Audio-based tourist attraction service guiding method

Abstract

The invention relates to the technical field of artificial intelligence, and discloses a scenic spot service guiding method based on audio. The method comprises the following steps: determining an associated path point of a scenic spot; determining a personnel flow trend of the path points according to the acquired path point audio information of the associated path points; displaying personnel flow trend information according to the personnel flow trend; wherein the personnel flow trend is obtained according to the loudness change trend of sounds in different frequency bands in the path point audio information. According to the technical scheme, the problem of low personnel flow management efficiency in hot tourist attractions is solved, the personnel flow trend of the associated path points can be determined in real time, the personnel flow strategy is adjusted in time, congestion is effectively prevented, and tourist safety is enhanced.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence technology, and in particular to an audio-based tourist attraction service guidance method. Background Art

[0002] In the existing tourist attraction management system, the monitoring and management of personnel flow usually relies on traditional technologies such as visual or static sensors. Although these technologies have solved the congestion management problem in densely populated areas to a certain extent, they have many shortcomings in dynamic and complex environments. Video surveillance system is a common technical means at present. By setting up cameras inside the scenic area or on key sections, the dynamic information of tourists can be obtained in real time. However, video surveillance not only has limited coverage and is difficult to monitor all areas, but also the accuracy of video analysis is greatly reduced when the crowd is dense or the scale of the scenic area is large. At the same time, the installation and maintenance costs of video surveillance equipment are high, and privacy issues often cause public concerns, which limits the application of this technology in some scenic spots. For infrared sensors, although they can detect whether there are people in a specific area, they cannot identify the specific number and flow direction of people, so it is difficult to provide more accurate information on personnel flow.

[0003] In addition, in recent years, there are also personnel flow management solutions based on GPS or mobile applications. By tracking the geographic location of tourists, scenic spots can roughly understand the distribution and movement trajectory of tourists. However, this type of technology relies on the active participation of tourists, and the accuracy is not high in indoor environments or areas with poor signals, making it difficult to meet real-time and accurate requirements. Especially when there are multiple roads, branch points or complex paths inside the scenic area, the existing technology often cannot accurately reflect the actual flow trend of tourists, which in turn affects the management and regulation of the flow of people in the scenic area. With the rapid development of the tourism industry, scenic spots have an increasingly urgent need for real-time, accurate and efficient monitoring of personnel flow, and traditional technical means have been unable to meet these complex management needs. Therefore, the existing personnel flow monitoring technology has many shortcomings in terms of accuracy, real-time performance, implementation cost and privacy protection. Especially in tourist attractions where the dynamic changes of crowd behavior are significant, the existing technology cannot quickly respond and accurately predict the changing trend of the flow of people, making it difficult for scenic area management to take effective measures in time to avoid congestion or emergencies. Summary of the invention

[0004] At least one aspect or advantage of the invention will be set forth in part in the following description, or may be obvious from the description, or may be learned by practice of the disclosed subject matter.

[0005] The technical solution of the present invention solves the problem of low efficiency in personnel flow management in popular tourist attractions. The present invention can determine the personnel flow trend of associated path points in real time and adjust the personnel flow strategy in time to effectively prevent congestion and enhance tourist safety.

[0006] According to a first aspect of the present invention, a tourist attraction service guidance method based on audio includes:

[0007] Determine the associated waypoints of tourist attractions;

[0008] Determine the personnel flow trend of the waypoints according to the audio information collected at the waypoints associated with the waypoints;

[0009] Display personnel flow trend information based on personnel flow trend;

[0010] Among them, the personnel flow trend is obtained based on the loudness change trend of sounds in different frequency bands in the audio information of the path points.

[0011] According to one embodiment of the present invention, the associated path point is a branch point of a road with branches, or an intersection of roads;

[0012] The audio information is obtained through a microphone arranged at an associated path point.

[0013] According to an embodiment of the present invention, at least two pickups are provided corresponding to each path point and are provided along the connection direction between the path points.

[0014] According to an embodiment of the present invention, several frequency intervals in the 1400 Hz frequency band are determined as specific frequency intervals according to the loudness changes corresponding to 85-300 Hz in the first time window in the collected audio information; wherein the first loudness changes of adjacent specific frequency intervals in the first time window are similar to each other and are greater than a first threshold.

[0015] According to an embodiment of the present invention, the first loudness change of the frequency interval in the first time window is obtained as follows:

[0016] Determine a sequence of loudness values ​​within a first time window of a frequency interval with a first step length;

[0017] Performing a zeroing operation on the loudness values ​​in the loudness value sequence that are lower than the average loudness value of all frequency intervals in the first time window;

[0018] The loudness value sequence is normalized by using the maximum loudness value in the first time window to obtain a first loudness change of the frequency interval in the first time window.

[0019] According to one embodiment of the present invention, the process of determining the personnel flow trend further includes:

[0020] Obtaining a mean loudness value within a first time window based on a plurality of selected specific frequency intervals;

[0021] A reference frequency interval is selected from a plurality of specific frequency intervals, wherein, within a first time window, an objective function corresponding to the reference frequency interval is higher than an objective function corresponding to other specific frequency intervals; and the objective function is the sum of cosine approximations of a second loudness change of the frequency interval within the first time window and a second loudness change of other specific frequency intervals within the first time window.

[0022] According to an embodiment of the present invention, a directed graph is determined according to the loudness change value and the coordinates of the associated path points within the reference frequency interval, the nodes of the directed graph are the associated path points, the weights of the directed graph are the loudness change values, and when the loudness change value is negative, the directed graph includes an edge from the current node to the adjacent node, and when the loudness change value is positive, the directed graph includes an edge from the adjacent node to the current node;

[0023] Remove intermediate nodes whose absolute value of the sum of weight values ​​of the relations is greater than a first threshold from the directed graph;

[0024] Output personnel flow trends based on the updated directed graph;

[0025] The intermediate node simultaneously serves as the starting point of at least one edge and the end point of at least one edge in the directed graph.

[0026] According to an embodiment of the present invention, the personnel flow trend information includes path point information with positive loudness change.

[0027] According to a second aspect of the present invention, a computer device includes a memory and a processor, wherein the memory stores a computer program, and the processor implements an audio-based tourist attraction service guidance method when executing the computer program.

[0028] According to a third aspect of the present invention, a computer-readable storage medium stores a computer program, which, when executed by a processor, implements an audio-based tourist attraction service guidance method.

[0029] Compared with the prior art, the technical solution of the present invention has the following beneficial effects:

[0030] By analyzing audio data, the present invention can grasp the flow trend of tourists in a scenic area in real time, ensuring a quick understanding of crowd density and trends.

[0031] The technical solution of the present invention can accurately monitor the flow of tourists, making it easier for management personnel to adjust scenic area routes, reduce congestion, and improve operational efficiency.

[0032] The present invention uses audio monitoring instead of cameras, which has lower costs and does not involve privacy issues, thereby enhancing tourists' sense of trust. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 A flow chart of an audio-based tourist attraction service guidance method provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0034] The present disclosure will now be discussed with reference to several exemplary embodiments. It should be understood that these embodiments are discussed only to enable those skilled in the art to better understand and thus implement the present disclosure, rather than implying any limitation on the scope of the present disclosure.

[0035] As used herein, the term "including" and its variants are to be interpreted as open-ended terms meaning "including but not limited to". The term "based on" is to be interpreted as "based at least in part on". The terms "one embodiment" and "an embodiment" are to be interpreted as "at least one embodiment". The term "another embodiment" is to be interpreted as "at least one other embodiment". The orientation or position relationship indicated by the terms "upper", "lower", "left", "right", "front", "back", "top", "bottom", "inner", "outer", "vertical", "horizontal", "lateral", "longitudinal" and the like is based on the orientation or position relationship shown in the accompanying drawings. These terms are mainly for better describing the present application and its embodiments, and are not used to limit the indicated devices, elements or components to have a specific orientation, or to be constructed and operated in a specific orientation. In addition, in addition to being used to indicate an orientation or position relationship, some of the above terms may also be used to indicate other meanings, such as the term "upper" may also be used to indicate a certain dependency or connection relationship in some cases. For those of ordinary skill in the art, the specific meanings of these terms in this application can be understood according to the specific circumstances. In addition, the terms "install", "set", "provided with", "connected" and "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral structure; it can be a mechanical connection, or an electrical connection; it can be directly connected, or indirectly connected through an intermediate medium, or it can be an internal connection between two devices, elements or components. For those of ordinary skill in the art, the specific meanings of the above terms in this application can be understood according to the specific circumstances. In addition, the terms "first", "second", etc. are mainly used to distinguish different devices, elements or components (the specific types and structures may be the same or different), and are not used to indicate or imply the relative importance and quantity of the indicated devices, elements or components. Unless otherwise specified, "plurality" means two or more.

[0036] The existing management of personnel flow in scenic spots mainly relies on technologies such as video surveillance, infrared sensors and GPS tracking. Although video surveillance can obtain real-time crowd dynamics, it has limited coverage, serious privacy issues, and is difficult to use in low-light environments. Infrared sensors can only detect whether there are people, but cannot provide specific flow trends. The GPS system requires active user participation and has poor accuracy in places with weak signals.

[0037] When dealing with dynamic and complex environments, these technologies often find it difficult to provide real-time and accurate personnel flow data, resulting in low management efficiency and inability to respond to crowd congestion or emergencies in a timely manner.

[0038] According to one embodiment of the present invention, referring to Figure 1 As shown, the present invention provides a tourist attraction service guidance method based on audio, comprising:

[0039] Determine the associated path points of the tourist attractions; wherein the associated path points are branch points of a road with branches, or intersections of roads.

[0040] Specifically, associated path points are set at forks, branch points or intersections in the scenic area. These locations are key areas for tourists to choose routes or flow directions. By selecting these points as audio collection locations, real-time data on tourist flow can be obtained more accurately. Through the flow trends of these locations, the flow of the entire crowd can be effectively grasped, unnecessary areas can be monitored, resources can be saved, and key nodes can be effectively covered to ensure the accuracy of scenic area flow management.

[0041] The personnel flow trend of the path point is determined according to the audio information collected at the path point associated with the path point; wherein the personnel flow trend is obtained according to the loudness change trend of the sound in different frequency bands in the audio information of the path point; the audio information is obtained by the microphone set at the associated path point. In this embodiment, at least two microphones are set corresponding to each path point, and are set along the connection direction between the path points.

[0042] Specifically, microphones are installed at associated path points to collect audio information when tourists pass by. The system analyzes different frequency bands in the audio and infers the density of people and flow direction on the current path through changes in loudness. The present application monitors the flow of people at tourist attractions through sound, because sound is a natural signal source, especially in open places, where tourists' footsteps, voices, etc. can reflect the number and movement of people. Loudness changes are different from visual monitoring, and it can work normally in environments without light or limited vision. By analyzing the changes in loudness in different frequency bands, it is possible to accurately distinguish trends in the flow of people without relying on complex image processing or GPS signals.

[0043] Specifically, in the present embodiment, the number of microphones is at least two, and they are arranged in the direction along the path point, so that sound information can be collected from multiple directions to form complete audio field data. This can effectively reduce the blind spots or errors that may be generated by a single microphone when capturing sound, especially in complex terrain or crowded scenes. In addition, multiple microphones can calculate the source position of the sound by comparing the received audio signals. The present invention adopts a triangulation method to locate the position and moving direction of an object through sound differences. When multiple microphones are arranged at the path point, some irrelevant or interfering sound information (such as wind sound, vehicle sound, etc.) can be filtered out through cross-verification of signals collected at multiple points, thereby improving the system's recognition accuracy of crowd sounds.

[0044] Display personnel flow trend information according to personnel flow trend. Based on the parsed audio data, the system generates visual personnel flow trend information in real time and displays it on the personnel flow management platform to help scenic area managers intuitively understand the flow of tourists. This can guide the flow of tourists in a targeted manner and avoid congestion.

[0045] According to an embodiment of the present invention, several frequency intervals in the 1400 Hz frequency band are determined as specific frequency intervals according to the loudness changes corresponding to 85-300 Hz in the first time window in the collected audio information; wherein the first loudness changes of adjacent specific frequency intervals in the first time window are similar to each other and are greater than a first threshold.

[0046] Specifically, the system first collects audio information at the path point and extracts loudness change data in the 85-300Hz frequency band. This frequency band mainly contains low-frequency sounds, such as footsteps of people and some environmental noise. The system monitors the loudness changes of these low-frequency bands within a set time window. By analyzing these changes, the system can identify the flow of people near the current path point.

[0047] Next, the system further analyzes the audio signals in the 1400Hz band based on the loudness changes in these 85-300Hz bands. The sounds in the 1400Hz band usually include information such as conversations and noises of the crowd, which can provide more clues about crowd density and activities. The system divides the 1400Hz band into several specific frequency intervals (specific frequency intervals) and calculates the loudness changes in these frequency intervals. If the approximation of the loudness changes of adjacent specific frequency intervals within the time window is greater than the set first threshold, it is considered that the change trends of these intervals are similar, reflecting that the current changes in personnel flow in the area are consistent.

[0048] In this application, the basic activities of the crowd are analyzed through the low frequency band of 85-300Hz. This is because the 85-300Hz frequency band contains a lot of low-frequency sound information related to crowd activities, such as footsteps, sounds of mobile devices, etc. By analyzing the loudness changes in this frequency band, the system can identify basic signs of human activities.

[0049] The detection accuracy is improved by using the 1400Hz high frequency band, which contains more detailed sounds, such as conversations and noise. The appearance of these sounds is usually related to high-density crowd activities, so it is particularly important when detecting subtle changes in the flow of people. Taking the loudness changes in the 85-300Hz frequency band as a basis, further analysis of the 1400Hz frequency band can improve the accuracy of detection. By combining multiple frequency bands, it can more accurately reflect the changes in different types of sound sources (such as footsteps and conversations), and improve the sensitivity and accuracy of the system in detecting crowd activities.

[0050] The sound is filtered by using specific frequency intervals and the approximation of loudness changes. This is because not all sound changes in frequency intervals are related to the flow of people. Therefore, the system filters out irrelevant frequency intervals by calculating the approximation of loudness changes in adjacent frequency intervals. Setting a threshold to ensure that only those frequency intervals with similar change trends within the time window are retained can improve the reliability of the data. By setting a threshold to filter irrelevant frequencies, the system can reduce noise interference, ensure more accurate detection results, and avoid mistaking irrelevant sound changes for personnel flow trends.

[0051] According to an embodiment of the present invention, the first loudness change of the frequency interval in the first time window is obtained as follows:

[0052] Determine a sequence of loudness values ​​within a first time window of a frequency interval with a first step length;

[0053] Performing a zeroing operation on the loudness values ​​in the loudness value sequence that are lower than the average loudness value of all frequency intervals in the first time window;

[0054] The loudness value sequence is normalized by using the maximum loudness value in the first time window to obtain a first loudness change of the frequency interval in the first time window.

[0055] Specifically, the system divides the first time window with the set first step length, and divides the audio data in the time window into multiple time segments. Each segment corresponds to a loudness value at a moment, and the loudness values ​​of all segments constitute a loudness value sequence of the frequency interval. This sequence reflects the loudness change of the frequency interval in the time window. The system filters the loudness value sequence and sets the loudness value in the sequence that is lower than the average loudness value of all frequency intervals in the time window to zero. In other words, all sounds below the overall average value are considered to be background noise or irrelevant sounds, and are therefore ignored, ensuring that only relatively large and important sound signals are retained. Next, the system uses the maximum loudness value in the time window to normalize the loudness value sequence. The purpose of normalization is to standardize the range of loudness changes so that the loudness changes in different time windows and different frequency intervals can be compared. The normalized loudness change sequence is used for further analysis and calculation.

[0056] In this application, the time window is divided by setting a step size to obtain a refined loudness value sequence. This is because setting a step size to subdivide the time window can capture more subtle sound changes and avoid missing important sound dynamics. At the same time, this method ensures that the system can analyze personnel flow trends in a short period of time, not just long-term trends. By obtaining the loudness sequence of time segments, the audio information can be analyzed more carefully to ensure that even small changes in personnel flow can be detected.

[0057] By setting the loudness below the average value to zero, background noise is removed. This is because background noise exists in any environment, and this noise is usually stable and has nothing to do with the flow of people. By setting the loudness value below the overall mean to zero, these noises can be effectively filtered out, allowing the system to focus on detecting loudness changes related to crowd activities. This processing method reduces the interference of irrelevant information on the system, improves the recognition accuracy of valid audio signals, and improves the accuracy of detecting crowd flow trends.

[0058] Through normalization, the loudness changes are standardized. This is because the maximum loudness of the sound may be different in different time windows, and directly comparing the loudness changes in different time windows is prone to misjudgment. Through normalization, the loudness sequence is standardized to ensure that the loudness changes in different windows are comparable, allowing the system to more accurately analyze the change trends in each time period. The normalized loudness changes allow the system to accurately detect the relative change trends in different time windows, thereby increasing sensitivity to dynamic changes in crowd flow.

[0059] According to one embodiment of the present invention, the process of determining the personnel flow trend further includes:

[0060] Obtaining a mean loudness value within a first time window based on a plurality of selected specific frequency intervals;

[0061] A reference frequency interval is selected from a plurality of specific frequency intervals, wherein, within a first time window, an objective function corresponding to the reference frequency interval is higher than an objective function corresponding to other specific frequency intervals; and the objective function is the sum of cosine approximations of a second loudness change of the frequency interval within the first time window and a second loudness change of other specific frequency intervals within the first time window.

[0062] Specifically, the system first calculates the mean loudness value of each specific frequency interval in the first time window based on the analyzed specific frequency intervals. These frequency intervals are extracted based on the relevant personnel flow information in the audio. The purpose of this step is to determine the overall sound changes of each frequency interval in the time window to provide basic data for subsequent analysis.

[0063] From the calculated specific frequency intervals, the system selects a "reference frequency interval" according to a specific objective function. This reference frequency interval refers to the frequency interval with the most significant loudness change trend and the highest correlation with other intervals in the first time window. The objective function is determined by calculating the sum of the cosine approximations of the loudness changes of this frequency interval and other specific frequency intervals in the time window. Cosine approximation is used to quantify the similarity of loudness changes between different frequency intervals. The higher the score, the more similar their change trends are.

[0064] Once the reference frequency interval is determined, the system will analyze the current trend of people flow based on it. Because the reference frequency interval reflects the most representative characteristics of crowd activity in the entire time window, its loudness changes directly indicate the intensity and direction of crowd flow.

[0065] In this application, the mean loudness value is obtained by obtaining a specific frequency interval. This is because the loudness changes in different frequency intervals reflect different types of sound activities. For example, low frequencies may represent footsteps, and high frequencies may represent conversations. By obtaining the mean loudness values ​​of these frequency intervals, the system can better understand the overall sound characteristics of personnel flow. This method ensures that the system can extract useful information from multiple sound sources and provide a basis for the subsequent selection of key frequency intervals.

[0066] Among all the specific frequency intervals, the reference frequency interval is the interval that reflects the most significant crowd activity. By using cosine approximation, the system can identify which frequency interval is most consistent with the changes of other intervals in the first time window, ensuring that the analyzed frequency interval is related to the actual crowd flow. This method effectively filters out those frequency intervals that may be interfered by noise, ensuring that the selected reference frequency interval is highly representative. This can more accurately reflect the current trend of personnel flow.

[0067] Analyze frequency interval changes through cosine approximation. Cosine approximation can quantify whether the change trends of two frequency intervals are consistent. By calculating the similarity of loudness changes between different frequency intervals, the system can ensure that the selected reference frequency interval reflects the overall trend that is consistent with the change trends of other frequency intervals. Cosine approximation enables the system to more effectively evaluate the correlation between different frequency intervals, ensuring a more accurate analysis of personnel flow trends and avoiding misjudgments.

[0068] According to an embodiment of the present invention, a directed graph is determined according to the loudness change value and the coordinates of the associated path points within the reference frequency interval, the nodes of the directed graph are the associated path points, the weights of the directed graph are the loudness change values, and when the loudness change value is negative, the directed graph includes an edge from the current node to the adjacent node, and when the loudness change value is positive, the directed graph includes an edge from the adjacent node to the current node;

[0069] Remove intermediate nodes whose absolute value of the sum of weight values ​​of the relations is greater than a first threshold from the directed graph;

[0070] Output personnel flow trends based on the updated directed graph;

[0071] The intermediate node simultaneously serves as the starting point of at least one edge and the end point of at least one edge in the directed graph.

[0072] The personnel flow trend information includes the path point information with positive loudness change.

[0073] Specifically, the system first constructs a directed graph based on the loudness change value within the reference frequency range and the coordinates of the associated path points. In this directed graph:

[0074] Each node represents an associated path point, which are key locations in the scenic area, such as intersections and branch points.

[0075] If the loudness change value of the base frequency interval is negative, it means that the crowd is leaving the current waypoint, and the system will create an edge from the current node to the adjacent node in the directed graph.

[0076] If the loudness change value is positive, indicating that a crowd is entering the current waypoint, the system creates an edge from the adjacent node to the current node in the directed graph.

[0077] The weight of the edge is determined by the loudness change value. The greater the loudness change, the more obvious the change in personnel flow at the path point.

[0078] In a directed graph, if the absolute value of the sum of the weight values ​​of all related edges of a certain intermediate node (as the starting point of at least one edge and the end point of at least one edge) exceeds the set first threshold, it indicates that the node is too extreme and may cause deviation or error in the analysis results. Therefore, the system will remove these intermediate nodes from the directed graph.

[0079] After the directed graph is cleaned, the system outputs the personnel flow trend based on the updated directed graph, especially the path point information with positive loudness changes. These path points represent areas where tourists are increasing or gathering. The system can display these path points to managers to help understand the personnel flow situation in real time.

[0080] In this application, the flow relationship between path points is represented by a directed graph, which is a very intuitive way to show the flow relationship between path points. The change in loudness reflects the flow of the crowd. Combined with the coordinates of the path points, an intuitive directed graph can be constructed to clearly show the flow direction and intensity of the crowd from one path point to another. The directed graph can help scenic area managers quickly understand the flow trend of tourists, accurately grasp the direction and concentration of the crowd, and facilitate measures to guide the flow of people or control congestion.

[0081] The positive or negative sign of the loudness change value determines the direction of crowd flow. The positive or negative sign of the loudness change represents the entry and exit of the crowd between the path points. Using the sign of the loudness change value, the system can accurately determine whether a person is entering or leaving a path point, and then represent this flow relationship through the edges of the directed graph. Based on the positive or negative sign of the loudness change value, the system can more intuitively display the direction of crowd flow, making it easier to grasp the dynamic changes of the flow of people between different path points.

[0082] Moreover, if the sum of the weight values ​​of the intermediate nodes is too large, it may indicate that the node is abnormal, such as noise interference, equipment failure, etc. This will have a negative impact on the judgment of the flow trend. The present application removes these abnormal intermediate nodes to improve the accuracy of data analysis, avoid erroneous flow trend predictions, and make the personnel flow trend output by the system more accurate and reliable.

[0083] Path points with positive loudness changes indicate where people are gathering, which is very important information for managers, especially when they need to manage congestion and optimize the visitor experience. By outputting this information, the system can help managers quickly identify key areas. By outputting path points where people gather, managers can respond to possible congestion in advance, guide tourists in time, and avoid excessive concentration of people in the scenic area.

[0084] According to one embodiment of the present invention, a computer device includes a memory and a processor, wherein the memory stores a computer program, and the processor implements an audio-based tourist attraction service guidance method when executing the computer program.

[0085] According to one embodiment of the present invention, a computer-readable storage medium stores a computer program, which implements an audio-based tourist attraction service guidance method when executed by a processor.

[0086] The beneficial effects of the present invention are:

[0087] The technical solution of the present invention can realize real-time monitoring of the flow trend of people by analyzing the audio information at the path points. Compared with the traditional static monitoring method, the audio-based monitoring system can more flexibly capture the changing trend of the crowd, ensuring that the management personnel can understand the density and flow direction of tourists in different areas of the scenic spot in a short time.

[0088] By accurately judging the direction and flow of people, the present invention enables scenic area managers to make reasonable arrangements based on real-time data, such as adjusting open areas and guiding tourists to avoid congested paths, ensuring tourists' safety and improving the overall experience of the scenic area. This automated flow control capability greatly reduces the workload of manual management and improves the operational efficiency of the scenic area.

[0089] The present invention replaces traditional camera monitoring with audio analysis, reducing the cost of hardware installation and maintenance. At the same time, audio monitoring will not directly capture or record personal privacy information. Compared with video monitoring, it has a better privacy protection effect and can effectively avoid tourists' concerns about privacy infringement.

[0090] The technical solution of the present invention relies on audio data rather than visual information, and is suitable for areas with poor lighting conditions or where cameras cannot be installed, such as forests, indoor scenic spots, or crowded places. In addition, audio sensors can cover a large range of scenic spots without densely deploying points on each path, which has good scalability.

[0091] The technical solution of the present invention can accurately predict and control the flow of people in real time, so that tourists can avoid entering overcrowded areas and reduce waiting time. At the same time, it can also ensure the safety of tourists in the scenic area. Especially in emergency situations, the system can respond quickly and guide tourists to evacuate in time, thereby improving the emergency handling capabilities of the scenic area.

[0092] Those of ordinary skill in the art will appreciate that the modules and algorithm steps 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 performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0093] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices and equipment can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0094] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0095] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the embodiments of the present invention.

[0096] In addition, each functional module in the embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0097] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the energy-saving signal sending / receiving method of each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a ROM, a RAM, a magnetic disk, or an optical disk.

[0098] The above description is only a preferred embodiment of the present application and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the present application is not limited to the technical solution formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the inventive concept. For example, the above features are replaced with (but not limited to) technical features with similar functions disclosed in the present application.

[0099] It should be understood that the size of the sequence number of each step in the content of the invention and the embodiments of the present invention does not absolutely mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention. For the purpose of example and description, the foregoing description of the implementation of the present disclosure has been given. The foregoing description is not exhaustive and is not intended to limit the present disclosure to the exact form disclosed. Various deformations and modifications may exist according to the above teachings, or various deformations and modifications may be obtained from the practice of the present disclosure. These embodiments are selected and described to illustrate the principles of the present disclosure and its practical application, so that those skilled in the art can use the present disclosure in various embodiments and various modifications suitable for the specific purpose conceived.

Claims

1. A tourist attraction service guidance method based on audio, characterized in that: include: Determine the associated waypoints of tourist attractions; Determine the personnel flow trend of the waypoints according to the audio information collected at the waypoints associated with the waypoints; Display personnel flow trend information based on personnel flow trend; Among them, the personnel flow trend is obtained based on the loudness change trend of sounds in different frequency bands in the audio information of the path points.

2. The audio-based tourist attraction service guidance method according to claim 1, characterized in that: The associated path point is a branch point of a road with branches, or an intersection of roads; The audio information is obtained through a microphone arranged at an associated path point.

3. The audio-based tourist attraction service guidance method according to claim 2, characterized in that: Corresponding to each path point, at least two pickups are set, and are set along the connection direction between the path points.

4. The audio-based tourist attraction service guidance method according to claim 1, characterized in that: According to the loudness change corresponding to 85-300 Hz in the first time window in the collected audio information, several frequency intervals in the 1400 Hz frequency band are determined as specific frequency intervals; wherein the first loudness change approximation of adjacent specific frequency intervals in the first time window is greater than a first threshold.

5. The audio-based tourist attraction service guidance method according to claim 4, characterized in that: The first loudness change of the frequency interval in the first time window is obtained as follows: Determine a sequence of loudness values ​​within a first time window of a frequency interval with a first step length; Performing a zeroing operation on the loudness values ​​in the loudness value sequence that are lower than the average loudness value of all frequency intervals in the first time window; The loudness value sequence is normalized by using the maximum loudness value in the first time window to obtain a first loudness change of the frequency interval in the first time window.

6. The audio-based tourist attraction service guidance method according to claim 4, characterized in that: The process of determining the personnel flow trend also includes: Obtaining a mean loudness value within a first time window based on a plurality of selected specific frequency intervals; A reference frequency interval is selected from a plurality of specific frequency intervals, wherein, within a first time window, an objective function corresponding to the reference frequency interval is higher than an objective function corresponding to other specific frequency intervals; and the objective function is the sum of cosine approximations of a second loudness change of the frequency interval within the first time window and a second loudness change of other specific frequency intervals within the first time window.

7. The audio-based tourist attraction service guidance method according to claim 6, characterized in that: Determine a directed graph according to the loudness change value and the coordinates of the associated path points within the reference frequency interval, wherein the nodes of the directed graph are the associated path points, the weights of the directed graph are the loudness change values, and when the loudness change value is negative, the directed graph includes an edge from the current node to the adjacent node, and when the loudness change value is positive, the directed graph includes an edge from the adjacent node to the current node; Remove intermediate nodes whose absolute value of the sum of weight values ​​of the relations is greater than a first threshold from the directed graph; Output personnel flow trends based on the updated directed graph; The intermediate node simultaneously serves as the starting point of at least one edge and the end point of at least one edge in the directed graph.

8. The audio-based tourist attraction service guidance method according to claim 7, characterized in that: The personnel flow trend information includes path point information with positive loudness changes.

9. A computer device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program, and the processor implements the audio-based tourist attraction service guidance method according to any one of claims 1 to 8 when executing the computer program.

10. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed by a processor, the audio-based tourist attraction service guidance method described in any one of claims 1 to 8 is implemented.

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