CN117312684A - Scenic spot guide element plan generating system and method based on artificial intelligence - Google Patents
Scenic spot guide element plan generating system and method based on artificial intelligence Download PDFInfo
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Abstract
The invention discloses a scenic spot guide element plan generating system and method based on artificial intelligence, which relate to the technical field of plan generation, wherein a plan generating module periodically acquires multi-source data of all scenic spots after generating a scenic spot plan guide map based on a plan generating technology according to map data of a scenic spot, a guide element database and personalized requirements of users, ranking coefficients are generated for all scenic spots according to the multi-source data, ranking of all scenic spots is updated in a ranking area of the plan guide map, and a scenic spot highlighting module highlights all scenic spots according to the ranking coefficients based on view highlighting technology. The invention not only enables tourists to intuitively identify important scenic spots and characteristic guide elements on a plan view and avoids the tourists from missing the important scenic spots, but also plans a travel path for the tourists, thereby helping the tourists to guide in scenic spots more efficiently.
Description
Technical Field
The invention relates to the technical field of plan generation, in particular to a system and a method for generating a scenic spot guiding element plan based on artificial intelligence.
Background
With the continuous development of economy and the improvement of living standard of people, the tourist industry is vigorous, more and more people are willing to go out for sightseeing, especially to scenic spots with graceful nature and long history culture for playing;
tourist attractions often have complex terrains, rich and diverse landscapes and various services, in which tourists may face difficulties in navigation and positioning, and in order to enhance the tourist's tour experience, a attraction guide element plan generation system has been developed.
The prior art has the following defects:
in tourist attractions, various attractions are usually included, the existing plan generating system usually only depends on navigation routes to generate a static plane guide diagram, and the plane guide diagram only marks the position and the route of each attraction, however, the static plane guide diagram cannot rank all attractions and make corresponding highlighting marks, tourists cannot easily judge which attractions are more worthy of visiting, and in a attraction with a plurality of attractions, the tourists may miss some places worth of one trip because the importance of each attraction cannot be distinguished.
Disclosure of Invention
The invention aims to provide a scenic spot guiding element plan generating system and method based on artificial intelligence, which are used for solving the defects in the background technology.
In order to achieve the above object, the present invention provides the following technical solutions: the scenic spot guiding element plan generating system based on artificial intelligence comprises a map data acquisition module, an element identification module, a database module, a plan generating module, a ranking updating module, a scenic spot highlighting module, a data updating module, a display module and an intelligent navigation module;
a map data acquisition module: acquiring map data of a scenic spot from a geospatial data source;
element identification module: analyzing scenic spots through image processing and computer vision technology, and identifying guide elements;
a database module: for storing the recognition result of the guide element in a database;
a plan view generation module: generating a scenic spot plane guide map based on a plane map generating technology according to map data of a scenic spot, a guide element database and personalized requirements of a user;
a ranking updating module: periodically acquiring multi-source data of each scenic spot, generating ranking coefficients for each scenic spot according to the multi-source data, and updating the ranks of all scenic spots in the ranking area of the plane guide graph;
and the scenic spot highlighting module is used for: performing highlighting processing on each scenic spot according to the ranking coefficient based on view highlighting technology;
and a data updating module: monitoring the real-time change of the scenic spot, and updating the guide element database when the scenic spot changes;
and a display module: the method comprises the steps of displaying a plane guide graph, a scenic spot ranking and a scenic spot mark which is highlighted in the plane guide graph;
and the intelligent navigation module is used for: and taking the position of the display module as the position of the tourist and marking the position on the plane guide map by using the pattern, and planning a walking path for the tourist by the intelligent navigation module after the tourist determines the scenic spot to be moved and the tour preference.
In a preferred embodiment, the ranking updating module periodically acquires multi-source data of each scenic spot, wherein the multi-source data comprises tour data and economic data, the tour data comprises a standard deviation index of people flow and a ratio of people average tour duration, and the economic data comprises economic benefit coefficients.
In a preferred embodiment, the ranking updating module respectively marks the standard deviation index of the people flow, the average tour time length ratio and the economic benefit coefficient as rlb, tlc, jxs;
the ranking coefficient pmx is obtained by comprehensive calculation after the scaled standard deviation index of the people flow, the average tour time length ratio and the economic benefit coefficient are removed from dimension, and the calculation expression is as follows:
in the formula, tlc is the average tour time length ratio of people, jxs is the economic benefit coefficient, rlb is the standard deviation index of people flow, a 1 、a 2 、a 3 The ratio of the average tour time length, the economic benefit coefficient and the standard deviation index of the people flow are respectively the ratio coefficient of a 1 、a 2 、a 3 Are all greater than 0.
In a preferred embodiment, after the ranking updating module obtains the ranking coefficient pmx, each scenic spot in the scenic spot is ranked from large to small according to the ranking coefficient pmx, and the ranking of all the scenic spots is updated in the ranking area of the plane guide map, and the larger the value of the ranking coefficient pmx of the scenic spot is, the more front the ranking of the scenic spot in the ranking area of the plane guide map is.
In a preferred embodiment, the logic for calculating the standard deviation index rlb of the traffic is:
calculating the standard deviation RC and the average value of the people flow
If the average value of the people flow is less than or equal to the flow threshold value, and the standard deviation RC of the people flow is less than or equal to the standard deviation threshold value, rlb =0.8;
if the average value of the people flow is less than or equal to the flow threshold value, and the standard deviation RC of the people flow is more than the standard deviation threshold value, rlb =0.6;
if the average value of the people flow is greater than the flow threshold value, and the standard deviation RC of the people flow is greater than the standard deviation threshold value, rlb =0.4;
if the average value of the people flow is greater than the flow threshold, and the standard deviation RC of the people flow is less than or equal to the standard deviation threshold, rlb =0.2.
In a preferred embodiment, the standard deviation RC of the traffic is calculated as:
where i= {1, 2, 3,..n }, n represents the number of sampling time points, n is a positive integer, and RL i Representing the flow of people at the ith sampling time point,is a human beingFlow average.
In a preferred embodiment, the calculation expression of the average tour duration ratio is:
in the formula, cavg is the people's average tour time length of the scenic spot in the scenic spot operation time, and yc is the scenic spot operation time length.
In a preferred embodiment, the economic benefit coefficient is calculated as:
in the formula, whc is the maintenance cost of the scenic spot, rs is the number of tourists of the scenic spot, rxf is the average consumption of people, xfs is the consumption coefficient between industries, and cz is the industrial production value.
In a preferred embodiment, the salient point module performs salient processing on each scenery spot according to the ranking coefficient based on the view salient point technology, and the salient point processing comprises the following steps:
according to the ranking coefficient of the scenic spots, the identification of the scenic spots is subjected to enlargement or reduction treatment;
adjusting the identification brightness of the scenic spots according to the ranking coefficients of the scenic spots;
and applying light effects of different colors for the marks of different sceneries according to the ranking coefficients of the sceneries.
The invention also provides a scenic spot guiding element plan generating method based on artificial intelligence, which comprises the following steps:
the method comprises the steps of obtaining map data of scenic spots from a geospatial data source, analyzing the scenic spots through image processing and computer vision technology, identifying guide elements, storing identification results of the guide elements in a database, generating a scenic spot plane guide map based on a plane map generating technology according to map data of the scenic spots, guide element database and personalized requirements of users, periodically obtaining multi-source data of all the scenic spots, generating ranking coefficients for all the scenic spots according to the multi-source data, updating ranks of all the scenic spots in the ranking area of the plane guide map, performing highlighting processing on all the scenic spots according to the ranking coefficients based on a view highlighting technology, displaying the plane guide map, the ranks of the scenic spots and scenic spot identifications subjected to highlighting processing in the plane guide map, monitoring real-time changes of the scenic spots and updating the guide element database, taking the display positions as positions of tourists and using pattern marks on the plane guide map, and planning a walk path for the tourists after the tourists determine the scenic spots and tourist preferences needing to go.
In the technical scheme, the invention has the technical effects and advantages that:
1. according to the invention, after the plan generating module generates the plan guide map of the scenic spot based on map data of the scenic spot, the guide element database and personalized requirements of users, the ranking updating module periodically acquires multi-source data of each scenic spot, generates ranking coefficients for each scenic spot according to the multi-source data, updates the ranking of all scenic spots in the ranking area of the plan guide map, and performs highlighting processing on each scenic spot according to the ranking coefficients by the scenic spot highlighting module based on the view highlighting technology, and after the scenic spot and the tour preference which need to be addressed are determined by the tourist, the intelligent navigation module plans a tour path for the tourist, so that the tourist can intuitively identify important scenic spots and characteristic guide elements on the plan, avoid the tourist from missing the important scenic spot, plan the tour path for the tourist, and help the tourist to guide in the scenic spot more efficiently;
2. according to the method, the ranking coefficients are comprehensively calculated and obtained after the calibrated standard deviation index of the traffic flow, the average tour duration ratio and the economic benefit coefficient are removed, the data processing efficiency is effectively improved, after the ranking coefficients pmx are obtained, all scenic spots in the scenic spots are ranked from large to small according to the ranking coefficients pmx, the ranking of all scenic spots is updated in the ranking area of the plane guide graph, the larger the value of the ranking coefficient pmx of the scenic spot is, the more front the ranking of the scenic spots in the ranking area of the plane guide graph is, and therefore tourists and tour guides can plan tour routes better.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments described in the present invention, and other drawings may be obtained according to these drawings for a person having ordinary skill in the art.
FIG. 1 is a block diagram of a system according to the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1: referring to fig. 1, the scenic spot guiding element plan generating system based on artificial intelligence according to the present embodiment includes a map data acquiring module, an element identifying module, a database module, a plan generating module, a ranking updating module, a scenic spot highlighting module, a data updating module, a display module, and an intelligent navigation module;
A. a map data acquisition module: the module is responsible for acquiring map data of scenic spots from a geographic information system, an open map data source or other data sources, wherein the map data comprises elements such as geographic coordinates, building outlines, road networks, marks, landscapes and the like, and the map data is sent to the element identification module and the plan generation module;
determining data requirements: firstly, determining specific requirements and targets for acquiring map data, and definitely determining which elements and attributes are required, such as geographic coordinates, building information, road networks, signs, landscapes and the like;
determining the source of the data: determining a proper data source according to the data demand; geographic Information Systems (GIS) typically contain rich geospatial data, while open map data sources such as OpenStreetMap, google Maps, etc. also provide publicly available map data;
accessing a map data source: accessing a geographic information system or an open map data source through an API interface or a download service; some data sources may need to register and acquire access keys to ensure that data is legally acquired;
data download or query: according to the data requirement, downloading or inquiring the data; the complete map data set may be obtained by a data download service or the data of a specific area or element may be obtained by a query service.
B. Element identification module: the module analyzes scenic spots through image processing and computer vision technology, identifies guide elements such as buildings, marks, landscapes and the like, and sends guide element data to the database module;
object detection: identifying guide elements such as buildings, marks, landscapes and the like in the scenic spot images by utilizing a computer vision technology and adopting an object detection algorithm such as target detection, edge detection and the like;
feature extraction: extracting features of the detected guide elements to obtain feature information such as the shape, the size, the color and the like of the object so as to facilitate subsequent classification and identification;
guide element classification: classifying the guide elements by adopting an image classification algorithm such as a Support Vector Machine (SVM), deep learning (such as convolutional neural network) and the like according to the extracted characteristic information, and distinguishing buildings, marks, landscapes and the like;
geographic coordinate positioning: associating the identified guide elements with geographic coordinates, determining their location and coordinates on the scenic spot map for marking and presentation on the planar guide map;
guide element marking: the identified guide elements are marked on the planar guide map according to the classification and the geographic coordinate information, for example, the map is marked with icons or names of buildings, marks and landscapes.
C. A database module: storing the recognition result of the guide element in a database for subsequent plan generation, wherein the database needs to have an efficient storage and retrieval mechanism to support a rapid plan generation process;
database design: designing a database structure, and determining the attributes of guide elements to be stored, such as building names, geographic coordinates, classification information, feature descriptions and the like; selecting proper data types and index modes to optimize storage and retrieval performances;
creating a database: according to the design of the database, a proper data table and fields are created, so that the structure of the database can meet the storage requirement of the guide elements;
and (3) data storage: storing the recognition result of the guide element in a database; the results comprise guide element information obtained through image processing and computer vision recognition, and associated geographic coordinates and other data;
data index: for fields that need frequent retrieval, such as geographic coordinates, building names, etc., an appropriate index is created to increase the retrieval efficiency.
D. A plan view generation module: generating a scenic spot plane guide map based on a plane map generating technology according to map data of scenic spots, a guide element database and personalized requirements of users, wherein the plane map generating technology comprises map drawing, element layout algorithm, route planning and the like, and the plane guide map is sent to a display module;
map data preparation: obtaining map data of scenic spots from a geographic information system, an open map data source or other data sources, wherein the map data comprise geographic coordinates, building outlines, road networks, marks, landscapes and other elements;
guiding element database query: inquiring guide elements needing to be displayed on a plan from a guide element database, wherein the guide elements comprise information such as buildings, marks, landscapes and the like; according to the personalized requirements of the user, the displayed guide elements can be dynamically selected;
and (3) map drawing: drawing elements such as roads, buildings, marks, landscapes and the like in map data on a plane map by using a map drawing tool or a map drawing library to form a basic plane map;
element layout algorithm: reasonably distributing and arranging the guide elements by adopting an element distribution algorithm; according to the position, importance and user individuation requirements of the guide elements, determining the position and display mode of the guide elements on the plan view so as to improve the guide effect;
route planning: if the plane guide diagram needs to show the tour route, a route planning algorithm can be applied to plan the tour route according to the position, distance, connectivity and other factors of the guide elements in the scenic spot, and the tour route is marked on the plane diagram;
personalized customization: according to the personalized requirements of users, specific marks, labels or icons, such as self-defined scenic spots, parking lots, restaurants and other information, can be added on the plan so as to meet the specific navigation requirements of the users;
beautifying the map: beautifying and optimizing the generated plan view to make the visual effect more attractive, and ensuring the clear and recognizable information on the graph;
plan view output: the final scenic spot plan guide map is generated and can be output as an image file or web page format for viewing and use by the tourists.
E. A ranking updating module: and periodically acquiring multi-source data of each scenic spot, generating ranking coefficients for each scenic spot according to the multi-source data, updating the ranks of all scenic spots in a ranking area of the plane guide graph, sending the ranking coefficients to a scenic spot highlighting module, and sending the ranking data to a display module.
F. And the scenic spot highlighting module is used for: the view highlighting technology comprises the steps of enlarging or reducing different scenic spot identifications according to ranking coefficients, increasing or reducing the brightness of the different scenic spot identifications according to the ranking coefficients, enabling the different scenic spot identifications to emit light with different colors according to the ranking coefficients, and the like.
G. And a data updating module: the module is responsible for monitoring the real-time changes of scenic spots, such as building construction, sign change and the like, and when the scenic spots change, the system needs to update the guide element database in time and maintain the accuracy of the plan;
and (3) detecting change: performing change detection on the acquired image data through image processing and computer vision technology; comparing the difference between the real-time data and the historical data, and identifying the changed areas and elements, such as newly added buildings, changed marks and the like;
updating a database: updating the detected change information into a guide element database; adding attribute information (such as names, geographic coordinates, classifications and the like) of the newly added guide elements into a database; updating attribute information of the changed guide elements;
updating a plan: updating the guide elements on the plan according to the change of the database; and drawing the newly added guide elements on the plan, and updating the information of the existing guide elements so as to maintain the accuracy of the plan.
H. And a display module: the intelligent navigation module is used for displaying the plane guide graph, the scenic spot ranking and the scenic spot identification which is highlighted in the plane guide graph, and sending the position information of the display module to the intelligent navigation module;
plane guide view shows: displaying the loaded plane guide map data to tourists in a map form; the guide elements can be drawn on the map using a map display library or a map drawing tool to form a planar guide map;
scenic spot ranking shows: displaying ranking information of scenic spots on the plane guide graph; the ranking values of the scenic spots can be displayed on the corresponding scenic spot identifications in a label or icon mode, so that tourists can quickly know the importance and welcome degree of the scenic spots;
and (5) highlighting and displaying scenic spots: displaying the highlighted scenic spot marks on the plane guide graph in a special style or icon; these sight marks may be enlarged, highlighted or use of different colors of light, etc., to attract the attention of the tourist and highlight its importance;
navigation function: the tourists are provided with a tour guide function, so that the tourists can find interesting scenic spots according to the plane guide diagram, plan tour paths and know basic information of the scenic spots;
user personalization: allowing tourists to customize the display mode of the plane guide graph according to personalized requirements and preferences of users; this may include selecting to display a particular category of attractions, hiding certain attractions, custom tags, etc.;
interaction function: providing interactive functions of the plane guide graph for enhancing user experience; the tourist can zoom in, zoom out, drag the map to better view and plan the tour route.
I. And the intelligent navigation module is used for: the position of the display module is taken as the position of the tourist and marked on the plane guide diagram by using the pattern, and after the tourist determines the scenic spot to be moved to and the tourist preference, the intelligent navigation module plans a moving path for the tourist, and the tourist preference comprises that the tourist is to be moved to the determined scenic spot directly, and the tourist hopes to move to the determined scenic spot to be moved to other scenic spots;
obtaining the position of a tourist: the method comprises the steps of obtaining real-time position information of tourists through a positioning technology (such as GPS or Wi-Fi positioning), and marking the position information on a plane guide chart as a display module position;
tour preference acquisition: the tourist preference information is obtained by interacting with the tourist or setting a tourist preference option in the system; the tourist can specify the determined scenic spot which needs to go directly or hope to visit other scenic spots along the way to the determined scenic spot;
navigation path planning: according to the position and the tour preference of tourists, performing intelligent tour guide path planning by using a navigation algorithm; the navigation path planning considers factors such as distance between scenic spots, tour preference, importance and ranking of scenic spots and the like, and feasibility between the position of tourists and the scenic spots, and finally plans out an optimal tour path;
and (5) displaying a navigation path: displaying the intelligently planned navigation path on a plane guide graph; marking the tour path by using different colors or line patterns, so that tourists can conveniently and clearly see the planned tour path on the map;
providing navigation information: providing tourists with navigation information on the plane guide map; each scenic spot is briefly introduced, including names, characteristics, historical backgrounds and the like, so as to help tourists to make tour decisions;
real-time navigation update: in the travelling process of tourists, the tour guide path is updated and adjusted in real time according to the actual position and the change of the tour guide path, so that the tourists can plan tour guide according to the latest path;
interaction navigation: providing an interactive navigation function for enhancing user experience; the tourist can manually adjust on the tour guide path, and select to skip some scenic spots or add other scenic spots to meet personalized requirements.
According to the method and the system, after the plan generating module generates the plan guide map of the scenic spot based on map data of the scenic spot, the guide element database and personalized requirements of users, the ranking updating module periodically acquires multi-source data of all the scenic spots, ranking coefficients are generated for all the scenic spots according to the multi-source data, ranking of all the scenic spots is updated in the ranking area of the plan guide map, the scenic spot highlighting module highlights all the scenic spots based on the ranking coefficients based on the view highlighting technology, and after the tourists determine scenic spots and tour preferences needing to go, the intelligent navigation module plans a tour path for the tourists, so that the tourists can intuitively identify important scenic spots and characteristic guide elements on the plan, avoid the tourists from missing the important scenic spots, plan the tour path for the tourists, and help the tourists to guide in the scenic spot more efficiently.
Example 2: the ranking updating module periodically acquires multi-source data of all the scenic spots, generates ranking coefficients for all the scenic spots according to the multi-source data, updates the ranking of all the scenic spots in a ranking area of the plane guide graph, sends the ranking coefficients to the scenic spot highlighting module, and sends the ranking data to the display module.
The ranking updating module periodically acquires multi-source data of each scenic spot, wherein the multi-source data comprises tour data and economic data, the tour data comprises a traffic standard deviation index and a per capita tour duration ratio, and the economic data comprises economic benefit coefficients;
the standard deviation index of the people flow, the average tour time length ratio and the economic benefit coefficient are respectively calibrated to rlb, tlc, jxs;
the ranking coefficient pmx is obtained by comprehensively calculating the calibrated standard deviation index of the people flow, the average tour time length ratio and the economic benefit coefficient after removing the dimension, and the calculation expression is as follows:
in the formula, tlc is the average tour time length ratio of people, jxs is the economic benefit coefficient, rlb is the standard deviation index of people flow, a 1 、a 2 、a 3 The ratio of the average tour time length, the economic benefit coefficient and the standard deviation index of the people flow are respectively the ratio coefficient of a 1 、a 2 、a 3 Are all greater than 0.
After the ranking coefficients pmx are obtained, ranking all the scenic spots in the scenic spots according to the ranking coefficients pmx from large to small, and updating the ranking of all the scenic spots in the ranking area of the plane guide graph, wherein the higher the value of the ranking coefficient pmx of the scenic spot is, the higher the ranking of the scenic spot in the ranking area of the plane guide graph is.
The calculation logic of the standard deviation index rlb of the people flow is as follows:
and calculating the standard deviation RC of the flow of people, wherein the expression is as follows:
where i= {1, 2, 3,..n }, n represents the number of sampling time points, n is a positive integer, and RL i Representing the flow of people at the ith sampling time point,is the average value of the people flow;
if the average value of the people flow is less than or equal to the flow threshold value and the standard deviation RC of the people flow is less than or equal to the standard deviation threshold value, the overall people flow of the scenic spot is smaller and the people flow is relatively stable within the operation time period of the scenic spot, wherein rlb =0.8;
if the average value of the traffic is less than or equal to the traffic threshold value and the standard deviation RC of the traffic is greater than the standard deviation threshold value, the overall traffic of the scenic spot is smaller and the traffic is relatively unstable (i.e. the traffic is greater than the traffic threshold value occasionally) within the operation time period of the scenic spot, rlb =0.6;
if the average value of the traffic is greater than the traffic threshold and the standard deviation RC of the traffic is greater than the standard deviation threshold, it indicates that the overall traffic of the scenic spot is greater and the traffic is relatively unstable (i.e., the traffic is less than the traffic threshold occasionally) within the operating time period of the scenic spot, rlb =0.4;
if the average value of the traffic is greater than the traffic threshold and the standard deviation RC of the traffic is less than or equal to the standard deviation threshold, the overall traffic of the scenic spot is larger and the traffic is relatively stable within the operation time period of the scenic spot, rlb =0.2.
In summary, the larger the standard deviation index rlb of the pedestrian flow is, the smaller the pedestrian flow of the scenic spot in different periods is when the scenic spot operates.
The calculation expression of the average person tour time length ratio is as follows:
in the method, cavg is the average sightseeing time length of the scenic spot in the scenic spot operation time, yc is the scenic spot operation time length, and the logic for acquiring the average sightseeing time length of the scenic spot in the scenic spot operation time is as follows: when a tourist enters a certain scenic spot, a gate at an entrance of the scenic spot is used for scanning a ticket two-dimensional code, the tourist starts to record the tourist's duration after entering, an entry time point is obtained, when the tourist passes through the gate at an exit of the scenic spot, the gate at the entrance of the scenic spot is used for scanning the ticket two-dimensional code, the tourist finishes recording the tourist's duration after exiting, an exit time point is obtained, the entry time point is subtracted from the exit time point to obtain the tourist's duration, and the tourist's duration of all the entry scenic spots in the operation time of the scenic spot can be compared with the tourist's duration of the tourist in the operation time of the scenic spot.
The calculation expression of the economic benefit coefficient is as follows:
wherein whc is the maintenance cost of the scenic spot, rs is the number of tourists in the scenic spot, rxf is the average consumption of people, xfs is the inter-industry consumption coefficient, cz is the industry yield, the inter-industry consumption coefficient represents the consumption level of the tourist industry on other industries, and the industry yield represents the yield of each industry.
According to the method, the ranking coefficient is comprehensively calculated and obtained after the calibrated standard deviation index of the traffic flow, the average tour duration ratio and the economic benefit coefficient are removed, the processing efficiency of data is effectively improved, after the ranking coefficient pmx is obtained, all scenic spots in the scenic spots are ranked from large to small according to the ranking coefficient pmx, the ranking of all scenic spots is updated in the ranking area of the plane guide graph, the larger the ranking coefficient pmx value of the scenic spots is, the more front the ranking of the scenic spots in the ranking area of the plane guide graph is, and therefore tourists and tour guides can plan tour routes better.
The view highlighting module performs highlighting processing on each view point according to the ranking coefficient based on view highlighting technology, wherein the view highlighting technology comprises the steps of enlarging or reducing different view point identifications according to the ranking coefficient, increasing or reducing the brightness of the different view point identifications according to the ranking coefficient, enabling the different view point identifications to emit lights with different colors according to the ranking coefficient, and the like, and the view highlighting module comprises the following steps:
1) The size of the mark is adjusted according to the ranking coefficient: according to the ranking coefficient of the scenic spots, the identification of the scenic spots is subjected to enlargement or reduction treatment; higher ranked sights can highlight their importance by magnifying the logo, and lower ranked sights can attenuate their visual impact by shrinking the logo;
2) Adjusting the brightness of the mark: adjusting the identification brightness of the scenic spots according to the ranking coefficients of the scenic spots; the scenic spots with higher ranks can increase the brightness of the marks so that the scenic spots are more striking and attractive on the map, and the scenic spots with lower ranks can reduce the brightness of the marks so that the scenic spots are relatively darker on the map;
3) Using different colors of light: according to the ranking coefficients of the scenic spots, applying light effects of different colors for the marks of different scenic spots; higher ranked attractions may use vivid colors, lower ranked attractions may use darker colors to enhance visual contrast and highlight effects;
4) Adjusting the shape of the mark: adjusting the identification shape of the scenic spot according to the ranking coefficient of the scenic spot; the scenic spots with higher ranks can adopt more prominent and unique identification shapes, and the scenic spots with lower ranks can adopt common or simplified identification shapes;
5) And (3) comprehensive treatment: the above steps of highlighting are comprehensively applied to the marks of all scenic spots, and a scenic spot guide diagram after view highlighting is generated.
Example 3: referring to fig. 1, the method for generating a scenic spot guiding element plan based on artificial intelligence according to the embodiment includes the following steps:
obtaining map data of scenic spots from a geographic information system, an open map data source or other data sources, wherein the map data comprises geographic coordinates, building outlines, road networks, marks, landscapes and other elements;
analyzing the scenic spot through image processing and computer vision technology, and identifying guiding elements such as buildings, marks, landscapes and the like;
storing the recognition result of the guide element in a database for subsequent plan generation, wherein the database needs to have an efficient storage and retrieval mechanism to support a rapid plan generation process;
generating a scenic spot plane guide map based on a plane map generating technology according to map data of scenic spots, a guide element database and personalized requirements of users, wherein the plane map generating technology comprises map drawing, element layout algorithm, route planning and the like;
periodically acquiring multi-source data of each scenic spot, generating ranking coefficients for each scenic spot according to the multi-source data, and updating the ranks of all scenic spots in the ranking area of the plane guide graph;
performing highlighting processing on each scenic spot according to the ranking coefficient based on a view highlighting technology, wherein the view highlighting technology comprises the steps of enlarging or reducing different scenic spot identifications according to the ranking coefficient, increasing or reducing the brightness of the different scenic spot identifications according to the ranking coefficient, enabling the different scenic spot identifications to emit lights with different colors according to the ranking coefficient and the like;
monitoring the real-time change of scenic spots, such as building construction, sign change and the like, when the scenic spots change, the guide element database needs to be updated in time, and the accuracy of the plan is maintained;
displaying the plane guide graph, the scenic spot ranking and the scenic spot mark which is highlighted in the plane guide graph;
and the display position is taken as the position of the tourist and marked on the plane guide map by using the pattern, and after the tourist determines the scenic spot to be moved to and the tourist's preference, the tourist plans a moving path for the tourist, and the tourist's preference comprises that the tourist is to be moved to the determined scenic spot directly, and other scenic spots are additionally moved to the tourist on the way of the determined scenic spot.
The above formulas are all formulas with dimensions removed and numerical values calculated, the formulas are formulas with a large amount of data collected for software simulation to obtain the latest real situation, and preset parameters in the formulas are set by those skilled in the art according to the actual situation.
In the description of the present specification, the descriptions of the terms "one embodiment," "example," "specific example," and the like, mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The preferred embodiments of the invention disclosed above are intended only to assist in the explanation of the invention. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention. The invention is limited only by the claims and the full scope and equivalents thereof.
Claims (10)
1. Scenic spot direction factor plan generation system based on artificial intelligence, its characterized in that: the system comprises a map data acquisition module, an element identification module, a database module, a plan view generation module, a ranking updating module, a scenic spot highlighting module, a data updating module, a display module and an intelligent navigation module;
a map data acquisition module: acquiring map data of a scenic spot from a geospatial data source;
element identification module: analyzing scenic spots through image processing and computer vision technology, and identifying guide elements;
a database module: for storing the recognition result of the guide element in a database;
a plan view generation module: generating a scenic spot plane guide map based on a plane map generating technology according to map data of a scenic spot, a guide element database and personalized requirements of a user;
a ranking updating module: periodically acquiring multi-source data of each scenic spot, generating ranking coefficients for each scenic spot according to the multi-source data, and updating the ranks of all scenic spots in the ranking area of the plane guide graph;
and the scenic spot highlighting module is used for: performing highlighting processing on each scenic spot according to the ranking coefficient based on view highlighting technology;
and a data updating module: monitoring the real-time change of the scenic spot, and updating the guide element database when the scenic spot changes;
and a display module: the method comprises the steps of displaying a plane guide graph, a scenic spot ranking and a scenic spot mark which is highlighted in the plane guide graph;
and the intelligent navigation module is used for: and taking the position of the display module as the position of the tourist and marking the position on the plane guide map by using the pattern, and planning a walking path for the tourist by the intelligent navigation module after the tourist determines the scenic spot to be moved and the tour preference.
2. The artificial intelligence based scenic spot guiding element plan generating system of claim 1, wherein: the ranking updating module periodically acquires multi-source data of each scenic spot, wherein the multi-source data comprises tour data and economic data, the tour data comprises a standard deviation index of people flow and a ratio of people average tour duration, and the economic data comprises economic benefit coefficients.
3. The artificial intelligence based scenic spot guiding element plan generating system of claim 2, wherein: the ranking updating module respectively marks the standard deviation index of the people flow and the average tour time length ratio and the economic benefit coefficient as rlb, tlc, jxs;
the ranking coefficient pmx is obtained by comprehensive calculation after the scaled standard deviation index of the people flow, the average tour time length ratio and the economic benefit coefficient are removed from dimension, and the calculation expression is as follows:
in the formula, tlc is the average tour time length ratio of people, jxs is the economic benefit coefficient, rlb is the standard deviation index of people flow, a 1 、a 2 、a 3 The ratio of the average tour time length, the economic benefit coefficient and the standard deviation index of the people flow are respectively the ratio coefficient of a 1 、a 2 、a 3 Are all greater than 0.
4. The artificial intelligence based scenic spot guiding element plan generating system according to claim 3, wherein: after the ranking updating module obtains the ranking coefficient pmx, each scenic spot in the scenic spot is ranked from large to small according to the ranking coefficient pmx, the ranking of all scenic spots is updated in the ranking area of the plane guide graph, and the larger the value of the ranking coefficient pmx of the scenic spot is, the higher the ranking of the scenic spot in the ranking area of the plane guide graph is.
5. The artificial intelligence based scenic spot guiding element plan generating system according to claim 4, wherein: the calculation logic of the standard deviation index rlb of the people flow is as follows:
calculating the standard deviation RC and the average value of the people flow
If the average value of the people flow is less than or equal to the flow threshold value, and the standard deviation RC of the people flow is less than or equal to the standard deviation threshold value, rlb =0.8;
if the average value of the people flow is less than or equal to the flow threshold value, and the standard deviation RC of the people flow is more than the standard deviation threshold value, rlb =0.6;
if the average value of the people flow is greater than the flow threshold value, and the standard deviation RC of the people flow is greater than the standard deviation threshold value, rlb =0.4;
if the average value of the people flow is greater than the flow threshold, and the standard deviation RC of the people flow is less than or equal to the standard deviation threshold, rlb =0.2.
6. The artificial intelligence based scenic spot guiding element plan generating system of claim 5, wherein: the calculation expression of the standard deviation RC of the flow of people is as follows:
where i= {1, 2, 3,..n }, n represents the number of sampling time points, n is a positive integer, and RL i Representing the flow of people at the ith sampling time point,is the average of the people flow.
7. The artificial intelligence based scenic spot guiding element plan generating system of claim 6, wherein: the calculation expression of the per-person tour time length ratio is as follows:
in the formula, cavg is the people's average tour time length of the scenic spot in the scenic spot operation time, and yc is the scenic spot operation time length.
8. The artificial intelligence based scenic spot guide element plan generating system of claim 7, wherein: the calculation expression of the economic benefit coefficient is as follows:
in the formula, whc is the maintenance cost of the scenic spot, rs is the number of tourists of the scenic spot, rxf is the average consumption of people, xfs is the consumption coefficient between industries, and cz is the industrial production value.
9. The artificial intelligence based scenic spot guiding element plan generating system of claim 1, wherein: the scenic spot highlighting module is used for carrying out highlighting processing on each scenic spot according to the ranking coefficient based on the view highlighting technology, and comprises the following steps:
according to the ranking coefficient of the scenic spots, the identification of the scenic spots is subjected to enlargement or reduction treatment;
adjusting the identification brightness of the scenic spots according to the ranking coefficients of the scenic spots;
and applying light effects of different colors for the marks of different sceneries according to the ranking coefficients of the sceneries.
10. The scenic spot guide element plan generating method based on artificial intelligence is characterized by comprising the following steps of: the generation method comprises the following steps:
the method comprises the steps of obtaining map data of scenic spots from a geospatial data source, analyzing the scenic spots through image processing and computer vision technology, identifying guide elements, storing identification results of the guide elements in a database, generating a scenic spot plane guide map based on a plane map generating technology according to map data of the scenic spots, guide element database and personalized requirements of users, periodically obtaining multi-source data of all the scenic spots, generating ranking coefficients for all the scenic spots according to the multi-source data, updating ranks of all the scenic spots in the ranking area of the plane guide map, performing highlighting processing on all the scenic spots according to the ranking coefficients based on a view highlighting technology, displaying the plane guide map, the ranks of the scenic spots and scenic spot identifications subjected to highlighting processing in the plane guide map, monitoring real-time changes of the scenic spots and updating the guide element database, taking the display positions as positions of tourists and using pattern marks on the plane guide map, and planning a walk path for the tourists after the tourists determine the scenic spots and tourist preferences needing to go.
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