Intelligent dynamic water regimen telemetering system and method

Abstract

The invention provides an intelligent dynamic water regimen telemetering system and method, and relates to the technical field of satellite communication, and the system comprises a hydro meteorological data remote obtaining module which is used for remotely obtaining the collected hydro meteorological data of a target watershed through a mixed network communication mode; wherein the mixed network communication mode at least comprises Beidou communication; and the dynamic water regimen telemetering module is used for carrying out dynamic water regimen telemetering on the target drainage basin based on the hydro-meteorological data. According to the invention, the hydrometeorological data of the target watershed are remotely acquired through a hybrid network communication mode integrating Beidou communication, the anti-interference capability of communication and the stability of data transmission are remarkably improved, and thus the timeliness and accuracy of water regimen analysis are enhanced. Besides, the system can automatically carry out dynamic water regimen telemetering based on real-time hydrometeorological data, water regimen analysis is carried out without manual intervention, the labor cost is reduced, and the analysis efficiency is greatly improved.

Description

Technical Field

[0001] The present invention relates to the field of satellite communication technology, and in particular to an intelligent dynamic water regime telemetry system and method. Background Art

[0002] Currently, when conducting remote sensing of water conditions in a river basin, it is first necessary to use remote communication to obtain the hydrological and meteorological data of the river basin, and then analyze it to obtain the water conditions.

[0003] Traditional methods for remotely acquiring hydrological and meteorological data often rely on radio communications. However, these methods are weak against interference, and data transmission is unstable, particularly in complex terrain and remote areas, significantly impacting the timeliness and effectiveness of subsequent water regime analysis. Furthermore, traditional analysis of hydrological and meteorological data often relies on manual labor, which is labor-intensive and inefficient.

[0004] Therefore, a solution is urgently needed. Summary of the Invention

[0005] One of the objectives of this invention is to provide an intelligent dynamic water regime telemetry system. By integrating hybrid network communication methods, including Beidou communications, this system remotely acquires hydrological and meteorological data from target basins, significantly improving communication interference resistance and data transmission stability, thereby enhancing the timeliness and accuracy of water regime analysis. Furthermore, the system automatically performs dynamic water regime telemetry based on real-time hydrological and meteorological data, eliminating the need for human intervention for water regime analysis. This reduces labor costs and significantly improves analysis efficiency.

[0006] An embodiment of the present invention provides an intelligent dynamic water regime telemetry system, comprising: A hydrological and meteorological data remote acquisition module is used to remotely acquire the collected hydrological and meteorological data of the target basin through a mixed network communication method; wherein the mixed network communication method includes at least: Beidou communication; The dynamic water regime telemetry module is used to perform dynamic water regime telemetry of the target basin based on hydrological and meteorological data.

[0007] Optional, intelligent dynamic water regime telemetry system also includes: The water regime visualization module is used to build a water regime visualization model based on dynamic water regime telemetry results; The water regime management decision-making assistance module is used to interactively assist users in making water regime management decisions for the target river basin based on the water regime visualization model based on a virtual camera.

[0008] Optional, interactive steps are as follows: The virtual camera is controlled to move along each active movement trajectory in the active movement trajectory sequence in the water situation visualization model in sequence, and the model images captured by the virtual camera during the active movement are displayed to the user in real time. Whenever the virtual camera starts to move along the i-th active movement trajectory in the active movement trajectory sequence, if the user starts to make a management decision at the same time, the i-th active movement trajectory is adaptively optimized based on the user's management decision content; otherwise, the passive movement control gap is planned. It allows users to control the virtual camera to passively move in the water situation visualization model within the passive movement control gap, and based on the passive movement trajectory of the virtual camera during the passive movement process, adapt and optimize the i+1th active movement trajectory in the active movement trajectory sequence.

[0009] Optionally, the steps for acquiring the active movement trajectory sequence are as follows: Search for management demand events from water situation visualization models; Create an associated active movement trajectory for each management demand event; The active movement trajectories are sorted from large to small according to the priority weights of the management demand events associated with them to obtain the active movement trajectory sequence.

[0010] Optionally, the steps of adaptively optimizing the i-th active movement trajectory are as follows: Based on the real-time compliance between the first logic of the management decision content and the second logic of the corresponding standard of the first i-1 active movement trajectories in the active movement trajectory sequence, the logic compliance-time curve is updated; When a complete peak segment first appears on the logic compliance-time curve, the trigger content distribution of the second logic is determined from the visualization model; Plan the shortest movement trajectory of the virtual camera to cover the distribution of the triggered content; Determine the first trajectory point closest to the starting point of the shortest trajectory from the i-th active movement trajectory; When the bifurcation cost of the first trajectory point does not exceed the threshold cost, the shortest moving trajectory is used as the temporary bifurcation path of the first trajectory point; otherwise, the second trajectory point with the minimum bifurcation cost within the preset trajectory range before and after the first trajectory point is determined from the i-th active moving trajectory; The shortest moving trajectory is used as a temporary branching road at the second trajectory point.

[0011] Optionally, the steps for planning the passive motion control gap are as follows: Determining the jth first captured content from the first captured content sequence of the i-th active movement trajectory; wherein the feature distributions of the first j-1 first captured content in the captured content sequence are first matched with the standard feature distribution; Create a start time and an end time respectively; the start time is the time when the virtual camera actively moves along the i-th active movement trajectory and covers the j-th first shot coverage content; the end time is the time when the virtual camera actively moves along the i-th active movement trajectory and ends; Create a passive motion control gap based on the start and end times.

[0012] Optionally, the steps of adaptively optimizing the i+1th active movement trajectory in the active movement trajectory sequence are as follows: Extract the association relationship between the second shot coverage content sequence of the passive movement trajectory and the third shot coverage content sequence of the (i+1)th active movement trajectory; based on the association relationship, attempt to search for association indicator content next to two adjacent second shot coverage contents in the third shot coverage content sequence in the water condition visualization model; When the search is found, the virtual camera is planned to follow the original shooting trajectory corresponding to the adjacent second shooting coverage content in the (i+1)th active movement trajectory to shoot a replacement trajectory that covers the associated indication content; The replacement trajectory is used to replace the original shooting trajectory in the i+1th active movement trajectory.

[0013] An embodiment of the present invention provides an intelligent dynamic water regime remote sensing method, characterized by comprising: Remotely obtain the collected hydrological and meteorological data of the target basin through a hybrid network communication method; wherein the hybrid network communication method includes at least: Beidou communication; Based on hydrological and meteorological data, dynamic water regime telemetry is carried out in the target basin.

[0014] Optional, intelligent dynamic water regime telemetry method also includes: Build a water regime visualization model based on dynamic water regime telemetry results; Based on the virtual camera, users are interactively assisted to make water management decisions for the target watershed according to the water regime visualization model.

[0015] Optional, interactive steps are as follows: The virtual camera is controlled to move along each active movement trajectory in the active movement trajectory sequence in the water situation visualization model in sequence, and the model images captured by the virtual camera during the active movement are displayed to the user in real time. Whenever the virtual camera starts to move along the i-th active movement trajectory in the active movement trajectory sequence, if the user starts to make a management decision at the same time, the i-th active movement trajectory is adaptively optimized based on the user's management decision content; otherwise, the passive movement control gap is planned. It allows users to control the virtual camera to passively move in the water situation visualization model within the passive movement control gap, and based on the passive movement trajectory of the virtual camera during the passive movement process, adapt and optimize the i+1th active movement trajectory in the active movement trajectory sequence.

[0016] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0017] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 A schematic diagram of an intelligent dynamic water regime telemetry system according to an embodiment of the present invention; Figure 2 This is a flow chart of an intelligent dynamic water regime telemetry method in an embodiment of the present invention. DETAILED DESCRIPTION

[0019] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0020] Example 1: The embodiment of the present invention provides an intelligent dynamic water regime telemetry system, such as Figure 1 Shown, including: The hydrological and meteorological data remote acquisition module 1 is used to remotely acquire the collected hydrological and meteorological data of the target basin through a mixed network communication method; wherein the mixed network communication method at least includes: Beidou communication; Dynamic water regime telemetry module 2 is used to perform dynamic water regime telemetry on the target basin based on hydrological and meteorological data.

[0021] The target basin is the river basin where water regime telemetry is required. Sensors deployed within the target basin collect real-time hydrometeorological data, including water level, flow, precipitation, temperature, and humidity. This data is remotely acquired via hybrid network communications, which can include various communication methods, including Beidou communications, and cellular communications. By analyzing this hydrometeorological data, the water regime of the target basin can be determined, enabling dynamic water regime telemetry. This analysis allows for real-time calculation of water level changes, flow forecasting, and flood warnings. Machine learning models can also be developed based on extensive manual water regime analysis experience, allowing for analysis of hydrometeorological data.

[0022] This embodiment of the present invention integrates hybrid network communication methods, including Beidou communications, to remotely acquire hydrological and meteorological data from the target basin. This significantly improves communication anti-interference capabilities and data transmission stability, thereby enhancing the timeliness and accuracy of water regime analysis. Furthermore, the system automatically performs dynamic water regime telemetry based on real-time hydrological and meteorological data, eliminating the need for human intervention for water regime analysis. This reduces labor costs and significantly improves analysis efficiency.

[0023] Example 2: In one embodiment, the intelligent dynamic water regime telemetry system further includes: The water regime visualization module is used to build a water regime visualization model based on dynamic water regime telemetry results; The water regime management decision-making assistance module is used to interactively assist users in making water regime management decisions for the target river basin based on the water regime visualization model based on a virtual camera.

[0024] When constructing a water regime visualization model, dynamic water regime telemetry results, including water level changes, predicted flow rates, and flood warning information, are placed at corresponding locations on a three-dimensional map of the target basin according to their geographic locations. This creates a water regime visualization model. A virtual camera moves within the model and captures the captured images for users to view, replacing the need for manual navigation. This interactive virtual camera assists users in making water regime management decisions for the target basin based on the model, improving their understanding of and decision-making efficiency, and providing a more user-friendly experience.

[0025] Example 3: In water situation visualization models, users often need to manually browse numerous model screens or views to make effective decisions in complex water scenarios. This is not only time-consuming but also easily influenced by individual operational experience, potentially leading to decision delays or misjudgments. Especially when there are multiple management demand events, users cannot efficiently process each one individually, significantly reducing decision-making efficiency and accuracy.

[0026] Furthermore, during the decision-making process, the virtual camera's movement trajectory is often fixed, lacking sufficient flexibility to respond to users' immediate decision-making needs. If the virtual camera's display does not match the user's decision needs while the user is making a decision, it may affect the consistency and accuracy of the decision.

[0027] Therefore, in order to solve the above technical problems, in one embodiment, the steps of interactive assistance are as follows: The virtual camera is sequentially controlled to actively move along each active movement trajectory in the active movement trajectory sequence in the water situation visualization model, and the model images captured by the virtual camera during the active movement are displayed to the user in real time. Whenever the virtual camera starts to actively move along the i-th active movement trajectory in the active movement trajectory sequence, if the user starts to make a management decision at the same time, the i-th active movement trajectory (i is an integer from 1 to M-1, and M is the total number of active movement trajectories in the active movement trajectory sequence) is adaptively optimized based on the user's management decision. Otherwise, the passive movement control gap is planned. Allow users to control the virtual camera to passively move in the water situation visualization model within the passive movement control interval, and based on the passive movement trajectory of the virtual camera during the passive movement process, adapt and optimize the i+1th active movement trajectory in the active movement trajectory sequence; The steps for obtaining the active movement trajectory sequence are as follows: Search for management demand events from water situation visualization models; Create an associated active movement trajectory for each management demand event; The active movement trajectories are sorted from large to small according to the priority weights of the management demand events associated with them to obtain the active movement trajectory sequence.

[0028] When setting up an active motion trajectory sequence, the water regime visualization model searches for management demand events (water regime events that require user management decisions, such as heavy rain warnings in areas with concentrated rainfall, abnormal water temperature changes in water bodies, and flood warnings). For each management demand event, an associated active motion trajectory is created. (As the virtual camera moves along the active motion trajectory, the footage sequentially displays all the details of the management demand event. For example, for a heavy rain warning event in a concentrated rainfall area, the associated active motion trajectory created allows the virtual camera to move along it, starting with a high-altitude aerial view of the area about to be affected by the heavy rain, followed by a display of the ground conditions affected by the heavy rain, with a focus on areas at risk of flash floods or mudslides.) On the active motion trajectory, the virtual camera's shooting position is constrained by trajectory points, and a shooting angle is set at the corresponding trajectory point. When the virtual camera reaches that trajectory point, it captures the image according to that angle. The priority weight of a management demand event represents the degree of priority that requires the user to make a decision when searching for a management demand event. It can be used to quantify the severity of the management demand event and the user's ability to make decisions about the management demand event. The active movement trajectories are sorted from large to small according to the priority weights of their associated management demand events, so that the virtual camera can prioritize displaying the event status of management demand events with high priority weights through the shooting screen.

[0029] In this way, when the virtual camera is controlled to move along the active movement trajectory in sequence, it can display the search management demand events to the user in sequence through the captured model images, without the need for users to operate and browse by themselves, thereby improving convenience.

[0030] When the virtual camera starts to actively move along the i-th active movement trajectory, if the user starts to make management decisions simultaneously, it means that the user wants to start making management decisions after viewing the model image previously captured by the virtual camera. At this time, if the virtual camera still actively moves along the i-th active movement trajectory, it will definitely affect the user's decision-making process (such as affecting their decision-making ideas). Therefore, based on the user's management decision content, the i-th active movement trajectory is adaptively optimized to overcome this problem.

[0031] Secondly, if the user does not start making management decisions synchronously, a passive movement control interval is planned to allow the user to control the virtual camera to passively move in the water situation visualization model at an appropriate time. During this process, the passive movement trajectory of the virtual camera will reflect the user's real-time management decision intention to a certain extent. Therefore, based on this, the i+1th active movement trajectory in the active movement trajectory sequence is adaptively optimized, so that the subsequent active movement trajectories can make changes that are consistent with the real-time management decision intention, thereby improving humanization.

[0032] After adaptively optimizing the i-th active movement trajectory, or adaptively optimizing the i+1-th active movement trajectory in the active movement trajectory sequence, the virtual camera will subsequently move along the i-th active movement trajectory or the i+1-th active movement trajectory after adaptive optimization.

[0033] The system of an embodiment of the present invention can dynamically adjust the movement trajectory and display content of the virtual camera based on the user's management decisions, thereby optimizing the user's decision-making process. Specifically, the system adopts two modes: active movement mode and passive movement mode. In active movement mode, the system displays management demand events according to priority and instantly adapts and optimizes the trajectory of the virtual camera based on factors such as the user's decision-making needs, thereby avoiding the interference of a fixed trajectory on decision-making thinking. Passive movement mode allows the user to independently control the virtual camera at the appropriate time, thereby providing flexible decision-making support, and reflects the user's real-time decision-making intention through the passive movement trajectory of the virtual camera, further optimizing the trajectory.

[0034] This real-time adaptive optimization technology significantly enhances the autonomy and flexibility of the virtual camera, ensuring that the most relevant water events are prioritized during the decision-making process, preventing irrelevant content from interfering with user decisions, and thus making decisions more accurate and efficient. This not only improves the user experience but also greatly enhances the system's decision-making support capabilities, enabling it to better meet users' immediate decision-making needs in complex water management scenarios.

[0035] Example 4: In one embodiment, the steps of adaptively optimizing the i-th active movement trajectory are as follows: Based on the real-time compliance between the first logic of the management decision content and the second logic of the corresponding standard of the first i-1 active movement trajectories in the active movement trajectory sequence, the logic compliance-time curve is updated; When a complete peak segment first appears on the logic compliance-time curve, the trigger content distribution of the second logic is determined from the visualization model; Plan the shortest movement trajectory of the virtual camera to cover the distribution of the triggered content; Determine the first trajectory point closest to the starting point of the shortest trajectory from the i-th active movement trajectory; When the bifurcation cost of the first trajectory point does not exceed the threshold cost, the shortest moving trajectory is used as the temporary bifurcation path of the first trajectory point; otherwise, the second trajectory point with the minimum bifurcation cost within the preset trajectory range before and after the first trajectory point is determined from the i-th active moving trajectory; The shortest trajectory serves as a temporary fork in the road at the second trajectory point. The second logic refers to the management decision logic that users should have after viewing the model images captured by the virtual camera along the first i-1 active movement trajectories. For example, if the model images captured by the first i-1 active movement trajectories show water level changes in different areas, traffic conditions in different areas, and the distribution of management personnel, the second logic will determine how to dispatch management personnel.

[0036] Whenever a management decision changes, the first logic is extracted, and its real-time conformance with the second logic (which can be calculated as the similarity between the two) is calculated. The current time is recorded, and the corresponding coordinate point of the real-time conformance is determined on the logical conformance-time curve. The original curve is then connected to this coordinate point to complete the update of the logical conformance-time curve. A peak segment is a region of the curve where the change in real-time conformance fluctuates and reaches a high peak at a certain moment. When the logical conformance-time curve first shows a complete peak segment, it indicates that the first logic is gradually approaching the second logic. After reaching the closest point, the two begin to diverge. At this point, it is optimal to adaptively optimize the i-th active movement trajectory to help the user quickly return to the second logic.

[0037] The trigger content distribution of the second logic refers to the distribution positions of multiple contents related to the second logic in the visualization model. For example, if the second logic is to decide how to dispatch management personnel, the relevant content is the location of the management personnel, etc. The model positions of these contents in the water situation visualization model jointly constitute the trigger content distribution.

[0038] The i-th active movement trajectory is set based on the principle that the virtual camera moves along it so that the captured image can fully display the entire situation of a search management event. If the shortest movement trajectory is directly added to it, this principle will be violated. Therefore, the two need to be optimally combined.

[0039] The bifurcation cost refers to the degree to which the setting of a temporary bifurcation at a trajectory point affects the above principles. It can be calculated as the weighted sum of the position ratio of the trajectory point (the larger the position ratio, the more shots the user has viewed, i.e. the greater the impact) and the degree of correlation between the contents of the shots taken by the virtual camera in front of the trajectory point and within a certain distance (e.g. 5 meters) (the greater the correlation, the more continuous shooting is needed, and the greater the impact) (the weight of the two can be set by technical personnel based on their relative impact on the bifurcation cost).

[0040] The preset trajectory range can be 10 meters. The threshold cost is a threshold representing a larger bifurcation cost. When performing the optimal combination, if the bifurcation cost of the first trajectory point does not exceed the threshold cost, the shortest trajectory is used as a temporary bifurcation for the first trajectory point. Otherwise, the shortest trajectory is used as a temporary bifurcation for the second trajectory point. When the virtual camera reaches the corresponding first or second trajectory point, it will first move along the temporary bifurcation and then continue moving along the remaining active trajectory to the corresponding first or second trajectory point.

[0041] This embodiment of the present invention updates the logical conformance-time curve. When the curve first reaches a complete peak, it begins adaptively optimizing the i-th active movement trajectory. This helps users align more closely with the secondary logic at the optimal moment, significantly improving assistance efficiency while also making the system more user-friendly and intelligent. Furthermore, based on the bifurcation cost and the distance between the i-th active movement trajectory and the shortest movement trajectory, temporary bifurcations are dynamically set to ensure that the i-th active movement trajectory remains compliant during the assistance process, significantly enhancing the system's flexibility and applicability.

[0042] Example 5: In one embodiment, the steps for planning the passive motion control gap are as follows: Determine the jth (j is an integer from 1 to N, where N is the total number of first captured content in the first captured content sequence) first captured content from the first captured content sequence of the i-th active movement trajectory; wherein the feature distributions of the first j-1 first captured content in the captured content sequence are first matched with the standard feature distribution; Create a start time and an end time respectively; the start time is the time when the virtual camera actively moves along the i-th active movement trajectory and covers the j-th first shot coverage content; the end time is the time when the virtual camera actively moves along the i-th active movement trajectory and ends; Create a passive motion control gap based on the start and end times.

[0043] The first captured content sequence of the i-th active motion trajectory includes the content captured and covered in the water regime visualization model by the virtual camera as it actively moves along the i-th active motion trajectory. The feature distribution includes at least content type and inter-content relationships. When the feature distribution of the first j-1 captured content in the captured content sequence matches the standard feature distribution, the user can passively control the virtual camera's movement at the moment the virtual camera completes capturing and covering the j-th captured content while actively moving along the i-th active motion trajectory. For example, if the standard feature distribution includes content types such as water level values ​​and trends, dam cracks and breach risks, river channel expansion areas, and siltation areas, then the user urgently needs to monitor flood trends, potential dam weaknesses, and possible siltation changes in a specific area. At this moment, the virtual camera's movement can be passively controlled based on user needs. The end time is the moment when the virtual camera's active movement along the i-th active motion trajectory ends. A passive motion control gap is created using the start and end times as the gap start and end times, respectively.

[0044] The embodiment of the present invention accurately determines the start and end times and plans the passive movement control gap of the virtual camera, so that the virtual camera can be dynamically adjusted according to user needs at the optimal time, thereby improving the user experience and further enhancing the applicability of the system.

[0045] Example 6: In one embodiment, the steps of adaptively optimizing the i+1th active movement trajectory in the active movement trajectory sequence are as follows: Extract the association relationship between the second shot coverage content sequence of the passive movement trajectory and the third shot coverage content sequence of the (i+1)th active movement trajectory; based on the association relationship, attempt to search for association indicator content next to two adjacent second shot coverage contents in the third shot coverage content sequence in the water condition visualization model; When the search is found, the virtual camera is planned to follow the original shooting trajectory corresponding to the adjacent second shooting coverage content in the (i+1)th active movement trajectory to shoot a replacement trajectory that covers the associated indication content; The replacement trajectory is used to replace the original shooting trajectory in the i+1th active movement trajectory.

[0046] Correspondingly, the second and third sequences of captured content each contain the content captured and captured in the water regime visualization model as the virtual camera moves along the passive and active motion trajectories, respectively. The extracted associations between the two include at least spatial overlap and content similarity. "Next to" two adjacent second-shot coverage contents means that the distance between the associated indicator content and the adjacent second-shot coverage content does not exceed a certain value (e.g., 20 meters). Based on these associations, the third sequence of captured content is searched for associated indicators next to two adjacent second-shot coverage contents. For example, if the associated indicators overlap in the geographic space of dynamic water level changes, environmental pollution, and zooplankton distribution, the associated indicators searched for are areas related to water flow, pollutant diffusion, and so on. After planning the replacement trajectory, it replaces the original capture trajectory, allowing users to quickly view the content relevant to the management decision-making intentions reflected in their passive motion trajectory.

[0047] By adaptively optimizing the (i+1)th active motion trajectory and combining it with the captured content association of the passive motion trajectory, the embodiment of the present invention can dynamically adjust the trajectory planning to ensure that the virtual camera covers important content related to the user's management decision-making intention reflected by the passive motion trajectory during the shooting process, thereby improving the user's management decision-making efficiency and being more user-friendly.

[0048] The embodiment of the present invention provides an intelligent dynamic water regime telemetry method, such as Figure 2 Shown, including: S1. Remotely acquire the collected hydrological and meteorological data of the target basin through a hybrid network communication method; wherein the hybrid network communication method includes at least Beidou communication; S2. Based on hydrological and meteorological data, dynamic water regime telemetry is performed on the target basin.

[0049] The intelligent dynamic water regime telemetry method also includes: Build a water regime visualization model based on dynamic water regime telemetry results; Based on the virtual camera, users are interactively assisted to make water management decisions for the target watershed according to the water regime visualization model.

[0050] The steps for interactive assistance are as follows: The virtual camera is controlled to move along each active movement trajectory in the active movement trajectory sequence in the water situation visualization model in sequence, and the model images captured by the virtual camera during the active movement are displayed to the user in real time. Whenever the virtual camera starts to move along the i-th active movement trajectory in the active movement trajectory sequence, if the user starts to make a management decision at the same time, the i-th active movement trajectory is adaptively optimized based on the user's management decision content; otherwise, the passive movement control gap is planned. It allows users to control the virtual camera to passively move in the water situation visualization model within the passive movement control gap, and based on the passive movement trajectory of the virtual camera during the passive movement process, adapt and optimize the i+1th active movement trajectory in the active movement trajectory sequence.

[0051] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. An intelligent dynamic water regime telemetry system, characterized in that: include: A hydrological and meteorological data remote acquisition module is used to remotely acquire the collected hydrological and meteorological data of the target basin through a mixed network communication method; wherein the mixed network communication method includes at least: Beidou communication; The dynamic water regime telemetry module is used to perform dynamic water regime telemetry of the target basin based on hydrological and meteorological data.

2. The intelligent dynamic water regime telemetry system according to claim 1, characterized in that: Also includes: The water regime visualization module is used to build a water regime visualization model based on dynamic water regime telemetry results; The water regime management decision-making assistance module is used to interactively assist users in making water regime management decisions for the target river basin based on the water regime visualization model based on a virtual camera.

3. The intelligent dynamic water regime telemetry system according to claim 2, characterized in that: The steps for interactive assistance are as follows: The virtual camera is controlled to move along each active movement trajectory in the active movement trajectory sequence in the water situation visualization model in sequence, and the model images captured by the virtual camera during the active movement are displayed to the user in real time. Whenever the virtual camera starts to move along the i-th active movement trajectory in the active movement trajectory sequence, if the user starts to make a management decision at the same time, the i-th active movement trajectory is adaptively optimized based on the user's management decision content. Otherwise, plan the passive mobile control gap; It allows users to control the virtual camera to passively move in the water situation visualization model within the passive movement control gap, and based on the passive movement trajectory of the virtual camera during the passive movement process, adapt and optimize the i+1th active movement trajectory in the active movement trajectory sequence.

4. The intelligent dynamic water regime telemetry system according to claim 3, characterized in that: The steps for obtaining the active movement trajectory sequence are as follows: Search for management demand events from water situation visualization models; Create an associated active movement trajectory for each management demand event; The active movement trajectories are sorted from large to small according to the priority weights of the management demand events associated with them to obtain the active movement trajectory sequence.

5. The intelligent dynamic water regime telemetry system according to claim 3, characterized in that: The steps for adaptive optimization of the i-th active movement trajectory are as follows: Based on the real-time compliance between the first logic of the management decision content and the second logic of the corresponding standard of the first i-1 active movement trajectories in the active movement trajectory sequence, the logic compliance-time curve is updated; When a complete peak segment first appears on the logic compliance-time curve, the trigger content distribution of the second logic is determined from the visualization model; Plan the shortest movement trajectory of the virtual camera to cover the distribution of the triggered content; Determine the first trajectory point closest to the starting point of the shortest trajectory from the i-th active movement trajectory; When the bifurcation cost of the first trajectory point does not exceed the threshold cost, the shortest moving trajectory is used as the temporary bifurcation road of the first trajectory point; Otherwise, determine the second trajectory point with the minimum bifurcation cost within the preset trajectory range before and after the first trajectory point from the i-th active movement trajectory; The shortest moving trajectory is used as a temporary branching road at the second trajectory point.

6. The intelligent dynamic water regime telemetry system according to claim 3, characterized in that: The steps for planning passive motion control clearance are as follows: Determining the jth first captured content from the first captured content sequence of the i-th active movement trajectory; wherein the feature distributions of the first j-1 first captured content in the captured content sequence are first matched with the standard feature distribution; Create a start time and an end time respectively; the start time is the time when the virtual camera actively moves along the i-th active movement trajectory and covers the j-th first shot coverage content; the end time is the time when the virtual camera actively moves along the i-th active movement trajectory and ends; Create a passive motion control gap based on the start and end times.

7. The intelligent dynamic water regime telemetry system according to claim 3, characterized in that: The steps for adaptive optimization of the i+1th active movement trajectory in the active movement trajectory sequence are as follows: Extract the association relationship between the second shot coverage content sequence of the passive movement trajectory and the third shot coverage content sequence of the (i+1)th active movement trajectory; based on the association relationship, attempt to search for association indicator content next to two adjacent second shot coverage contents in the third shot coverage content sequence in the water condition visualization model; When the search is found, the virtual camera is planned to follow the original shooting trajectory corresponding to the adjacent second shooting coverage content in the (i+1)th active movement trajectory to shoot a replacement trajectory that covers the associated indication content; The replacement trajectory is used to replace the original shooting trajectory in the i+1th active movement trajectory.

8. An intelligent dynamic water regime remote sensing method, characterized in that: include: Remotely obtain the collected hydrological and meteorological data of the target basin through a hybrid network communication method; wherein the hybrid network communication method includes at least: Beidou communication; Based on hydrological and meteorological data, dynamic water regime telemetry is carried out in the target basin.

9. The intelligent dynamic water regime remote sensing method according to claim 8, characterized in that: Also includes: Build a water regime visualization model based on dynamic water regime telemetry results; Based on the virtual camera, users are interactively assisted to make water management decisions for the target watershed according to the water regime visualization model.

10. The intelligent dynamic water regime remote sensing method according to claim 9, characterized in that: The steps for interactive assistance are as follows: The virtual camera is controlled to move along each active movement trajectory in the active movement trajectory sequence in the water situation visualization model in sequence, and the model images captured by the virtual camera during the active movement are displayed to the user in real time. Whenever the virtual camera starts to move along the i-th active movement trajectory in the active movement trajectory sequence, if the user starts to make a management decision at the same time, the i-th active movement trajectory is adaptively optimized based on the user's management decision content. Otherwise, plan the passive mobile control gap; It allows users to control the virtual camera to passively move in the water situation visualization model within the passive movement control gap, and based on the passive movement trajectory of the virtual camera during the passive movement process, adapt and optimize the i+1th active movement trajectory in the active movement trajectory sequence.

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