Smart tourism service system based on Internet of Things

Abstract

The invention discloses a smart tourism service system based on the Internet of Things, relates to the technical field of tourism services, and is used for solving the problems that the intelligent degree of tourism services is low and the tourism experience of users is reduced due to the fact that existing smart tourism services cannot perform active services based on the real-time states of tourists. Comprising a tourist behavior analysis module, an intelligent service module and an operation module. Behavior data of tourists are collected in real time through the tourist behavior analysis module and analyzed, the operation module provides an operation interface for the tourists, and interaction with scenic spot information and service providers is carried out through intelligent mobile equipment. And the intelligent service module actively provides personalized services based on the real-time states of the tourists, so that the sightseeing experience of the tourists is effectively improved, and the safety and comfort of the tourists in the scenic spot are guaranteed. Meanwhile, the system can help a scenic spot manager to better grasp the tourist flow condition, improve the management efficiency and reduce congestion and potential risks.

Description

Technical Field

[0001] The present invention relates to the technical field of tourism services, and in particular to a smart tourism service system based on the Internet of Things. Background Art

[0002] Smart tourism services, also known as intelligent tourism services, use modern information technologies such as cloud computing and the Internet of Things to actively perceive and integrate information on tourism resources, tourism economy, tourism activities, and tourists through the Internet / mobile Internet and portable terminal Internet devices. They provide users with intelligent tourism services, thereby upgrading and transforming the traditional tourism industry and improving the quality and efficiency of tourism services.

[0003] However, the existing smart tourism services are unable to provide proactive services based on tourists' real-time status, resulting in a low level of intelligence in tourism services, which in turn reduces users' travel experience. Summary of the invention

[0004] The purpose of the present invention is to solve the problem that the existing smart tourism services cannot provide active services based on the real-time status of tourists, resulting in a low level of intelligence in tourism services, thereby reducing the tourism experience of users, and provide a smart tourism service system based on the Internet of Things. The system can integrate a variety of Internet of Things devices and technologies, realize intelligent interaction between tourists, scenic spots, and service providers, provide personalized and real-time tourism services, thereby improving tourism experience and management efficiency.

[0005] The purpose of the present invention can be achieved by the following technical solutions: A smart tourism service system based on the Internet of Things, including a tourist behavior analysis module and an intelligent service module, wherein the tourist behavior analysis module is used to collect and analyze the behavior data of tourists in real time, and the specific analysis process is as follows:

[0006] When a tourist scans the QR code for entering the scenic area through a smart mobile device, the tourist is judged to have entered the scenic area and the authorization permission of the tourist's smart mobile device is obtained. After obtaining the permission, the tourist's real-time location data, the time the tourist entered the scenic area, the moving distance S, and the stay time t are obtained; according to the preset tourist physical formula Output the tourist's physical fitness index P; where α1, β1 and γ1 are weight factors, Bn and Xn are the average moving step frequency and average heart rate respectively; time is the time taken, which is equal to the time of entering the scenic area minus the stay time; the physical fitness index corresponding to 10 minutes of the tourist entering the scenic area is marked as the maximum physical fitness index Pmax; the maximum physical fitness index Pmax and the real-time physical fitness index of the tourist are sent to the intelligent service module;

[0007] The intelligent service module is used to receive the maximum physical strength index Pmax and the real-time physical strength index of the tourists and provide intelligent services to the tourists. Specifically, when the real-time physical strength index P of the tourists is less than half of the maximum physical strength index Pmax of the tourists, that is, P<1 / 2Pmax, then plan signal 1, plan signal 2 and plan signal 3 are generated and sent to the tourists' smart mobile devices; when the tourists receive plan signal 1, plan signal 2 and plan signal 3 through the smart mobile devices, the corresponding plans 1, 2 and 3 are executed.

[0008] As a preferred implementation of the present invention, the process of the intelligent service module executing solution 1 is:

[0009] Get the nearest resting place between the scenic spot and the tourist location, and plan several paths based on the tourist location and the nearest resting place. Output the path evaluation function F, α2, β2 and γ2 are all proportional weight factors, λ, δ and K are the weights corresponding to the tourists' moving distance S, path flatness W and number of tourists Nsxt respectively; mark the path with the smallest path evaluation function as the best path, send the best path to the tourists' corresponding smart mobile devices, and navigate for the tourists according to the best path.

[0010] As a preferred embodiment of the present invention, the specific calculation process of the path flatness W is as follows: the path is divided into a number of sub-segments according to the order of starting and ending and marked as Lj, j = 1, 2, ..., m1, where m1 is the total number of sub-segments, and the value is a positive integer; the slope and the number of steps of each sub-segment are obtained and their values ​​are marked as PDj and JTj respectively; the slope corresponding to each sub-segment is sorted according to the order, and the size between two adjacent slopes is compared. If the slope in the first order is smaller than the slope in the second order, the difference between the two is calculated and marked as the ascending slope value. If the slope in the first order is equal to the slope in the second order, the value of one of the slopes is multiplied by a preset dimension slope factor to obtain the dimension slope value; If the slope before sorting is greater than the slope after sorting, the difference between the two is calculated and marked as the descending slope value; all the ascending slope values, dimension slope values ​​and descending slope values ​​are summed up to obtain the total ascending slope value, the total dimension slope value and the total descending slope value, and the values ​​of the total ascending slope value, the total dimension slope value and the total descending slope value are marked as SP1, WP2 and JP3 respectively; the weight factors corresponding to the total ascending slope value, the total dimension slope value and the total descending slope value are set to es1, es2 and es3 respectively; and es1>es2>es3>0, and the value is a custom setting, such as 0.6, 0.4 and 0.35, whichever meets the relationship; the slope neighbor value PL of the path is obtained by using the formula PL=SP1×es1+WP2×es2-JP3×es3;

[0011] The slope, number of steps and slope neighbor value of each sub-section are normalized and substituted into the flatness analysis model. The path flatness W corresponding to the output path is obtained, where PDmax is the maximum slope among all sub-segments, JTmax is the maximum number of steps among all sub-segments, and μ1, μ2, μ3, u4 and μ5 are all preset weight factors.

[0012] As a preferred implementation of the present invention, the process of the intelligent service module executing Solution 2 is: obtaining the real-time location of the tourist, matching the corresponding idle special car in the corresponding scenic spot, and planning the optimal route for the special car based on the real-time location of the tourist.

[0013] As a preferred embodiment of the present invention, the process of the intelligent service module executing scheme three is: sending a product list to the tourist's smart terminal, the tourist browses the product list through the smart mobile device and selects the required products, after the tourist places an order, the order information is sent to the nearest scenic spot distribution center or store, and the required products in the order information are delivered.

[0014] As a preferred embodiment of the present invention, the intelligent service module is also used to identify visitor behavior in real time and compare it with normal behavior to generate predictive alarms and send alarm information to security management personnel in real time.

[0015] Compared with the prior art, the present invention has the following beneficial effects:

[0016] 1. The present invention uses the scenic area information collection module to achieve real-time monitoring and uploading of information such as the environment, roads, and tourist flow in the scenic area, ensuring the accuracy and timeliness of the data; the operation module provides a convenient interactive platform for tourists and managers, allowing tourists to obtain scenic area information in real time, query scenic spots and facilities, and interact with service providers; managers can effectively monitor the status of IoT devices and data accuracy. The advantage of this system is that it improves the experience of tourists, enhances the efficiency of scenic area management, and provides a solid foundation for the comprehensive construction of smart scenic areas.

[0017] 2. The present invention can realize comprehensive monitoring of tourist behavior and personalized service through tourist behavior analysis module and intelligent service module; the tourist behavior analysis module generates a scenic spot heat map, identifies crowded areas, and provides strong support for scenic spot management and tourists by collecting and analyzing data such as tourist movement distance, residence time, and physical index; the intelligent service module actively provides personalized services such as navigation, special car pick-up, and commodity delivery based on the real-time status of tourists, which effectively improves the tourists' sightseeing experience and ensures the safety and comfort of tourists in the scenic area; it also helps scenic area managers to better grasp the flow of tourists, improve management efficiency, and reduce congestion and potential risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The present invention will be further described below in conjunction with the accompanying drawings.

[0019] Figure 1 It is a schematic diagram of module connection of the present invention. DETAILED DESCRIPTION

[0020] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] It should be understood that the terms "include" and "comprising" used in the specification and claims of the present disclosure indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or collections thereof.

[0022] It should also be understood that the terms used in this disclosure are only for the purpose of describing specific embodiments and are not intended to limit the disclosure. As used in this disclosure and claims, the singular forms of "a", "an", and "the" are intended to include the plural forms unless the context clearly indicates otherwise. It should also be further understood that the term "and / or" used in this disclosure and claims refers to any combination of one or more of the associated listed items and all possible combinations, including these combinations.

[0023] See also Figure 1 As shown, a smart tourism service system based on the Internet of Things includes a scenic spot information collection module, a tourist behavior analysis module, an information data storage library, an intelligent service module and an operation module.

[0024] The scenic area information collection module uses IoT devices (such as sensors and cameras) to collect terrain and road information, environmental information, tourist flow, and equipment status data in the scenic area in real time, and upload the data to the information data repository; specifically: deploy a variety of sensors at key locations in the scenic area (such as temperature sensors that convert temperature changes into electrical signals, and transmit the collected temperature data in real time to the cloud for storage and analysis through wired or wireless networks, and the same applies to humidity sensors, light sensors, and gas sensors, etc.) to collect environmental data in real time, including temperature coefficient, humidity coefficient, light coefficient, and air coefficient; terrain and road information collects altitude information and location information through smart mobile devices, and then calculates terrain and road information based on altitude / unit distance (100m) = road flatness; HD cameras are deployed in major scenic spots, entrances and other areas, and by analyzing the HD videos shot by the HD cameras and counting the faces or human body contours in the video frames, the camera system can count the real-time number of tourists Nsxt in the shooting area, and then calculate the flow of tourists Vsxt and traffic conditions through time accumulation and calculation; the system also uploads the HD videos shot by the HD cameras and image information to the cloud for storage.

[0025] The operation module is used as the user interface. Visitors download, register accounts, and fill in basic personal information through smart mobile devices. Visitors enter the operation module through smart mobile devices. The operation module obtains data from the information data repository in real time and displays scenic area information on smart mobile devices. Visitors can query scenic spots and specific facilities information through the search engine of the operation module and interact with service providers. The information of the intelligent service module is also transmitted to visitors through the operation module to realize intelligent interaction between tourists, scenic spots, and service providers. Scenic area managers enter the management mode through operation module authentication to check whether the scenic area's IoT devices are working properly and whether the information collected by each device is accurate.

[0026] The tourist behavior analysis module collects tourist behavior data in real time through IoT devices (such as cameras, sensors, and smart mobile devices) in the scenic area, and uploads it to the information data repository for storage, including analyzing the tourist's moving distance S and stay time t (when the tourist's position is not detected to have changed, the time t=0 is accumulated, that is, t1=t, when the tourist's position is detected to have changed again t2=t, and so on); using IoT intelligent analysis technology, analyze tourists' regular behavior paths and crowded areas, specifically: when tourists use the operation module to scan the code to enter the scenic area, the tourists are judged to have entered the scenic area, and the authorization authority of the tourists' smart mobile devices is obtained. After obtaining the authorization, the tourists' real-time positioning data, the time of tourists entering the scenic area, and the number of operation module searches are obtained using the tourists' smart mobile devices. According to the preset tourist physical strength formula: Output the tourist's physical index P, where α1, β1 and γ1 are all weight factors, and their sizes are customized according to the tourist's gender and age. The weight factor corresponding to young and middle-aged men or women is the largest, such as α1, β1 and γ1 are 1.35, 1.2 and 1.17 respectively. e is a natural constant. From the time the tourist just enters the scenic area to 10 minutes after entering the scenic area, that is, 0-10 minutes of play, during this period of time, the tourist's physical index P is the largest. The tourist's physical index during this period is marked as the maximum physical index, that is, Pmax; the average heart rate Xn, average moving step frequency Bn, moving distance S and time used time=10min-t of the tourist in the 0-10min play can be obtained through the tourist's smart mobile device.

[0027] All tourists' path data are superimposed to generate a heat map of the scenic area. The areas where tourists concentrate their activities (hot spots) and the areas where fewer people visit are intuitively displayed; the tourist behavior path data at different time periods are analyzed to identify the peak visit periods of each scenic spot in the scenic area and derive the regular behavior path of tourists.

[0028] High-definition cameras installed at each scenic spot capture images, count faces or human body outlines in video frames to obtain the real-time number of tourists Nsxt at each scenic spot, analyze the real-time number of tourists Nsxt at each scenic spot, and calculate the moving speed V of tourists at the scenic spot (the moving speed V is obtained by dividing the moving distance S of the tourists by the time taken). If the moving speed V of all tourists at a certain scenic spot is less than the corresponding average speed of the tourists, and the number of tourists Nsxt belongs to the preset high-density interval corresponding to the scenic spot, the scenic spot is judged as a crowded area and provided for tourists to view, so that tourists can understand the degree of crowding of the scenic spot in real time.

[0029] The intelligent service module obtains the data from the information data repository and is responsible for providing real-time services to tourists based on the tourist information data. It proactively provides personalized services and reminders to tourists by monitoring tourists' behaviors, physical conditions and other data in real time, rather than passively waiting for tourists to make requests. The following is a specific manifestation of the intelligent service module as an active service: The intelligent service module continuously analyzes the data by obtaining the data from the information data repository based on the tourists' behavior data, physical conditions, location information, etc. When it is detected that the tourist's physical index P is less than 50% of the tourist's maximum physical index Pmax, it is determined that the tourist needs to rest and generates multiple plans;

[0030] Solution 1: Navigation and rest. When tourists accept this solution through smart mobile devices, they start to navigate to the nearest resting place according to the best path. Specifically, they query the nearest resting place in the scenic area through the data information of the scenic area, and then plan several paths according to the location of the tourists. The best path is selected through the path evaluation function F. The formula is:

[0031] Output the path evaluation function F, where α2, β2 and γ2 are proportional weight factors, W is the path flatness; λ, δ and K are the nonlinear weights of the path corresponding to the tourist's moving distance S, path flatness W and the number of tourists Nsxt in the formula, and their sizes are custom settings. The smaller the value of F, the best path. The path with the smallest path evaluation function is marked as the best path, and the best path is pushed to the operation module for tourists to choose. The specific calculation process of the path flatness is as follows: divide the path into several sub-segments according to the order of starting and ending and mark them as Lj, j = 1, 2, ..., m1, where m1 is the total number of sub-segments and is a positive integer; obtain the slope and number of steps of each sub-segment and mark their values ​​as PDj and JTj respectively; sort the slope corresponding to each sub-segment according to the order, compare the size of the two adjacent slopes, if the slope in the first order is smaller than the slope in the second order, calculate the difference between the two and mark it as the ascending slope value, if the slope in the first order is equal to the slope in the second order, then multiply the value of one of the slopes by the preset The dimension slope factor is used to obtain the dimension slope value; if the slope before sorting is greater than the slope after sorting, the difference between the two is calculated and marked as the descending slope value; all the ascending slope values, dimension slope values ​​and descending slope values ​​are summed up to obtain the total ascending slope value, the total dimension slope value and the total descending slope value, and the values ​​of the total ascending slope value, the total dimension slope value and the total descending slope value are marked as SP1, WP2 and JP3 respectively; the weight factors corresponding to the total ascending slope value, the total dimension slope value and the total descending slope value are set to es1, es2 and es3 respectively; and es1>es2>es3>0, and its value is a custom setting, such as 0.6, 0.4 and 0.35, which meet the relationship; use the formula

[0032] PL = SP1 × es1 + WP2 × es2 - JP3 × es3 to obtain the slope value PL of the path;

[0033] The slope, number of steps and slope neighbor value of each sub-section are normalized and substituted into the flatness analysis model. The path flatness W corresponding to the output path is obtained, where PDmax is the maximum slope among all sub-segments, and JTmax is the maximum number of steps among all sub-segments; μ1, μ2, μ3, u4, and μ5 are all preset weight factors, and their sizes are custom values, such as 1.2, 1.4, 0.5, 0.3, and 1.5.

[0034] Solution 2: Special car pick-up. When tourists accept this solution through smart mobile devices, the real-time location of tourists is obtained, and the corresponding idle special cars in the corresponding scenic spots are matched. According to the real-time location of tourists, the optimal path is planned for the special car, avoiding crowded areas, ensuring that the special car quickly reaches the location of tourists and picks them up to the designated location of tourists. The specific process of planning the optimal path is: according to the real-time location of tourists, the location is obtained, and the location is matched with the corresponding location of the special car to several driving paths, and the total distance, number of pedestrians and number of turns corresponding to each driving path are identified; the total distance, number of pedestrians and number of turns are normalized and the normalized values ​​of the three are marked as LF1, LF2 and LF3 respectively; the formula XS=100-(LF1×0.7+LF2×0.3+LF3×0.3) is used to output the path merit of the driving path, and the driving path with the largest path merit is marked as the optimal path.

[0035] Solution 3: Product delivery: If tourists accept this solution through smart mobile devices, they will use the service provider to provide product delivery services under the reminder of the smart service module. Specifically, the product list is sent to the tourist's smart terminal, and the tourist browses the product list (such as food and beverages) through the smart mobile device and selects the required products. After the tourist places an order, the order information is sent to the nearest scenic spot distribution center or store, and the goods are delivered according to the tourist's location.

[0036] All of the above solutions are implemented on tourists' smart mobile devices through the operation module. Tourists can choose according to their own intentions, or accept none of them. By analyzing service events and process records, the system can evaluate the response speed, execution efficiency and success rate of each service, so as to optimize it. Based on the interaction records, the system gradually learns tourists' preferences and adjusts future service suggestions to make them more in line with tourists' needs and improve the overall service quality.

[0037] The intelligent service module is also used to identify tourist behavior in real time and compare it with normal behavior: for example, if the number of tourists Nsxt in a certain area suddenly increases in a short period of time, and grows to a normal value far greater than the number of tourists Nsxt within two minutes, and the flow of tourists Vsxt remains basically unchanged; or if the flow of tourists Vsxt in a certain area suddenly increases in a short period of time, and the flow of tourists is more than twice the normal level, moving in one direction; it is determined as abnormal group behavior, and a predictive alarm is generated. The alarm information is sent to the security management personnel in real time through the operation module, including time and location information. In this way, the system can actively remind the management personnel of potential safety issues through the operation module, restrict tourists from entering specific areas or adjust the flow of people in the scenic area to ensure the safety of tourists.

[0038] The intelligent service module is also used to obtain tourists' own data in real time to determine whether it is normal: the heart rate data of tourists is monitored in real time through intelligent mobile devices, and the cadence data is collected. The device will continuously record the number of heartbeats and cadences per minute. Based on the historical data and general health status of tourists, their normal heart rate and cadence range are established. Under normal circumstances, the heart rate may be between 60-120BPM, and the cadence may be between 60-120 steps / minute. When the heart rate is monitored to suddenly exceed 180BPM or fall below 40BPM, and the cadence suddenly rises or falls sharply, it is judged that the tourist's physiology is abnormal. Immediately perform secondary verification on the abnormal data to eliminate the possibility of equipment failure or data transmission error. After the verification is passed, the system will immediately generate an alarm, and prompt the tourist's physical abnormality through the operation module, or the scenic spot staff will call the tourist to remind the tourist to rest, whether medical help is needed, or directly contact the emergency service, and at the same time remind the management staff to pay attention. If the tourist has not responded, further measures will be automatically taken to generate an emergency signal. The scenic spot emergency personnel will automatically guide the emergency personnel to the location of the tourist according to the emergency signal to ensure that they arrive at the scene in the shortest time. At the same time, the intelligent service module manages and records all emergency events and emergency processes and uploads them to the information data repository to ensure the quality and traceability of the service.

[0039] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A smart tourism service system based on the Internet of Things, including a tourist behavior analysis module and an intelligent service module, characterized in that: The tourist behavior analysis module is used to collect and analyze the tourist behavior data in real time. The specific analysis process is as follows: When a tourist scans the QR code for entering the scenic area through a smart mobile device, the tourist is judged to have entered the scenic area and the authorization permission of the tourist's smart mobile device is obtained. After obtaining the permission, the tourist's real-time location data, the time the tourist entered the scenic area, the moving distance S, and the stay time t are obtained; according to the preset tourist physical formula Output the tourist's physical fitness index P; α1, β1 and γ1 are weight factors, Bn and Xn are the average moving step frequency and average heart rate respectively; time is the time taken, which is equal to the time of entering the scenic area minus the time of staying; The physical strength index of the tourist corresponding to ten minutes after entering the scenic spot is marked as the maximum physical strength index Pmax; the maximum physical strength index Pmax and the real-time physical strength index of the tourist are sent to the intelligent service module; The intelligent service module is used to receive the maximum physical strength index Pmax and the real-time physical strength index of the tourists and provide intelligent services to the tourists. Specifically, when the real-time physical strength index P of the tourists is less than half of the maximum physical strength index Pmax of the tourists, that is, P<1 / 2Pmax, then plan signal 1, plan signal 2 and plan signal 3 are generated and sent to the tourists' smart mobile devices; when the tourists receive plan signal 1, plan signal 2 and plan signal 3 through the smart mobile devices, the corresponding plans 1, 2 and 3 are executed.

2. According to claim 1, a smart tourism service system based on the Internet of Things is characterized in that: The process of the intelligent service module executing solution 1 is as follows: Get the nearest resting place between the scenic spot and the tourist location, and plan several paths based on the tourist location and the nearest resting place. Output the path evaluation function F, α2, β2 and γ2 are all proportional weight factors, λ, δ and K are the weights corresponding to the tourists' moving distance S, path flatness W and number of tourists Nsxt respectively; mark the path with the smallest path evaluation function as the best path, send the best path to the tourists' corresponding smart mobile devices, and navigate for the tourists according to the best path.

3. According to claim 2, a smart tourism service system based on the Internet of Things is characterized in that: The specific calculation process of the path flatness W is: The path is divided into several sub-segments according to the order of starting and ending, and the slope and number of steps of each sub-segment are obtained. The slopes corresponding to each sub-segment are sorted in order, and the size between two adjacent slopes is compared. If the slope in the front is smaller than the slope in the back, the difference between the two is calculated and marked as the ascending slope value. If the slope in the front is equal to the slope in the back, the value of one of the slopes is multiplied by the preset dimension slope factor to obtain the dimension slope value; if the slope in the front is greater than the slope in the back, the difference between the two is calculated and marked as the descending slope value; all the ascending slope values, dimension slope values ​​and descending slope values ​​are summed up to obtain the total ascending slope value, the total dimension slope value and the total descending slope value, and the total ascending slope value, the total dimension slope value and the total descending slope value are analyzed to obtain the slope neighbor value of the path, and the slope and the number of steps of each sub-segment and the slope neighbor value are normalized, and substituted into the flatness analysis model to output the path flatness corresponding to the path.

4. According to claim 2, a smart tourism service system based on the Internet of Things is characterized in that: The process of the intelligent service module executing the second solution is: obtaining the real-time location of tourists, matching the corresponding idle special cars in the corresponding scenic spots, and planning the optimal route for the special cars according to the real-time location of tourists.

5. According to the Internet of Things-based smart tourism service system of claim 2, it is characterized in that: The process of the intelligent service module executing scheme three is as follows: a product list is sent to the tourist's smart terminal, and the tourist browses the product list and selects the required products through the smart mobile device. After the tourist places an order, the order information is sent to the nearest scenic spot distribution center or store, and the required products in the order information are delivered.

6. The smart tourism service system based on the Internet of Things according to claim 2 is characterized in that: The intelligent service module is also used to identify visitor behavior in real time and compare it with normal behavior to generate predictive alerts and send alarm information to security managers in real time.

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