route. The real-time movement trajectory is determined to update the digital twin model of the park, so that the digital twin model of the park is synchronized with the movement of the temporary object, thereby improving the accuracy of positioning and tracking.

[0114] Specifically, it also includes:

[0115] Step S5, determining a feasible area based on the route range of the stage action route;

[0116] Step S6: Determine whether a danger warning is triggered based on the area identifier corresponding to the feasible area and the authority information of the temporary object. If a danger warning is triggered, issue a warning message and update the digital twin model of the park.

[0117] Specifically, in step S6, determining whether to trigger a danger warning based on the area identifier corresponding to the feasible area and the permission information of the temporary object includes:

[0118] Step S61, determining a number of reachable areas of the temporary object based on the permission information of the temporary object;

[0119] Step S62 : determining whether a danger warning is triggered based on a comparison result of the area identifiers corresponding to the reachable areas and the area identifiers corresponding to the feasible areas.

[0120] During implementation, the spatial scope of the route is calculated based on the staged action route. A rectangular or polygonal area can be determined as the route range by calculating the coordinate range of each node on the route. All walkable areas within the route range are identified as feasible areas, including buildings and roads within the park. The area identifier includes attribute information of the area, such as the area type (office area, public area, danger zone, etc.) and whether specific types of personnel or equipment are allowed to enter. Several reachable areas of the temporary object are determined based on the permission information of the temporary object. If the area identifier within the feasible area does not have a corresponding reachable area, indicating that the temporary object has entered an unreachable area, a danger warning is triggered.

[0121] It is understood that once a danger warning is triggered, the park's alarm system will issue an alert message, which includes the temporary object's identity information, current location, and the area it has entered. Simultaneously with the alert, the park's digital twin model will be updated with the temporary object's status in the digital twin, such as marking it as having entered a non-authorized area and displaying its current location.

[0122] The present invention determines the feasible area based on the stage action route, and combines the area identification and temporary object permission information to determine the danger warning and update the digital twin model of the park. It can clearly define the scope of temporary objects' allowed activities, and make judgments based on the area identification and permission information. It can effectively prevent temporary objects from entering dangerous areas that they are not authorized to enter. Once a temporary object is found to enter such an area, a danger warning will be immediately triggered and a message will be issued to remind relevant personnel to take measures, thereby improving the safety level of the park.

[0123] The present invention utilizes the access information of temporary objects to input into the digital twin model of the park to generate candidate action routes, thereby improving the rationality and feasibility of route planning. By combining the action information of the temporary object and the candidate action routes to determine the stage action route, and determining the path label of the stage action route, a basis is provided for the subsequent determination of the model update method, thereby improving the accuracy and efficiency of positioning and tracking. The update method of the digital twin model of the park where the temporary object is in the stage action route is determined according to the path label of the stage action route, thereby improving the pertinence and efficiency of the model update, and enabling the digital twin model of the park to more accurately reflect the motion state of the temporary object. The concentrated path label indicates that the action path is relatively concentrated in the stage action route, and the action trajectory of the temporary object can be predicted and analyzed. The digital twin model of the park for the temporary object is updated based on the basic momentum information of the starting point of the stage action route, which can reduce the amount of data processing and improve the efficiency of positioning and tracking. The discrete path label indicates that the action path is relatively dispersed in the stage action route, and it is difficult to determine the specific action trajectory of the temporary object. The digital twin model of the park for the temporary object is updated based on the basic momentum information, which can improve the accuracy of positioning and tracking.

[0124] Thus far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art may make equivalent changes or substitutions to the relevant technical features, and the technical solutions after such changes or substitutions will fall within the scope of protection of the present invention.

Claims

1. A multi-sensor integrated campus visual security positioning and real-time tracking method, characterized in that: include: In response to a temporary object entering the park, obtaining access information and action information of the temporary object, wherein the access information includes identity information, destination, authority information, and historical access information of the temporary object, and the action information includes action mode, action tendency, and action speed; Inputting the access information into the digital twin model of the park to generate a number of candidate action routes and corresponding action nodes, wherein each candidate action route includes a number of action nodes, and the end point of each candidate action route is the destination of the temporary object; Determining a stage action route based on the action information of the temporary object and each of the candidate action routes, and determining a path label of the stage action route, including a concentrated path label and a discrete path label; Determining an update method of the digital twin model of the park where the temporary object is in the stage action route based on the path label of the stage action route includes: If the path label of the stage action route is a path concentration label, predicting the action trajectory of the temporary object on the stage action route to update the campus digital twin model for the temporary object; If the path label of the stage action route is a discrete path label, obtaining the real-time action trajectory of the temporary object on the stage action route to update the campus digital twin model for the temporary object; The path label for determining the action route of the stage includes: Retrieving historical path data corresponding to the stage action route, and determining a path label for the stage action route based on similarity between the historical path data; The historical path data includes the historical action paths of several objects on the action routes of the stage; Determine a number of similarities based on the similarities of any two groups of historical action paths on the stage action route, and determine the similarity of each historical path data based on the average of each similarity; If the similarity of each historical path data is greater than a preset similarity, the path label of the action route of the stage is determined to be a path concentration label; If the similarity of each historical path data is less than or equal to the preset similarity, the path label of the action route in the stage is determined to be a discrete path label.

2. The method for real-time tracking of visual safety positioning in a park integrating multiple sensors according to claim 1 is characterized in that: Determine the course of action for each phase, including: Screening each of the candidate action routes based on the action mode of the temporary object to obtain a number of optional action routes; Splitting each optional action route based on the action nodes on each optional action route to obtain a plurality of alternative stage action routes; The stage action route is determined based on the association degree between the action information of the temporary object and the starting action node of each candidate stage action route.

3. The method for real-time tracking of visual safety positioning in a park integrating multiple sensors according to claim 2 is characterized in that: Predicting the movement trajectory of the temporary object along the movement route of the stage includes: Obtaining basic momentum information of the temporary object at the starting point of the action route of the stage; determining a predicted motion trajectory of the temporary object in the motion route of the stage based on the basic momentum information; The campus digital twin model for the temporary object is updated based on the predicted motion trajectory.

4. The method for real-time tracking of visual safety positioning in a park integrating multiple sensors according to claim 3 is characterized in that: Obtaining the real-time movement trajectory of the temporary object on the movement route of the stage includes: Acquiring real-time momentum information of the temporary object in the action route of the stage; determining a real-time motion trajectory of the temporary object in the stage motion route based on the real-time momentum information; The campus digital twin model for the temporary object is updated based on the real-time action trajectory.

5. The method for real-time tracking of visual safety positioning in a park integrating multiple sensors according to claim 1 is characterized in that: Also includes: Determining a feasible area based on the route range of the action route for the stage; Based on the area identifier corresponding to the feasible area and the permission information of the temporary object, it is determined whether a danger warning is triggered. If a danger warning is triggered, a warning message is issued and the digital twin model of the park is updated.

6. The method for real-time tracking of visual safety positioning in a park integrating multiple sensors according to claim 5 is characterized in that: Determining whether to trigger a danger warning based on the area identifier corresponding to the feasible area and the permission information of the temporary object includes: determining a plurality of reachable areas of the temporary object based on the permission information of the temporary object; Whether to trigger a danger warning is determined based on a comparison result of the area identifier corresponding to each of the reachable areas and the area identifier corresponding to the feasible area.

7. The method for real-time tracking of visual safety positioning in a park integrating multiple sensors according to claim 1 is characterized in that: The access information is input into the digital twin model of the park to generate several candidate action routes and corresponding action nodes, including: Inputting the access information into the digital twin model of the park to generate several candidate action routes; Evaluate each of the candidate action routes based on a preset evaluation index to determine a number of candidate action routes; The corresponding action node is determined based on the sensor coverage range in each candidate action route.

8. The method for real-time tracking of visual safety positioning in a park integrating multiple sensors according to claim 4 is characterized in that: The stage action route is determined based on the association degree between the action information of the temporary object and the starting action node of each candidate stage action route, wherein: If the maximum correlation degree between the action information of the temporary object and the starting action node of each of the candidate stage action routes is greater than a preset correlation degree, the candidate stage action route corresponding to the maximum correlation degree is determined as the stage action route.

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