CN113240354B - Intelligent scenic spot data processing method and system based on electronic map - Google Patents
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Abstract
The invention relates to the technical field of digital communication, and discloses an intelligent scenic spot data processing method and system based on an electronic map to assist scenic spots in intelligent management and control. The method comprises the following steps: each tourist downloads and installs an APP client of a single scenic spot electronic map by a mobile terminal with an LBS function; the cloud server segments the playing route of the scenic spot, and at least one section of the playing route is set as a night road which is not recommended for specific people due to faults or gaps of supporting facilities around the road; the cloud server acquires LBS position information uploaded by the APP client in real time according to a period, screens out specific crowds of non-recommended night lanes layer by layer according to the current LBS position information of each mobile terminal in a specific time period, and then broadcasts corresponding early warning information to the APP client corresponding to the screened specific crowds.
Description
Technical Field
The invention relates to the technical field of digital communication, in particular to an intelligent scenic spot data processing method and system based on an electronic map.
Background
The electronic map is a system for map making and application, is a map generated by the control of an electronic computer, is also a screen map based on a digital cartographic technology, and is a visual real map.
With the rise of intelligent scenic spots, electronic map programs of scenic spots are developed in part of scenic spots so as to facilitate navigation, shopping and tour route planning of tourists.
Meanwhile, in some scenic spots, especially natural landscape scenic spots such as forests and the like, there are some potential safety hazards caused by no lighting light or lack of other supporting facilities in some tourist routes to night travel of some specific crowds (such as old tourists, pregnant women, infants and the like); especially, some routes are long and steep, and when the part of specific people completely stranges the route, the safety problem is easy to breed. In the conventional scenic spot management, such problems are often overlooked due to insufficient staffing or low management awareness. Therefore, the intelligent scenic spot management and control system is based on the electronic map for the first time to assist the scenic spot to perform intelligent management and control. The night line can be opened to some matched tourists (such as young and strong years), and the user experience is enriched; and the specific crowd who does not adapt to the night line can be guided to other safer routes through reasonable management and control.
Disclosure of Invention
The invention aims to disclose an intelligent scenic spot data processing method and system based on an electronic map so as to assist scenic spots in intelligent management and control.
In order to achieve the above object, the present invention discloses an intelligent scenic spot data processing method based on an electronic map, comprising:
each tourist downloads and installs an APP client of a single scenic spot electronic map by a mobile terminal with an LBS (Location Based Services) function;
in the process that any tourist is registered and logged in through an APP client, authorization for using the tourist identity information and the corresponding mobile terminal identity information is obtained, and a data interaction channel between the tourist and a cloud server is established;
the cloud server segments the playing route of the scenic spot, at least one section of the playing route is set as a night road which is not recommended for a specific crowd due to faults or gaps of supporting facilities around the road, and a time period for screening the specific crowd in the scenic spot and carrying out early warning treatment on the specific crowd is set;
the cloud server acquires LBS position information uploaded by the APP client in real time according to a period, and screens out tourist information of a current LBS position in a first set in the scenic spot according to the current LBS position information of each mobile terminal after judging that the current time is in the time period; then, calculating the distance between each tourist in the first set and a target intersection according to the route of the electronic map, wherein the target intersection is a first intersection at which two ends of the night road which is not recommended for the specific crowd respectively intersect with other subsection routes (the other subsection routes refer to routes suitable for all the crowds, the first intersection is a node at which the head and the tail of the night road and other subsection routes form a three-way intersection), and screening out the tourist information in the second set with the distance within a set distance threshold, wherein the maximum value of the distance threshold is smaller than the shortest distance between the target intersection and the adjacent other intersections; then searching LBS historical position information of the tourists in the second set within the previous half hour, judging the traveling route and the direction of the corresponding tourists according to the LBS historical position information (in the judging process, the judgment can be carried out by combining the characteristics of the playing route and the common habits of the tourists), and screening out the tourists in a third set which travel to the night lane which is not recommended for the specific crowd according to the judging result (mainly used for filtering out the tourists which belong to the threshold range of the intersection point but have the traveling direction far away from the night lane); finally, calculating the average speed of the tourists in the third set based on LBS historical position information in the last half hour, estimating the time required by the tourists to walk through the night lane which is not recommended for the specific crowd from the current position according to the average speed of the tourists, and if the estimated time is in a night time period, judging the tourists as the specific crowd needing early warning processing;
and the cloud server broadcasts corresponding early warning information to the APP client sides corresponding to the selected specific crowds.
Preferably, the method of the present invention further comprises: and generating a new planned route for replacing the non-recommended night road for the specific crowd and displaying the new planned route on the APP client corresponding to the specific crowd while broadcasting the early warning information. For example: and providing other suitable driving routes when meeting the three-way intersection.
Preferably, the method of the present invention further comprises: and the APP client performs automatic voice explanation on the received alarm information.
Further, the method of the invention also comprises the following steps: and tracking the adoption result of the specific crowd to the early warning information based on LBS position information, and pushing the contact information of the corresponding tourists to a scenic spot call center or a nearest patrol manager after the tourists in the specific crowd are tracked to enter the night passage which is not recommended for the specific crowd without adopting the early warning information so as to allow corresponding workers to persuade through the telephone.
Optionally, the setting method of the time period is as follows: calculating the average passing time of the tourists at the current target intersection point through the non-recommended night road for the specific crowd according to the statistical experience value of the average speed of the tourists, and then subtracting the average passing time from the sunset time of the current day to be recorded as the starting time of the time period; the end time of the time period is the sunrise time of the next day.
In order to achieve the above object, the present invention further discloses an intelligent scenic spot data processing system based on an electronic map, comprising:
downloading and installing APP clients corresponding to a single scenic spot electronic map of each tourist self-prepared mobile terminal with LBS function;
the APP client is used for acquiring authorization for using the identity information of the tourist and the identity information of the corresponding mobile terminal in the process of registering and logging in any tourist and establishing a data interaction channel with the cloud server;
the cloud server is used for executing the following steps:
step S10, segmenting the playing route of the scenic spot, setting at least one section of the night road which is not recommended for specific people due to faults or vacancy of supporting facilities around the road, and setting a time period for screening the specific people in the scenic spot and carrying out early warning treatment on the specific people;
step S20, obtaining LBS position information uploaded by the APP client in real time according to periods, and screening out tourist information of the current LBS position in a first set in the scenic spot according to the current LBS position information of each mobile terminal after judging that the current time is in the time period; then, calculating the distance between each tourist in the first set and a target intersection according to the route of the electronic map, wherein the target intersection is the first intersection where two ends of the night road which is not recommended for the specific crowd respectively intersect with other subsection routes, and screening out the tourist information in the second set with the distance within a set distance threshold, wherein the maximum value of the distance threshold is smaller than the shortest distance between the target intersection and other adjacent intersections; then searching LBS historical position information of the tourists in the second set within the first half hour, judging the traveling route and direction of the corresponding tourists according to the LBS historical position information, and screening out the tourists in a third set traveling towards the night road which is not recommended for the specific crowd according to the judgment result; finally, calculating the average speed of the tourists in the third set based on LBS historical position information in the last half hour, estimating the time required by the tourists to walk through the night lane which is not recommended for the specific crowd from the current position according to the average speed of the tourists, and if the estimated time is in a night time period, judging the tourists as the specific crowd needing early warning processing;
and step S30, broadcasting corresponding early warning information to the APP client corresponding to the screened specific crowd.
The invention has the following beneficial effects:
the LBS position information is combined with the electronic map, tourists near the target point can be screened out, the traveling direction of the tourists can be judged, and the average speed of the tourists can be calculated, so that specific crowds unsuitable for passage of the night road can be screened out according to the behavior characteristics of the specific tourists (for example, the average speed of old, young, sick and pregnant groups is obviously slower than that of young and strong years), intelligent, fine and diversified management and control can be performed on scenic spots in an auxiliary mode, the corresponding night line can be opened to part of matched tourists (such as young and strong years), and the user experience of the tourists is enriched; and the specific crowd who does not adapt to the night line can be guided to other safer routes through reasonable management and control.
The present invention will be described in further detail below with reference to the accompanying drawings.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the invention and, together with the description, serve to explain the invention and not to limit the invention. In the drawings:
fig. 1 is a schematic flow chart of a method for processing intelligent scenic spot data based on an electronic map according to an embodiment of the present invention.
Detailed Description
The embodiments of the invention will be described in detail below with reference to the drawings, but the invention can be implemented in many different ways as defined and covered by the claims.
Example 1
The embodiment discloses an intelligent scenic spot data processing method based on an electronic map, as shown in fig. 1, including:
and step S1, each tourist downloads and installs APP client sides of the single scenic spot electronic map from the mobile terminal with the LBS function. For example, the mobile terminal is typically a 4G/5G handset.
And step S2, acquiring authorization for using the identity information of the tourist and the corresponding mobile terminal identity information in the process of registering and logging in any tourist through the APP client, and establishing a data interaction channel with the cloud server.
The authorization process of this step includes authorization to obtain the geographical location information. Correspondingly, taking hua as mobile phone mate10 Pro as an example, after authorization, a list of APP clients that can access mobile phone location information can be displayed in the mobile phone setup-security and privacy-location service (using GPS, WLAN and mobile network); clicking on the permission setting of each application can also change the position information access permission in the position information, and three selectable options are generally allowed all the time and allowed and disabled only during the use. For the convenience of the implementation of the subsequent steps, the present embodiment preferably selects the access right of the location information as always permitted.
Step S3, the cloud server segments the playing route of the scenic spot, at least one section of the playing route is set as a night road which is not recommended for the specific crowd due to faults or gaps of supporting facilities around the road, and a time period for screening the specific crowd in the scenic spot and carrying out early warning processing on the specific crowd is set.
At present, in most forests and geological parks, because of high cost, easy damage to natural landscapes and potential safety hazards such as fire danger and the like, part of scenic spot visiting lines are not matched with power transmission lines and lighting facilities.
In this step, the time period may be set by: calculating the average passing time of the tourists at the current target intersection point through the non-recommended night road aiming at the specific crowd according to the statistical experience value of the average speed of the tourists, and then subtracting the average passing time from the sunset time of the current day to be recorded as the starting time of the time period; the end time of the period may be set to the sunrise time of the next day.
And step S4, the cloud server acquires LBS position information uploaded by the APP client in real time according to a period, and screens out specific crowds of the night road which are not recommended layer by layer according to the current LBS position information of each mobile terminal in a specific time period.
In correspondence to the above example, if the mobile terminal is a 4G/5G mobile phone, the LBS location is usually located based on a GPS (Global Positioning System). In a location service system, assisted GPS technology combined with network-based positioning technology is the mainstream of positioning technology. The availability of the GPS is not only compensated by the network positioning technology, but also is based on network positioning in weak GPS signal areas such as indoors and the like. And the GPS reference network is introduced into the mobile communication network, so that the time between the base stations can be kept synchronous, and the network positioning precision is obviously improved.
In this step, it specifically includes:
the cloud server acquires LBS position information uploaded by the APP client in real time according to a period, and screens out tourist information of a first set of the current LBS position in a scenic spot according to the current LBS position information of each mobile terminal after judging that the current time is in a time period; then, calculating the distance between each tourist in the first set and a target intersection according to the route of the electronic map, wherein the target intersection is a first intersection which is formed by two ends of a night road which is not recommended for a specific crowd and is respectively intersected with other subsection routes, screening out the tourist information in the second set with the distance within a set distance threshold, and the maximum value of the distance threshold is smaller than the shortest distance between the target intersection and other adjacent intersections; then searching LBS historical position information of the tourists in the second set within the first half hour, judging the traveling route and direction of the corresponding tourists according to the LBS historical position information, and screening out the tourists in a third set traveling towards a night road which is not recommended for a specific crowd according to the judgment result; and finally, calculating the average speed of the tourists in the third set based on the LBS historical position information in the last half hour, estimating the time required by the tourists to walk through a night road which is not recommended for the specific crowd from the current position according to the average speed of the tourists, and if the estimated time is in a night time period, judging the tourists as the specific crowd needing early warning processing.
Therefore, the complex process can be simplified through the layer-by-layer screening of the upper section, and the data processing amount is greatly reduced. Moreover, through reasonable setting of the distance threshold, interference caused by shunting at other branch roads on the accuracy of prejudgment of the traveling direction of the tourists and the like is effectively avoided.
And step S5, the cloud server broadcasts corresponding early warning information to the APP client corresponding to the screened specific crowd. Preferably, the corresponding APP client performs automatic voice interpretation on the received alarm information, and the effect is equivalent to voice call. Preferably, while broadcasting the early warning information, a new planned route replacing the non-recommended night crossing for the specific crowd is generated and displayed on the APP client corresponding to the specific crowd.
Further, the method in this embodiment further includes: and tracking the adoption result of the specific crowd to the early warning information based on LBS position information, and pushing the contact information of the corresponding tourists to a scenic spot call center or a nearest patrol manager after the tourists in the specific crowd are tracked to enter the night passage which is not recommended for the specific crowd without adopting the early warning information so as to allow corresponding workers to persuade through the telephone.
Example 2
Corresponding to the above method, the present embodiment discloses an intelligent scenic spot data processing system based on an electronic map, comprising:
and downloading and installing the APP client side of the corresponding single scenic spot electronic map of each tourist self-prepared mobile terminal with the LBS function.
The APP client is used for obtaining authorization for using the identity information of the tourist and the corresponding mobile terminal identity information in the process of registering and logging in any tourist and establishing a data interaction channel with the cloud server.
The cloud server is used for executing the following steps:
step S10, segmenting the playing route of the scenic spot, setting at least one segment of the night road that is not recommended for a specific crowd due to a fault or a vacancy of a supporting facility around the road, and setting a time period for screening out the specific crowd in the scenic spot and performing early warning processing on the specific crowd (the specific setting method may refer to the above embodiment, and is not described in detail).
Step S20, obtaining LBS position information uploaded by the APP client in real time according to periods, and screening out tourist information of the current LBS position in a first set in the scenic spot according to the current LBS position information of each mobile terminal after judging that the current time is in the time period; then, calculating the distance between each tourist in the first set and a target intersection according to the route of the electronic map, wherein the target intersection is the first intersection where two ends of the night road which is not recommended for the specific crowd respectively intersect with other subsection routes, and screening out the tourist information in the second set with the distance within a set distance threshold, wherein the maximum value of the distance threshold is smaller than the shortest distance between the target intersection and other adjacent intersections; then searching LBS historical position information of the tourists in the second set within the first half hour, judging the traveling route and direction of the corresponding tourists according to the LBS historical position information, and screening out the tourists in a third set traveling towards the night road which is not recommended for the specific crowd according to the judgment result; and finally, calculating the average speed of the tourists in the third set based on LBS historical position information in the last half hour, estimating the time required by the tourists to walk through the night lane which is not recommended for the specific crowd from the current position according to the average speed of the tourists, and if the estimated time is in a night time period, judging the tourists as the specific crowd needing early warning processing.
And step S30, broadcasting corresponding early warning information to the APP client corresponding to the screened specific crowd.
Preferably, the cloud server is further configured to generate a new planned route that replaces the non-recommended night street for the specific crowd and display the new planned route on the APP client corresponding to the specific crowd while broadcasting the warning information.
Preferably, the APP client in this embodiment is further configured to perform automatic voice explanation on the received alarm information.
Preferably, the cloud server of this embodiment is further configured to track an adoption result of the specific group of people for the warning information based on the LBS location information, and push contact information of a corresponding visitor to a scenic spot call center or a nearest patrol manager after it is tracked that the visitor in the specific group of people enters the night road that is not recommended for the specific group of people without adopting the warning information, so that the corresponding staff can make a recommendation by telephone.
In summary, the intelligent scenic spot data processing method and system based on the electronic map disclosed in the above embodiments of the present invention at least have the following beneficial effects:
the LBS position information is combined with the electronic map, tourists near the target point can be screened out, the traveling direction of the tourists can be judged, and the average speed of the tourists can be calculated, so that specific crowds unsuitable for passage of the night road can be screened out according to the behavior characteristics of the specific tourists (for example, the average speed of old, young, sick and pregnant groups is obviously slower than that of young and strong years), intelligent, fine and diversified management and control can be performed on scenic spots in an auxiliary mode, the corresponding night line can be opened to part of matched tourists (such as young and strong years), and the user experience of the tourists is enriched; and the specific crowd who does not adapt to the night line can be guided to other safer routes through reasonable management and control.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. An intelligent scenic spot data processing method based on an electronic map is characterized by comprising the following steps:
each tourist downloads and installs an APP client of a single scenic spot electronic map by a mobile terminal with an LBS function;
in the process that any tourist is registered and logged in through an APP client, authorization for using the tourist identity information and the corresponding mobile terminal identity information is obtained, and a data interaction channel between the tourist and a cloud server is established;
the cloud server segments the playing route of the scenic spot, at least one section of the playing route is set as a night road which is not recommended for a specific crowd due to faults or gaps of supporting facilities around the road, and a time period for screening the specific crowd in the scenic spot and carrying out early warning treatment on the specific crowd is set;
the cloud server acquires LBS position information uploaded by the APP client in real time according to a period, and screens out tourist information of a current LBS position in a first set in the scenic spot according to the current LBS position information of each mobile terminal after judging that the current time is in the time period; then, calculating the distance between each tourist in the first set and a target intersection according to the route of the electronic map, wherein the target intersection is the first intersection where two ends of the night road which is not recommended for the specific crowd respectively intersect with other subsection routes, and screening out the tourist information in the second set with the distance within a set distance threshold, wherein the maximum value of the distance threshold is smaller than the shortest distance between the target intersection and other adjacent intersections; then searching LBS historical position information of the tourists in the second set within the first half hour, judging the traveling route and direction of the corresponding tourists according to the LBS historical position information, and screening out the tourists in a third set traveling towards the night road which is not recommended for the specific crowd according to the judgment result; finally, calculating the average speed of the tourists in the third set based on LBS historical position information in the last half hour, estimating the time required by the tourists to walk through the night lane which is not recommended for the specific crowd from the current position according to the average speed of the tourists, and if the estimated time is in a night time period, judging the tourists as the specific crowd needing early warning processing;
and the cloud server broadcasts corresponding early warning information to the APP client sides corresponding to the selected specific crowds.
2. The method of claim 1, further comprising:
and generating a new planned route for replacing the non-recommended night road for the specific crowd and displaying the new planned route on the APP client corresponding to the specific crowd while broadcasting the early warning information.
3. The method of claim 2, further comprising:
and the APP client performs automatic voice explanation on the received alarm information.
4. The method of any of claims 1 to 3, further comprising:
and tracking the adoption result of the specific crowd to the early warning information based on LBS position information, and pushing the contact information of the corresponding tourists to a scenic spot call center or a nearest patrol manager after the tourists in the specific crowd are tracked to enter the night passage which is not recommended for the specific crowd without adopting the early warning information so as to allow corresponding workers to persuade through the telephone.
5. The method according to any one of claims 1 to 3, wherein the time period is set by:
calculating the average passing time of the tourists at the current target intersection point through the non-recommended night road for the specific crowd according to the statistical experience value of the average speed of the tourists, and then subtracting the average passing time from the sunset time of the current day to be recorded as the starting time of the time period; the end time of the time period is the sunrise time of the next day.
6. An intelligent scenic spot data processing system based on an electronic map is characterized by comprising:
downloading and installing APP clients corresponding to a single scenic spot electronic map of each tourist self-prepared mobile terminal with LBS function;
the APP client is used for acquiring authorization for using the identity information of the tourist and the identity information of the corresponding mobile terminal in the process of registering and logging in any tourist and establishing a data interaction channel with the cloud server;
the cloud server is used for executing the following steps:
step S10, segmenting the playing route of the scenic spot, setting at least one section of the night road which is not recommended for specific people due to faults or vacancy of supporting facilities around the road, and setting a time period for screening the specific people in the scenic spot and carrying out early warning treatment on the specific people;
step S20, obtaining LBS position information uploaded by the APP client in real time according to periods, and screening out tourist information of the current LBS position in a first set in the scenic spot according to the current LBS position information of each mobile terminal after judging that the current time is in the time period; then, calculating the distance between each tourist in the first set and a target intersection according to the route of the electronic map, wherein the target intersection is the first intersection where two ends of the night road which is not recommended for the specific crowd respectively intersect with other subsection routes, and screening out the tourist information in the second set with the distance within a set distance threshold, wherein the maximum value of the distance threshold is smaller than the shortest distance between the target intersection and other adjacent intersections; then searching LBS historical position information of the tourists in the second set within the first half hour, judging the traveling route and direction of the corresponding tourists according to the LBS historical position information, and screening out the tourists in a third set traveling towards the night road which is not recommended for the specific crowd according to the judgment result; finally, calculating the average speed of the tourists in the third set based on LBS historical position information in the last half hour, estimating the time required by the tourists to walk through the night lane which is not recommended for the specific crowd from the current position according to the average speed of the tourists, and if the estimated time is in a night time period, judging the tourists as the specific crowd needing early warning processing;
and step S30, broadcasting corresponding early warning information to the APP client corresponding to the screened specific crowd.
7. The system of claim 6, wherein the cloud server is further configured to generate a new planned route that replaces the non-recommended night crossing for the specific group of people and display the new planned route on the APP client corresponding to the specific group of people while broadcasting the warning information.
8. The system of claim 7, wherein the APP client is further configured to perform automatic voice interpretation of the received alert information.
9. The system according to any one of claims 6 to 8, wherein the cloud server is further configured to track an adoption result of the specific group of people for the warning information based on LBS location information, and when it is tracked that visitors in the specific group of people enter the non-recommended night crossing for the specific group of people without adopting the warning information, push contact information of the corresponding visitors to a scenic area call center or a nearest patrol manager, so that the corresponding staff can persuade the contact information through a telephone.
10. The system according to any one of claims 6 to 8, wherein the time period is set by:
calculating the average passing time of the tourists at the current target intersection point through the non-recommended night road for the specific crowd according to the statistical experience value of the average speed of the tourists, and then subtracting the average passing time from the sunset time of the current day to be recorded as the starting time of the time period; the end time of the time period is the sunrise time of the next day.
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