Tourism geographic data acquisition and management method and system

Abstract

The invention relates to the technical field of tourism geographic data collection, in particular to a tourism geographic data collection management method and system, and the method comprises the steps: obtaining an original geographic image sent by a passenger, generating a real-time geographic image, and recognizing a geographic collection region, an image main body, an image main body state and image collection time in the real-time geographic image; screening out a selected geographic area from the geographic acquisition areas, and generating image main body dynamic data; and performing geographic data updating on the selected geographic area according to the image main body dynamic data, and generating updated area geographic data. The problems of signal drifting and inaccurate acquisition caused by positioning acquisition depending on a mobile terminal in the prior art are solved, the acquisition cost of the tourism geographic data is effectively reduced, the tourism geographic data is finely acquired based on the travel route in the tourism process of the traveler by fully utilizing the information acquisition capability of the traveler, and the accuracy of the tourism geographic data is improved. And the acquisition precision of the tourism geographic data is improved.

Description

Technical Field

[0001] This application relates to the field of tourism geographic data collection technology, and in particular to a tourism geographic data collection and management method and system. Background Technology

[0002] With the development of the tourism industry, the collection of tourism geographic data is of paramount importance. Accurate and real-time collection of tourism geographic data helps to integrate tourism information resources, making them a productive force for tourism development and an important means to promote the development and management of the tourism industry.

[0003] There are various methods for collecting tourism geographic data, including manual collection, mobile terminal collection, drone detection, and satellite exploration. However, current methods for collecting tourism geographic data have problems. Manual collection is hampered by limited personnel and working hours at scenic spots, making real-time collection impossible and failing to cover the entire area. Mobile terminal collection is prone to signal drift in remote areas, leading to inaccurate detection. Drone detection involves flight control issues and is suitable for high-altitude detection; low-altitude detection within scenic areas can disrupt tourist activities and pose safety hazards. Satellite detection is costly and more suitable for large-scale geographic surveys, making it unsuitable for the detailed collection of geographic data for specific scenic areas.

[0004] Therefore, there is an urgent need to design a tourism geographic data collection and management method and system to solve the problems existing in the above-mentioned technologies. Summary of the Invention

[0005] Therefore, it is necessary to provide a tourism geographic data collection and management method and system to address the aforementioned technical problems. This method and system can solve the signal drift and inaccurate data collection issues caused by reliance on mobile terminal positioning in existing technologies. Furthermore, it eliminates the need for drones and satellite detection, effectively reducing the cost of tourism geographic data collection. By fully utilizing the information collection capabilities of tourists, it enables refined collection of tourism geographic data based on the travel routes of tourists during their travels, thereby improving the accuracy of tourism geographic data collection.

[0006] The technical solution of this invention is as follows: A method for collecting and managing tourism geographic data, the method comprising: The system acquires raw geographic images sent by passengers and generates real-time geographic images based on the raw geographic images, wherein the real-time geographic images conform to preset geographic data collection standards. Identify the geographic acquisition area, image subject, image subject status, and image acquisition time in the real-time geographic imagery; Selected geographic regions are selected from each of the geographic acquisition regions, and dynamic data of the image subjects are generated based on the image subject status and image acquisition time corresponding to the image subjects in the selected geographic regions. The selected geographic area is updated based on the dynamic data of the main image subject, and the updated regional geographic data is generated.

[0007] Optionally, the original geographic imagery includes original geographic video and original geographic images; The geographic data acquisition standards include video acquisition standards and image acquisition standards. The video acquisition standards include: the captured video contains at least two geographic landmarks. Obtain the raw geographic imagery sent by the passenger, including: Based on the image capture trigger command triggered by the passenger's touch screen, the system outputs collection guidance information and acquires the original geographical video captured by the passenger based on the collection guidance information. The collection guidance information is used to guide the passenger to capture video according to the video capture standards. In response to acquiring raw geographic video, guide travelers to take images and acquire the raw geographic images taken by the travelers.

[0008] Optionally, the real-time geographic imagery includes real-time geographic video and real-time geographic images; Generating real-time geographic images based on the original geographic images includes: The original geographic video is subjected to compliance verification according to the video acquisition standard. If the compliance verification is qualified, a real-time geographic video is generated. The original geographic image is verified for compliance according to the image acquisition standard. If the compliance verification is successful, a real-time geographic image is generated.

[0009] Optionally, identifying the geographic acquisition area, image subject, image subject status, and image acquisition time in the real-time geographic imagery includes: The geographic landmarks in the real-time geographic image are compared with a pre-stored landmark sequence list, and geographic collection areas are selected. The landmark sequence list includes standard geographic areas and corresponding standard landmarks. The geographic collection area is the standard geographic area corresponding to the standard landmark that is the same as the geographic landmark. The real-time geographic imagery is analyzed to extract the image subject, the image subject status, and the image acquisition time.

[0010] Optionally, selecting a geographic region from each of the said geographic data collection regions includes: Regional risk features are extracted from each of the aforementioned geographic data collection areas, and regional risk feature vectors are generated based on the regional risk features. The risk event data is generated by matching the regional risk feature vector with the event feature template. High-risk areas are identified based on the risk event data, and these high-risk areas are set as selected geographical regions.

[0011] Optionally, risk event data is generated by matching the regional risk feature vector with the event feature template, including: Feature values ​​corresponding to each event feature template are extracted from the regional risk feature vector, wherein each event feature template is preset. Determine whether the event determination condition is met based on the value of the feature item; If the determination criteria are met, risk event data is generated, which includes the risk event type and event intensity.

[0012] Optionally, high-risk areas are determined based on the risk event data, and the high-risk areas are set as selected geographical areas, including: A risk level coefficient is generated based on the risk event data corresponding to the geographically collected area. A risk assessment value is generated based on the risk level coefficient and the corresponding event intensity. High-risk areas are identified based on the risk assessment values, and these high-risk areas are designated as selected geographical regions.

[0013] Optionally, the selected geographic area is updated with geographic data based on the dynamic data of the image subject, and updated regional geographic data is generated, including: Extract the latest status data of the selected geographic area from the dynamic data of the main image subject; Extract the target time window summary status of the selected geographic region from the dynamic data of the main image subject; The geographic data is updated based on the latest status data and the target time window summary status, and the updated regional geographic data is generated.

[0014] Optionally, a tourism geographic data collection and management system is also provided, the system comprising: The geographic image acquisition module is used to acquire raw geographic images sent by passengers and generate real-time geographic images based on the raw geographic images, wherein the real-time geographic images conform to preset geographic data acquisition standards. The geographic data recognition module is used to identify the geographic acquisition area, image subject, image subject status, and image acquisition time in the real-time geographic image. The geographic region analysis module is used to filter out selected geographic regions from the various geographic acquisition regions, and generate dynamic data of the image subject based on the image subject status and image acquisition time corresponding to the image subject in the selected geographic region. The geographic region update module is used to update the geographic data of the selected geographic region based on the dynamic data of the image subject, and generate updated geographic data of the region.

[0015] Optionally, the original geographic imagery includes original geographic video and original geographic images; the geographic data acquisition standards include video acquisition standards and image acquisition standards, wherein the video acquisition standards include: the captured video contains at least two geographic landmarks; the geographic image acquisition module is further configured to: output acquisition guidance information according to the image capture trigger command touched by the passenger, and acquire the original geographic video captured by the passenger based on the acquisition guidance information, wherein the acquisition guidance information is used to guide the passenger to capture images according to the video acquisition standards; in response to acquiring the original geographic video, guide the passenger to capture images and acquire the original geographic images captured by the passenger.

[0016] Optionally, the real-time geographic imagery includes real-time geographic video and real-time geographic images; the geographic imagery acquisition module is further configured to: perform compliance verification on the original geographic video according to the video acquisition standard, and if the compliance verification is qualified, generate real-time geographic video; perform compliance verification on the original geographic image according to the image acquisition standard, and if the compliance verification is qualified, generate real-time geographic images.

[0017] Optionally, the geographic data identification module is further configured to: compare the geographic landmarks in the real-time geographic image with a pre-stored landmark sequence list and filter out the geographic acquisition area, wherein the landmark sequence list includes standard geographic areas and corresponding standard landmarks, and the geographic acquisition area is the standard geographic area corresponding to the standard landmark that is the same as the geographic landmark; analyze the real-time geographic image and extract the image subject, the image subject status and the image acquisition time.

[0018] Optionally, the geographic region analysis module is further configured to: extract regional risk features from each of the geographic collection areas, and generate regional risk feature vectors based on the regional risk features; match the regional risk feature vectors with event feature templates, and generate risk event data; determine high-risk areas based on the risk event data, and set the high-risk areas as selected geographic regions.

[0019] Optionally, the geographic region analysis module is further configured to: extract feature values ​​corresponding to each event feature template from the regional risk feature vector, wherein each event feature template is preset; determine whether the event determination conditions are met based on the feature values; if the determination conditions are met, generate risk event data, wherein the risk event data includes risk event type and event intensity.

[0020] Optionally, the geographic region analysis module is further configured to: generate a risk level coefficient based on the risk event data corresponding to the geographic collection area; generate a risk assessment value based on the risk level coefficient and the corresponding event intensity; determine high-risk areas based on the risk assessment value, and set the high-risk areas as selected geographic regions.

[0021] Optionally, the geographic region update module is further configured to: extract the latest status data of the selected geographic region from the dynamic data of the image subject; extract the target time window summary status of the selected geographic region from the dynamic data of the image subject; update the geographic data according to the latest status data and the target time window summary status, and generate updated regional geographic data.

[0022] Optionally, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps described in the above-described tourism geographic data collection and management method.

[0023] Optionally, a computer-readable storage medium is also provided, on which a computer program is stored, which, when executed by a processor, implements the steps described in the above-described tourism geographic data collection and management method.

[0024] The technical effects achieved by this invention are as follows: The aforementioned tourism geographic data collection and management method and system acquires original geographic images sent by tourists and generates real-time geographic images based on these original images, wherein the real-time geographic images conform to preset geographic data collection standards; identifies the geographic collection area, image subject, image subject status, and image collection time in the real-time geographic images; selects a chosen geographic area from each of the geographic collection areas and generates dynamic data of the image subject based on the image subject status and image collection time corresponding to the image subject in the chosen geographic area; updates the geographic data of the chosen geographic area based on the dynamic data of the image subject and generates updated regional geographic data. This application implements preset geographic data collection standards, filters raw geographic images taken by tourists during their travels, and selects real-time geographic images that meet the standards. It then identifies the geographic collection area, image subject, image subject status, and image collection time within these real-time images, and selects a chosen geographic area from each of these areas. Based on the image subject status and image collection time within the selected geographic area, it generates dynamic data for the image subject. Subsequently, it updates the geographic data of the selected geographic area based on this dynamic data, generating updated regional geographic data. This achieves the collection and management of tourism geographic data, significantly reducing workload during peak tourist seasons. The presence of tourism geographic data collection personnel in scenic areas allows staff to focus on maintaining safety and order, reducing the cost of collecting tourism geographic data. Although mobile terminals are used during filming, the data collection does not rely on the positioning of the mobile terminals themselves. Instead, it obtains relevant information about the geographic collection area based on the analysis of real-time geographic images. This solves the signal drift and inaccurate data collection problems caused by reliance on mobile terminal positioning in existing technologies. Furthermore, it eliminates the need for drones and satellite detection, effectively reducing the cost of collecting tourism geographic data. By fully utilizing the information collection capabilities of tourists, it enables refined collection of tourism geographic data based on the tourist's travel routes, improving the accuracy of tourism geographic data collection. Attached Figure Description

[0025] Figure 1 This is a flowchart illustrating a tourism geographic data collection and management method in one embodiment; Figure 2 This is a structural block diagram of a tourism geographic data collection and management system in one embodiment. Detailed Implementation

[0026] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0027] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0028] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0029] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."

[0030] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0031] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0032] In one embodiment, a terminal is provided, the terminal being configured to: acquire raw geographic images sent by passengers, and generate real-time geographic images based on the raw geographic images, wherein the real-time geographic images conform to preset geographic data acquisition standards; identify geographic acquisition areas, image subjects, image subject status, and image acquisition time in the real-time geographic images; select a selected geographic area from each of the geographic acquisition areas, and generate dynamic data of the image subject based on the image subject status and image acquisition time corresponding to the image subject in the selected geographic area; update the geographic data of the selected geographic area based on the dynamic data of the image subject, and generate updated regional geographic data.

[0033] The terminal may be, but is not limited to, various personal computers, laptops, smartphones, tablets, and portable wearable devices.

[0034] In one embodiment, such as Figure 1 As shown, a method for collecting and managing tourism geographic data is provided, the method comprising: Step S100: Acquire the original geographic image sent by the passenger, and generate a real-time geographic image based on the original geographic image, wherein the real-time geographic image conforms to the preset geographic data collection standard. Step S200: Identify the geographic acquisition area, image subject, image subject status, and image acquisition time in the real-time geographic image; Step S300: Select a geographic region from each of the geographic acquisition regions, and generate dynamic data of the image subject based on the image subject status and image acquisition time corresponding to the image subject in the selected geographic region; Step S400: Update the geographic data of the selected geographic area based on the dynamic data of the image subject, and generate updated geographic data of the area.

[0035] In this embodiment, a preset geographic data collection standard is established to filter raw geographic images taken by tourists during their visits. Real-time geographic images that meet the standard are selected. Then, the geographic collection area, image subject, image subject status, and image collection time in the real-time geographic images are identified. Selected geographic areas are selected from these areas, and dynamic image subject data is generated based on the image subject status and collection time within each selected area. The selected geographic area's geographic data is then updated based on this dynamic data, generating updated regional geographic data. This achieves the collection and management of tourism geographic data, significantly reducing workload during peak tourist seasons. The presence of tourism geographic data collection personnel in scenic areas allows staff to focus on maintaining safety and order, reducing the cost of collecting tourism geographic data. Although mobile terminals are used during filming, the data collection does not rely on the positioning of the mobile terminals themselves. Instead, it obtains relevant information about the geographic collection area based on the analysis of real-time geographic images. This solves the signal drift and inaccurate data collection problems caused by reliance on mobile terminal positioning in existing technologies. Furthermore, it eliminates the need for drones and satellite detection, effectively reducing the cost of collecting tourism geographic data. By fully utilizing the information collection capabilities of tourists, it enables refined collection of tourism geographic data based on the tourist's travel routes, improving the accuracy of tourism geographic data collection.

[0036] In one embodiment, the original geographic imagery includes original geographic video and original geographic images; The geographic data acquisition standards include video acquisition standards and image acquisition standards. The video acquisition standards include: the captured video contains at least two geographic landmarks. In step S100, the original geographic image sent by the passenger is acquired, including: Step S111: Output collection guidance information according to the image shooting trigger command of the passenger touch, and acquire the original geographical video shot by the passenger based on the collection guidance information, wherein the collection guidance information is used to guide the passenger to shoot according to the video collection standard; Step S112: In response to acquiring the original geographic video, guide the passenger to take an image and acquire the original geographic image taken by the passenger.

[0037] In this embodiment, the original geographic imagery refers to the raw data captured by passengers, including video and image content, specifically raw geographic video and raw geographic images. By setting geographic data acquisition standards, including video acquisition standards and image acquisition standards, subsequent guidance and screening of passenger-captured video data can be based on the video acquisition standards, and screening of passenger-captured image data can be based on the image acquisition standards.

[0038] In step S111, when the passenger triggers the image capture command via touch, an image prompt interface is generated. This interface displays capture guidance information, which is an image capture instruction video. This video instructs the passenger to capture images according to video capture standards. For example, the video might instruct the passenger to start capturing from the first geographical landmark and capture the second landmark before the video ends. Alternatively, the passenger could capture the first and second geographical landmarks first, then capture the others. The video only needs to contain at least two geographical landmarks.

[0039] The geographical markers are pre-set for subsequent regional positioning. That is, different geographical markers are pre-set as labels for different regions, so that once a geographical marker is identified, the corresponding geographical region can be identified, solving the problems of signal drift and inaccurate data collection caused by using mobile terminal positioning systems in existing technologies.

[0040] For example, the geographical indications include signs, directional signs, mileage markers, store signs, etc.

[0041] In step S112, in response to acquiring the original geographic video, an image shooting interface is generated to guide the passenger in taking images. This image shooting interface is a touch-sensitive interface; otherwise, the next step cannot be performed. Furthermore, the image shooting interface is set to exist for one minute, meaning the passenger needs to take a picture within one minute; otherwise, the video needs to be re-recorded. This design aims to ensure temporal continuity between the captured video and images, facilitating subsequent analysis and updates of geographic data, and also conforms to the passenger's habit of taking videos before taking photos.

[0042] After taking a picture on the image capture interface, the passenger can obtain the original geographic image captured by the passenger through the touch screen of the image capture interface.

[0043] In one embodiment, the real-time geographic imagery includes real-time geographic video and real-time geographic images; In step S100, generating real-time geographic images based on the original geographic images includes: Step S121: Perform compliance verification on the original geographic video according to the video acquisition standard. If the compliance verification is qualified, generate real-time geographic video. Step S122: Perform compliance verification on the original geographic image according to the image acquisition standard. If the compliance verification is qualified, generate a real-time geographic image.

[0044] In this embodiment, considering the problem that during actual filming, many tourists may be discouraged from taking photos due to numerous shooting requirements, resulting in less data collection, steps S111 to S112 only guide tourists based on the video acquisition standards. If the real-time captured images were to be inspected, and failures were detected, preventing tourists from filming or sending prompts indicating filming failure, many tourists would be unwilling to film. To solve this problem, without affecting tourists' enthusiasm for filming, and to obtain more tourism geographic data, this application performs a second compliance verification after collecting the original geographic video and original geographic images, thereby filtering the tourism geographic data.

[0045] In step S121, data analysis is performed on the original geographic video to determine whether its content meets the requirements of the video capture standard, thereby conducting a compliance verification. If the video capture standard is met, the compliance verification is deemed successful; if it is not met, the compliance verification is deemed unsuccessful. Original geographic videos that fail the compliance verification are discarded.

[0046] In step S122, it is determined whether the original geographic image meets the requirements of the image acquisition standard, thereby determining whether the compliance verification is qualified. If it meets the requirements of the image acquisition standard, the compliance verification is qualified. If it does not meet the requirements of the image acquisition standard, the compliance verification is unqualified. Similarly, the original geographic image that fails the compliance verification is discarded and will not be used for subsequent geographic data analysis.

[0047] In other words, the geographic data collection standard not only guides travelers during the data collection process, but also serves as a filter for subsequent data. Considering the large number of travelers, even after removing data that does not meet compliance verification, a considerable amount of valid data can still be obtained, which is conducive to promoting the collection and updating of tourism geographic data.

[0048] The image acquisition standards include at least pixel size requirements and resolution requirements. The pixel size requirements include a minimum of a preset threshold, such as a longer side greater than or equal to 1920 pixels, or a total pixel count greater than or equal to 2 million. Resolution requirements are set by those skilled in the art to avoid blurring affecting landmark recognition and geographic data analysis.

[0049] In one embodiment, step S200: identifying the geographic acquisition area, image subject, image subject status, and image acquisition time in the real-time geographic image includes: Step S210: Compare the geographic landmarks in the real-time geographic image with the pre-stored landmark sequence list and filter out the geographic acquisition area. The landmark sequence list includes standard geographic areas and corresponding standard landmarks. The geographic acquisition area is the standard geographic area corresponding to the standard landmark that is the same as the geographic landmark. Step S220: Analyze the real-time geographic image to extract the image subject, the image subject status, and the image acquisition time.

[0050] In this embodiment, the scenic area is divided into regions, and multiple standard geographical areas are generated after the division. These standard geographical areas include two categories. The first category includes areas that can be covered by conventional cameras, including but not limited to cable car areas, entrance gate areas, parking areas, shop areas, and viewing platform areas. The second category includes geographical areas that are not conventionally covered by cameras, such as hiking trails in the mountains, the ends of outdoor boardwalks, slope bends, behind scenic rocks, bamboo forest paths, and canyon boardwalks. These areas may have high wiring and maintenance costs due to their distance and numerous locations, or blind spots caused by the limited field of view of fixed cameras, preventing them from being covered by cameras.

[0051] For the first type of standard geographic area, fewer standard markers are typically set up to facilitate cross-data collection and updates using cameras. For the second type of standard geographic area, more standard markers are set up to address the problem of inadequate monitoring and inability to update geographic data due to insufficient camera coverage.

[0052] The standard markers mentioned are mainly low-cost markers, such as waterproof stickers, acrylic signs, and road signs with barcodes. These are standalone markers. Further cost savings can be achieved by setting up markers that are integrated with the existing geographical landmarks of the scenic area, such as attaching etched digital codes to existing signs.

[0053] By first dividing the geographic area into different standard geographic regions and then setting different standard landmarks within each region, a correspondence is established between one standard geographic region and multiple standard landmarks. Based on this correspondence, during subsequent analysis of the real-time geographic imagery, the matching analysis between the geographic landmarks in the real-time geographic imagery and the standard landmarks can be used to obtain the geographic landmarks that match the standard landmarks, thereby determining the geographic acquisition area where the video was captured and achieving geographic region positioning. Compared with existing methods that rely on analyzing the positioning system of mobile terminals for positioning, this embodiment, based on the setting of low-cost standard landmarks and pre-divided standard geographic regions, can achieve more accurate positioning and completely avoid the problem of inaccurate data acquisition caused by positioning drift.

[0054] In step S210, geographic landmarks are identified in both the original geographic video and the original geographic image in the real-time geographic imagery, and the geographic acquisition area is located based on the identified geographic landmarks. However, since the image acquisition standard does not require that images taken by passengers must contain geographic landmarks, the probability of extracting geographic landmarks from the original geographic image is relatively low during actual data processing; geographic landmark identification is mainly based on the original geographic video.

[0055] Restricting images to include geographical landmarks would result in them dominating the frame, preventing travelers from capturing their desired content. This discourages photography and reduces the amount of geographical data collected, ultimately impacting data acquisition. By omitting the requirement for geographical landmarks in the image acquisition standard, travelers are free to capture whatever they want, preserving their travel experience while maximizing the acquisition of geographical data. The video acquisition standard, requiring only two geographical landmarks and allowing for extended recording times, avoids this restriction. Furthermore, the requirement to immediately capture images after video ensures temporal continuity and minimal intervals, placing both within the same timeframe. This facilitates subsequent analysis of corresponding geographical areas within the same time period, improving analytical reliability. Additionally, video recordings may suffer from unclear transitions; combining this with image data allows for clearer and more accurate geographical data analysis, enhancing the precision and reliability of tourism geographical data analysis.

[0056] In step S210, the real-time geographic imagery is analyzed, including the original geographic video and the original geographic image, to extract the image subject, the image subject status, and the image acquisition time. The image subject includes road sections, boardwalk sections, parking lots, viewing platforms, etc. The image subject status includes open status, obstacle status, and risk status. The open status includes open, partially open, and closed. The obstacle status includes fallen tree obstacles, fencing obstacles, water accumulation obstacles, and crowd congestion obstacles. The risk status includes normal, slippery, rockfall, and poor visibility.

[0057] By analyzing the real-time geographic images, the image subject, the image subject status, and the image acquisition time can be obtained, which facilitates subsequent geographic area positioning, as well as geographic data analysis and updates.

[0058] In one embodiment, step S300, selecting a selected geographic region from each of the geographic data collection regions, includes: Step S311: Extract regional risk features from each of the geographic data collection areas, and generate a regional risk feature vector based on the regional risk features; Step S312: Match the regional risk feature vector with the event feature template and generate risk event data; Step S313: Determine high-risk areas based on the risk event data, and set the high-risk areas as selected geographical regions.

[0059] In step S311, the regional risk features include, but are not limited to, crowd density features, queue length features, traffic speed features, congestion features, temporary closure features, and construction features. When generating a regional risk feature vector based on the regional risk features, each regional risk feature is quantized and encoded according to a preset feature item set. The quantization and encoding includes at least one of the following: normalizing continuous features, hierarchicalizing discrete features, binarizing, or probabilizing them, to generate a regional risk feature vector with a fixed dimension. When a feature item cannot be extracted, a default value is assigned to that feature item and / or a missing identifier parameter is generated.

[0060] The preset feature set defines the dimensions of the regional risk feature vector, including at least feature index, feature type, feature quantization encoding method, and feature value range. The regional risk feature vector is generated according to the feature order determined by the preset feature set, thus maintaining a fixed vector dimension. This allows the risk feature vector to be matched with the event feature template at the same feature scale during subsequent analysis, facilitating subsequent calculation and analysis of risk events.

[0061] Next, in order to filter out the selected geographical areas, the risk feature vector of the area is matched with the event feature template to generate risk event data; and high-risk areas are determined based on the risk event data and set as the selected geographical areas.

[0062] In one embodiment, step S312: matching the regional risk feature vector with the event feature template and generating risk event data, including: Step S3121: Extract feature values ​​corresponding to each event feature template from the regional risk feature vector, wherein each event feature template is preset; Step S3122: Determine whether the event determination condition is met based on the value of the feature item; Step S3123: If the determination condition is met, risk event data is generated, which includes the risk event type and event intensity.

[0063] In this embodiment, the event feature template is a preset template in a preset template library. Each event feature template corresponds to at least one type of risk event. Each event feature template also has a preset feature item index and event judgment conditions. The risk event type corresponds to the feature item index. When the event judgment conditions are met, the corresponding event feature template is matched.

[0064] After obtaining the regional risk feature vector, it needs to be compared with each event feature template to determine whether they match. First, feature item values ​​are extracted from the regional risk feature vector using the feature item index corresponding to the event feature template. Then, the feature item values ​​are substituted into the event determination conditions for judgment. If the event determination conditions are not met, the corresponding event feature template is determined not to match. If the event determination conditions are met, the corresponding event feature template is determined to match, and risk event data is generated accordingly.

[0065] Taking the regional risk feature vector corresponding to the geographic data collection area as an example, which includes population density features, queue length features, passage speed features, and closure probability features, the regional risk feature vector is represented as [f1, f2, f3, f4], where f1, f2, f3, and f4 represent population density features, queue length features, passage speed features, and closure probability features, respectively.

[0066] The values ​​for crowd density, queue length, passage speed, and closure probability are all between 0 and 1. The larger the value, the greater the crowd density, the longer the queue, the faster the passage speed, and the greater the probability of closure.

[0067] If the values ​​of f1, f2, f3, and f4 are 0.85, 0.7, 0.2, and 0.3 respectively, the event feature template is set as the congestion event template. The feature item indices corresponding to the congestion event template are f1, f2, and f3. The event judgment conditions corresponding to the congestion event template include conditions A, B, and C. Condition A refers to the crowd density feature being greater than or equal to 0.7, condition B refers to the queue length feature being greater than or equal to 0.6, and condition C refers to the passage speed being less than or equal to 0.3. When conditions A and B are satisfied simultaneously, or conditions A and C are satisfied simultaneously, the congestion event is established.

[0068] The feature values ​​extracted from the regional risk feature vector according to the feature index are 0.85, 0.7, and 0.2. After substituting them into the event determination conditions, it is determined that the event determination conditions are met, so the current congestion event template is matched to generate risk event data. The event intensity is calculated based on the average value of the feature values, specifically (f1+f2+(1-f3)) / 3. In this embodiment, the calculated event intensity is approximately 0.78.

[0069] If f4 is included, the event intensity is calculated as ((f1+f2+(1-f3))+f4) / 4.

[0070] In one embodiment, step S313: determining high-risk areas based on the risk event data and setting the high-risk areas as selected geographical regions includes: Step S3131: Generate a risk level coefficient based on the risk event data corresponding to the geographically collected area; Step S3132: Generate a risk assessment value based on the risk level coefficient and the corresponding event intensity; Step S3133: Determine high-risk areas based on the risk assessment values, and set the high-risk areas as selected geographical regions.

[0071] In this embodiment, the geographic data collection area may correspond to multiple risk event data. An event level relationship table is pre-set, containing different risk event types and corresponding risk level coefficients. One geographic data collection area corresponds to multiple risk event data, that is, multiple risk event types. Each risk event type is compared with the event level relationship table to obtain a corresponding risk level coefficient. The risk level coefficient is then fused with the corresponding event intensity to obtain a single event risk value. These single event risk values ​​are summed to generate the risk assessment value. The higher the risk assessment value, the higher the risk level of the corresponding geographic data collection area, and the more necessary it is to update the geographic data. Therefore, high-risk areas are determined based on the risk assessment value and set as selected geographic areas.

[0072] Because different event types have varying degrees of danger, an event level relationship table is established, with risk level coefficients set for different risk event types. For example, when the risk event types include accident warnings, construction, roadside flooding, and traffic congestion, the risk level of accident warnings and traffic congestion is higher than that of construction and roadside flooding. The risk level coefficients for accident warnings and traffic congestion are typically set to 1 and 0.9, respectively, while the risk level coefficients for construction and roadside flooding are typically set to 0.7 and 0.75, respectively. The risk level coefficients range from 0 to 1 to ensure they are within the scale of event intensity, facilitating analysis.

[0073] Each risk event type and its corresponding risk level coefficient are preset and can be adaptively set based on historical accident data, such as risk events that have occurred in various scenic areas and their corresponding hazards. The risk level coefficient is used to characterize the contribution of different risk event types to the overall risk of the region.

[0074] When calculating the risk level coefficient and the corresponding event intensity, the calculation method includes at least one of summation, taking the maximum value, or weighted summation. In this embodiment, considering that multiple risks are usually superimposed in a region, the summation method is adopted to match the actual situation after multiple risks are superimposed.

[0075] When determining a high-risk area based on the risk assessment value, it is determined whether the risk assessment value is greater than or equal to a high-risk threshold. If the value is greater than or equal to the high-risk threshold, the area is determined to be a high-risk area. If the value is less than the high-risk threshold, the area is determined not to be a high-risk area.

[0076] The high-risk threshold is preset, for example, by adaptively setting the high-risk threshold by collecting risk events that have occurred in various scenic spots in the past and their corresponding hazards.

[0077] In another embodiment, the high-risk threshold is adjustable. For example, in severe weather, the high-risk threshold should be appropriately lowered. If the risk increases due to weather, judging by the conventional threshold could easily lead to a situation where a risky area is judged as risk-free. Therefore, the threshold needs to be adjusted based on real-time conditions. Specifically, scenic area management personnel can adjust the threshold appropriately based on experience or surveying. Alternatively, the high-risk threshold can be set in other ways; this application does not impose specific limitations, as long as it can effectively filter out high-risk areas.

[0078] In one embodiment, in step S300, when generating dynamic data of the image subject based on the image subject status and image acquisition time corresponding to the image subject in the selected geographical area, the state of the selected geographical area at different times is summarized according to the image acquisition time, thereby obtaining the state of the selected geographical area at different times, which is beneficial for subsequent geographical data updates.

[0079] In one embodiment, step S400: updating the selected geographic region's geographic data based on the image subject dynamic data, and generating updated regional geographic data, includes: Step S410: Extract the latest status data of the selected geographic area from the dynamic data of the image subject; Step S420: Extract the target time window summary status of the selected geographic area from the dynamic data of the image subject; Step S430: Update the geographic data based on the latest status data and the target time window summary status, and generate updated regional geographic data.

[0080] In this embodiment, updating the geographic data of the selected geographic region includes two aspects. Firstly, the original data of the selected geographic region is updated to the latest state. Specifically, the latest image subject state is extracted from the image subject dynamic data and used as the latest state data for the selected geographic region. Secondly, a representative state of the selected geographic region, i.e., the target time window summary state, is extracted from the image subject dynamic data. Then, geographic data is updated based on the latest state data and the target time window summary state, generating updated regional geographic data.

[0081] When extracting the target time window summary state, a representative state is obtained by summarizing the image subject states within multiple preset time windows. For example, if three preset time windows are collected, the first is of moderate congestion, and the second and third are of high congestion, then the target time window summary state is of high congestion.

[0082] In another embodiment, the target time window summary state further includes a representative time period. Continuing from the previous embodiment, when the target time window summary state is at a high level of congestion, the representative time period is the time period encompassed by three preset time windows. By including a representative time period, it becomes more targeted when using geographic data for risk warnings or geographic area utilization. The representative time period serves as the time attribute of the updated regional geographic data.

[0083] In another embodiment, multiple data collections can be performed within a preset time window. For example, a 10-minute time window can be set, and status data can be collected multiple times within this 10-minute time window. The statuses are then summarized to obtain the target time window summary status. When the target time window summary status is obtained, the status that appears most frequently is set as the target time window summary status.

[0084] Of course, other methods can be used to set the target time window summary status. The above are just examples and are not limited, as long as the target time window summary status can be obtained.

[0085] Therefore, in this embodiment, by directly using the latest acquisition time status of the dynamic data of the main image subject as the update basis, the regional geographic data is updated to the current latest status, enabling the regional geographic data to respond more quickly to sudden changes. This solves the problem of slow geographic data updates by scenic area staff in the prior art and also saves manpower in the scenic area. Furthermore, by collecting multiple statuses within a preset time window and summarizing them into a representative status, the error problem caused by updating data only once in the prior art is avoided, improving stability and robustness.

[0086] It should be noted that for image data collected from passengers, data involving passenger privacy is protected through blurring techniques, including but not limited to facial blurring and data anonymization. Furthermore, passengers can only access the image capture interface and proceed with image capture after agreeing to the data privacy agreement. This data privacy agreement is pre-set, primarily stating that passengers agree to the use of captured images for geographic data updates. This arrangement ensures that all data processing is conducted in a manner that does not infringe upon passenger privacy and guarantees compliance with laws and regulations.

[0087] In addition, to encourage passengers to take photos and make it easier for staff to update geographic data, a reward system for taking photos and making passengers aware of it before taking photos and making them more likely to take photos and make ...

[0088] In one embodiment, the image acquisition interface for tourists relies on the acquisition software provided by the scenic area. The acquisition software provided by the scenic area meets the requirements of security, reliability, and confidentiality, thereby ensuring security during the image acquisition and geographic data update process.

[0089] In one embodiment, such as Figure 2 As shown, a tourism geographic data collection and management system is also provided, the system comprising: The geographic image acquisition module is used to acquire raw geographic images sent by passengers and generate real-time geographic images based on the raw geographic images, wherein the real-time geographic images conform to preset geographic data acquisition standards. The geographic data recognition module is used to identify the geographic acquisition area, image subject, image subject status, and image acquisition time in the real-time geographic image. The geographic region analysis module is used to filter out selected geographic regions from the various geographic acquisition regions, and generate dynamic data of the image subject based on the image subject status and image acquisition time corresponding to the image subject in the selected geographic region. The geographic region update module is used to update the geographic data of the selected geographic region based on the dynamic data of the image subject, and generate updated geographic data of the region.

[0090] In one embodiment, the original geographic imagery includes original geographic video and original geographic images; the geographic data acquisition standard includes video acquisition standard and image acquisition standard, wherein the video acquisition standard includes: the captured video contains at least two geographic landmarks; the geographic image acquisition module is further configured to: output acquisition guidance information according to the image capture trigger command touched by the passenger, and acquire the original geographic video captured by the passenger based on the acquisition guidance information, wherein the acquisition guidance information is used to guide the passenger to capture images according to the video acquisition standard; in response to acquiring the original geographic video, guide the passenger to capture images and acquire the original geographic images captured by the passenger.

[0091] In one embodiment, the real-time geographic imagery includes real-time geographic video and real-time geographic images; the geographic imagery acquisition module is further configured to: perform compliance verification on the original geographic video according to the video acquisition standard, and if the compliance verification is qualified, generate real-time geographic video; perform compliance verification on the original geographic image according to the image acquisition standard, and if the compliance verification is qualified, generate real-time geographic images.

[0092] In one embodiment, the geographic data identification module is further configured to: compare the geographic landmarks in the real-time geographic image with a pre-stored landmark sequence list and filter out the geographic acquisition area, wherein the landmark sequence list includes standard geographic areas and corresponding standard landmarks, and the geographic acquisition area is a standard geographic area corresponding to a standard landmark that is the same as the geographic landmark; analyze the real-time geographic image and extract the image subject, the image subject status, and the image acquisition time.

[0093] In one embodiment, the geographic region analysis module is further configured to: extract regional risk features from each of the geographic collection areas, and generate a regional risk feature vector based on the regional risk features; match the regional risk feature vector with an event feature template to generate risk event data; determine high-risk areas based on the risk event data, and set the high-risk areas as selected geographic regions.

[0094] In one embodiment, the geographic region analysis module is further configured to: extract feature values ​​corresponding to each event feature template from the regional risk feature vector, wherein each event feature template is preset; determine whether the event determination conditions are met based on the feature values; if the determination conditions are met, generate risk event data, wherein the risk event data includes risk event type and event intensity.

[0095] In one embodiment, the geographic region analysis module is further configured to: generate a risk level coefficient based on the risk event data corresponding to the geographic collection area; generate a risk assessment value based on the risk level coefficient and the corresponding event intensity; determine a high-risk area based on the risk assessment value, and set the high-risk area as the selected geographic region.

[0096] In one embodiment, the geographic region update module is further configured to: extract the latest status data of the selected geographic region from the image subject dynamic data; extract the target time window summary status of the selected geographic region from the image subject dynamic data; update the geographic data according to the latest status data and the target time window summary status, and generate updated regional geographic data.

[0097] It should be noted that the information interaction and execution process between the above modules are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, which will not be repeated here.

[0098] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0099] This application also provides a network device, which includes: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, wherein the processor executes the computer program to implement the steps in any of the above method embodiments.

[0100] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps described in the various method embodiments above.

[0101] This application provides a computer program product that, when run on a mobile terminal, enables the mobile terminal to implement the steps described in the above-described method embodiments.

[0102] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above-described embodiments of this application can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying computer program code to a photographic device / terminal device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electrical carrier signals or telecommunication signals.

[0103] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0104] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0105] In the embodiments provided in this application, it should be understood that the disclosed apparatus / network devices and methods can be implemented in other ways. For example, the apparatus / network device embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0106] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0107] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

[0108] One embodiment of this application also provides a computer device, which includes: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, wherein the processor executes the computer program to implement the steps in any of the above-described methods.

[0109] The computer device may include, but is not limited to, a processor and memory. Those skilled in the art will understand that the above description is an example of a computer device and does not constitute a limitation on the computer device. It may include more or fewer components than described above, or a combination of certain components, or different components, such as input / output devices, network access devices, etc.

[0110] The processor referred to can be a Central Processing Unit (CPU), but it can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0111] In some embodiments, the memory may be an internal storage unit of the computer device, such as a hard drive or RAM. In other embodiments, the memory may be an external storage device of the computer device, such as a plug-in hard drive, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card. Furthermore, the memory may include both internal and external storage units of the computer device. The memory is used to store the operating system, applications, bootloader, data, and other programs, such as the program code of the computer program. The memory can also be used to temporarily store data that has been output or will be output.

[0112] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0113] The embodiments described above are merely examples of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for collecting and managing tourism geographic data, characterized in that, The method includes: The system acquires raw geographic images sent by passengers and generates real-time geographic images based on the raw geographic images, wherein the real-time geographic images conform to preset geographic data collection standards. Identify the geographic acquisition area, image subject, image subject status, and image acquisition time in the real-time geographic imagery; Selected geographic regions are selected from each of the geographic acquisition regions, and dynamic data of the image subjects are generated based on the image subject status and image acquisition time corresponding to the image subjects in the selected geographic regions. The selected geographic area is updated based on the dynamic data of the main image subject, and the updated regional geographic data is generated.

2. The tourism geographic data collection and management method according to claim 1, characterized in that, The original geographic imagery includes original geographic video and original geographic images; The geographic data acquisition standards include video acquisition standards and image acquisition standards. The video acquisition standards include: the captured video contains at least two geographic landmarks. Obtain the raw geographic imagery sent by the passenger, including: Based on the image capture trigger command triggered by the passenger's touch screen, the system outputs collection guidance information and acquires the original geographical video captured by the passenger based on the collection guidance information. The collection guidance information is used to guide the passenger to capture video according to the video capture standards. In response to acquiring raw geographic video, guide travelers to take images and acquire the raw geographic images taken by the travelers.

3. The tourism geographic data collection and management method according to claim 2, characterized in that, The real-time geographic imagery includes real-time geographic video and real-time geographic images. Generating real-time geographic images based on the original geographic images includes: The original geographic video is subjected to compliance verification according to the video acquisition standard. If the compliance verification is qualified, a real-time geographic video is generated. The original geographic image is verified for compliance according to the image acquisition standard. If the compliance verification is successful, a real-time geographic image is generated.

4. The tourism geographic data collection and management method according to claim 1, characterized in that, Identifying the geographic acquisition area, image subject, image subject status, and image acquisition time in the real-time geographic imagery includes: The geographic landmarks in the real-time geographic image are compared with a pre-stored landmark sequence list, and geographic collection areas are selected. The landmark sequence list includes standard geographic areas and corresponding standard landmarks. The geographic collection area is the standard geographic area corresponding to the standard landmark that is the same as the geographic landmark. The real-time geographic imagery is analyzed to extract the image subject, the image subject status, and the image acquisition time.

5. The tourism geographic data collection and management method according to claim 1, characterized in that, Selected geographic regions are filtered from the aforementioned geographic data collection regions, including: Regional risk features are extracted from each of the aforementioned geographic data collection areas, and regional risk feature vectors are generated based on the regional risk features. The risk event data is generated by matching the regional risk feature vector with the event feature template. High-risk areas are identified based on the risk event data, and these high-risk areas are set as selected geographical regions.

6. The tourism geographic data collection and management method according to claim 5, characterized in that, The risk event data is generated by matching the regional risk feature vector with the event feature template, including: Feature values ​​corresponding to each event feature template are extracted from the regional risk feature vector, wherein each event feature template is preset. Determine whether the event determination condition is met based on the value of the feature item; If the determination criteria are met, risk event data is generated, which includes the risk event type and event intensity.

7. The tourism geographic data collection and management method according to claim 5, characterized in that, High-risk areas are identified based on the risk event data, and these high-risk areas are set as selected geographical regions, including: A risk level coefficient is generated based on the risk event data corresponding to the geographically collected area. A risk assessment value is generated based on the risk level coefficient and the corresponding event intensity. High-risk areas are identified based on the risk assessment values, and these high-risk areas are designated as selected geographical regions.

8. A tourism geographic data collection and management system, characterized in that, The system includes: The geographic image acquisition module is used to acquire raw geographic images sent by passengers and generate real-time geographic images based on the raw geographic images, wherein the real-time geographic images conform to preset geographic data acquisition standards. The geographic data recognition module is used to identify the geographic acquisition area, image subject, image subject status, and image acquisition time in the real-time geographic image. The geographic region analysis module is used to filter out selected geographic regions from the various geographic acquisition regions, and generate dynamic data of the image subject based on the image subject status and image acquisition time corresponding to the image subject in the selected geographic region. The geographic region update module is used to update the geographic data of the selected geographic region based on the dynamic data of the image subject, and generate updated geographic data of the region.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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