Museum guiding method and system based on indoor positioning technology

Abstract

The invention provides a museum guide method and system based on an indoor positioning technology, and relates to the technical field of intelligent guide, and the method comprises the steps: obtaining tourist basic data and tourist positioning data; based on the tourist positioning data, calculating tourist movement conditions in real time by using an indoor positioning technology to obtain positioning prediction data; analyzing the tourist basic data by utilizing a retrieval enhancement generation model to obtain commentary data; and based on the positioning prediction data, adjusting the commentary data to obtain museum navigation data, and completing museum navigation. According to the invention, the problems of lack of guide experience, poor freedom and less extensibility of related cultural relics and knowledge when tourists autonomously visit the museum are solved.

Description

Technical Field

[0001] This specification relates to the field of intelligent tour guide technology, and in particular to a museum tour guide method and system based on indoor positioning technology. Background Art

[0002] Current problems with the use of commentary on some museum collections include: (1) a monotonous format. Differences in visitor preferences, age groups, gender, and even region can affect the effectiveness of collection commentary in the guided tour. Most commentary employs a fixed narrative style, lacking individuality and diversity, which can be tedious for visitors and hinders the commentary's inherent role in conveying information about the collection and connecting the past and present. (2) Limited by the collection itself, the amount of information provided is insufficient. Due to the museum's curatorial needs and objective constraints, a small number of "star exhibits" may receive more attention than other exhibits. Accordingly, in the traditional guidebook creation process, the commentary for these small number of "star exhibits" is often more detailed, striving to provide a more complete visitor experience. However, due to issues with their researchability and historical value, as well as the museum's own objective conditions, the commentary for some exhibits may be quite brief, providing only basic historical and background information without delving into their cultural, artistic, or scientific value, thus affecting the visitor's experience. (3) Lack of interaction with visitors. Traditional museum guidebooks are often one-way, unable to adapt in real time to audience reactions and interests, limiting their sense of engagement. Due to time constraints and other objective factors, many visitors may not be able to fully hear the introduction to each collection, significantly impacting their visitor experience. Traditional guidebooks, due to their one-way design, struggle to address this issue. Summary of the Invention

[0003] In response to the above-mentioned deficiencies in the prior art, the present invention provides a museum guiding method and system based on indoor positioning technology, which solves the problems of lack of guided experience, poor freedom, and limited extensibility of relevant cultural relics knowledge when tourists visit museums independently.

[0004] In order to achieve the above-mentioned purpose, the technical solution adopted by the present invention is: a museum tour guide method and system based on indoor positioning technology, comprising: S1: Obtain tourist basic data and tourist location data; S2: Based on the tourist positioning data, use indoor positioning technology to calculate the tourist movement situation in real time to obtain positioning prediction data; S3: Analyze the basic data of tourists using the retrieval enhancement generation model to obtain commentary data; S4: Based on the positioning prediction data, the commentary data is adjusted to obtain museum guide data, thereby completing the museum guide.

[0005] The beneficial effects of the present invention are: a museum tour guide method and system based on indoor positioning technology. (1) By utilizing a retrieval-enhanced generation model and precise indoor positioning, the system can sense the location of visitors and, in combination with factors such as their age, interests, and cultural background, generate explanations that are more tailored to their individual needs in real time, thereby improving the interactive experience and greatly reducing manual reliance. (2) By utilizing real-time indoor positioning technology, the system can obtain information on the trajectory of visitors' movements indoors, flexibly adjust the explanations, and enhance the audience's sense of immersion and interactivity. (3) Without the need for large-scale replacement of hardware equipment, the system has higher scalability and flexibility.

[0006] Furthermore, the S2 includes: Based on the visitor positioning data, indoor positioning technology is used to calculate the visitor's movement in real time to obtain position update data and acceleration data; Normalizing and error-correcting the acceleration data to obtain acceleration-corrected data; Predicting the position update data using the acceleration correction data to obtain initial positioning prediction data; The initial positioning prediction data is corrected based on the state transfer matrix and the measurement noise matrix to obtain positioning prediction data.

[0007] Furthermore, the expression of the location update data is: ; in, express The horizontal axis of tourists at the time, express The horizontal axis of tourists at the time, Indicates from Time has come The distance moved at any moment, express Time direction, express The vertical coordinate of tourists at the moment.

[0008] Furthermore, the expression of the acceleration correction data is: ; ; ; in, represents the normalized acceleration, represents the lateral acceleration, represents the longitudinal acceleration, Represents the acceleration influence vector in the horizontal and vertical coordinate systems, Represents the rotation matrix from the navigation coordinate system to the horizontal and vertical coordinate systems, Represents the acceleration influence vector in the navigation coordinate system, Indicates acceleration correction data.

[0009] Furthermore, the expression of the state transfer matrix is: ; in, represents the state transition matrix, Indicates from Time has come The distance moved at any moment, express Time direction; The expression of the measurement noise matrix is: ; in, represents the measurement noise matrix, represents the measurement noise variance in the east direction, represents the measurement noise variance in the north direction, Represents the measurement noise variance of the heading angle.

[0010] Furthermore, the S3 includes: Inputting the cultural relic corpus and the basic tourist data into the retrieval enhancement generation model to obtain initial commentary data and corresponding preference weights; The initial commentary data is sorted from high to low according to preference weight to obtain commentary data.

[0011] Using the retrieval-enhanced generative model can effectively suppress the illusion of large models, be closer to the museum scene, and meet the higher requirements for text accuracy in the museum scene.

[0012] A museum guide system based on indoor positioning technology, comprising: Acquisition module, used to obtain basic data and location data of tourists; A positioning module is used to calculate the movement of tourists in real time based on the tourist positioning data using indoor positioning technology to obtain positioning prediction data; A commentary generating module is used to analyze the basic data of tourists by using a search-enhanced generation model to obtain commentary data; The navigation module is used to adjust the commentary data based on the positioning prediction data to obtain museum navigation data and complete the museum navigation. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] This specification will be further described in the form of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. These embodiments are not limiting, and in these embodiments, like numbers represent like structures, wherein: Figure 1 is a module diagram of a museum guide system based on indoor positioning technology according to some embodiments of this specification; Figure 2 This is an exemplary flow chart of a museum tour method based on indoor positioning technology according to some embodiments of this specification. DETAILED DESCRIPTION

[0014] The specific embodiments of the present invention are described below to facilitate understanding of the present invention by those skilled in the art. However, it should be clear that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, as long as various changes are within the spirit and scope of the present invention as defined and determined by the appended claims, these changes are obvious, and all inventions and creations utilizing the concepts of the present invention are protected.

[0015] Example 1 Figure 1 This is a module diagram of a museum guide system based on indoor positioning technology according to some embodiments of this specification.

[0016] In some embodiments, the museum tour guide system based on indoor positioning technology may include an acquisition module, a positioning module, a commentary generation module, and a tour guide module.

[0017] The acquisition module is used to obtain basic data and location data of tourists.

[0018] The positioning module is used to calculate the movement of tourists in real time based on the tourist positioning data using indoor positioning technology to obtain positioning prediction data.

[0019] The commentary generating module is used to analyze the basic data of tourists by using the retrieval enhancement generation model to obtain commentary data.

[0020] The navigation module is used to adjust the commentary data based on the positioning prediction data to obtain museum navigation data and complete the museum navigation.

[0021] In some embodiments, a museum navigation system based on indoor positioning technology can also utilize a positioning module to determine the flow of visitors to a specific section of the museum in real time. This information can be analyzed to generate more detailed positioning predictions, which can then be used to inform curatorial decisions. For example, positioning predictions can be used for guidance during emergencies. For example, in the event of an emergency evacuation, real-time audio guidance can be used to guide users calmly and efficiently find an emergency exit.

[0022] In some embodiments, a museum guide system based on indoor positioning technology can be used to execute a museum guide method based on indoor positioning technology, including S1: obtaining basic data of tourists and tourist positioning data; S2: based on the tourist positioning data, using indoor positioning technology to calculate the movement of tourists in real time to obtain positioning prediction data; S3: using a retrieval enhanced generation model to analyze the basic data of tourists to obtain commentary data; S4: based on the positioning prediction data, adjusting the commentary data to obtain museum guide data and complete the museum guide.

[0023] In some embodiments of this specification, the processor utilizes a museum tour guide system based on indoor positioning technology to execute a museum tour guide method based on indoor positioning technology. In this way, (1) the retrieval enhancement generation model and indoor precise positioning can be used to perceive the location of visitors, and based on factors such as their age, interests, and cultural background, to generate explanation content that is more tailored to their individual needs in real time, thereby improving the interactive experience and greatly reducing manual dependence. (2) Real-time indoor positioning technology is used to obtain information on the trajectory of visitors' movements in the indoor location, and the commentary can be flexibly adjusted to enhance the audience's immersion and interactivity. (3) There is no need to replace hardware equipment on a large scale, and the system has higher scalability and flexibility.

[0024] Example 2 Figure 2 This is an exemplary flow chart of a museum tour method based on indoor positioning technology according to some embodiments of this specification. Figure 2 As shown, the process includes the following steps. In some embodiments, the process can be executed by a processor.

[0025] S1: Obtain tourist basic data and tourist location data.

[0026] Tourist basic data is data that reflects basic information about tourists. For example, tourist basic data may include age, interests, cultural background, etc.

[0027] In some embodiments, the processor may obtain basic visitor data through the client.

[0028] Visitor location data is data that reflects the current location of visitors.

[0029] In some embodiments, the processor can utilize Bluetooth indoor high-precision positioning technology to precisely locate objects or people in indoor environments using Bluetooth signals. Bluetooth beacons are deployed indoors and periodically transmit signals. For example, a mobile device (such as a smartphone) receives these signals and estimates the distance to the beacon using signal strength (RSSI). Using triangulation, the device's location is calculated based on multiple received beacon signals. Bluetooth 5.1 introduces a direction detection feature that provides even higher positioning accuracy. Ultra-wideband (UWB) technology combined with Bluetooth can achieve centimeter-level positioning accuracy. For example, the processor can implement AOA positioning technology based on Bluetooth indoor high-precision positioning technology to analyze visitor locations and generate visitor location data. For example, the processor can obtain location information from an AOA base station at a fixed frequency. The device obtains an ID from the Bluetooth base station, which then transmits the ID and device location information to a central server. The server then uses a discrimination algorithm to calculate the device's current status, providing information such as approaching exhibit A, approaching exhibit A, or viewing exhibit A.

[0030] S2: Based on the tourist positioning data, the indoor positioning technology is used to calculate the tourist movement status in real time to obtain positioning prediction data.

[0031] Positioning prediction data is data that predicts the movement of visitors. For example, positioning prediction data may include states such as approaching exhibit a, leaving exhibit a, and viewing exhibit a.

[0032] In some embodiments, the processor can implement S2 based on the following steps: based on the tourist positioning data, use indoor positioning technology to calculate the tourist movement status in real time to obtain position update data and acceleration data; normalize and error correct the acceleration data to obtain acceleration correction data; use the acceleration correction data to predict the position update data to obtain initial positioning prediction data; correct the initial positioning prediction data based on the state transition matrix and the measurement noise matrix to obtain positioning prediction data.

[0033] Location update data is data that reflects the real-time location of visitors.

[0034] Acceleration data is data that reflects the acceleration of the visitor's current movement.

[0035] In some embodiments, the expression of the location update data may be: ; in, express The horizontal axis of tourists at the time, express The horizontal axis of tourists at the time, Indicates from Time has come The distance moved at any moment, express Time direction, express The vertical coordinate of tourists at the moment.

[0036] The acceleration correction data is data for correcting the acquired acceleration.

[0037] In some embodiments, the acceleration correction data may be expressed as: ; ; ; in, represents the normalized acceleration, represents the lateral acceleration, represents the longitudinal acceleration, Represents the acceleration influence vector in the horizontal and vertical coordinate systems, Represents the rotation matrix from the navigation coordinate system to the horizontal and vertical coordinate systems, Represents the acceleration influence vector in the navigation coordinate system, Indicates acceleration correction data.

[0038] The initial positioning prediction data is the tourist movement information predicted by the acceleration correction data.

[0039] The state transition matrix is a matrix used to describe the position update situation.

[0040] The measurement noise matrix is a matrix used to describe the measurement noise situation.

[0041] In some embodiments, the expression of the state transition matrix may be: ; in, represents the state transition matrix, Indicates from Time has come The distance moved at any moment, express Time direction.

[0042] In some embodiments, the expression of the measurement noise matrix may be: ; in, represents the measurement noise matrix, represents the measurement noise variance in the east direction, represents the measurement noise variance in the north direction, Represents the measurement noise variance of the heading angle.

[0043] S3: Analyze the basic data of tourists using the retrieval enhancement generation model to obtain commentary data.

[0044] The Retrieval-Augmented Generation model (RAG model) is a large language model used to generate commentary.

[0045] The commentary data is the cultural relics-related language data broadcast in real time based on the tourists' movement time.

[0046] In some embodiments, the processor can implement S3 based on the following steps: inputting the cultural relics corpus and the basic data of the tourists into the retrieval enhancement generation model to obtain initial commentary data and corresponding preference weights; sorting the initial commentary data from high to low according to the preference weights to obtain commentary data.

[0047] Cultural relic corpus refers to the textual materials related to all cultural relics in a museum. For example, cultural relic corpus can include historical background, artistic style, archaeological discoveries, and other related information; basic questions and answers such as venue introductions, opening and closing times, visitor guides, and guided tours; and explanatory content such as explanations of museum and cultural relic terms and craftsmanship, combined with knowledge resources such as the Encyclopedia of Chinese and Baidu Encyclopedia, as well as personalized style templates.

[0048] The initial commentary data is the commentary data output by the retrieval enhancement generation model.

[0049] The preference weight is the weight that reflects the tourists' interest in the commentary.

[0050] In some embodiments, the processor can retrieve cultural relic corpus from a knowledge base containing extensive cultural relic information, analyze the cultural relic corpus and basic tourist data using a retrieval-enhanced generation model, and obtain initial commentary data and corresponding preference weights.

[0051] In some embodiments, the processor can obtain basic user information from the client and use indoor precise positioning technology to obtain visitor location information. A retrieval-enhanced generation model is used to generate text, including a logic judgment layer that receives basic visitor information, selects an appropriate tour style, and interacts with the visitor location information from the client in real time to obtain preference weights; a text generation layer that receives basic exhibit information and text for different tour styles through retrieval-enhanced technology, receives the preference weights generated by the logic judgment layer, and ultimately generates corresponding commentary as commentary data.

[0052] S4: Based on the positioning prediction data, the commentary data is adjusted to obtain museum guide data, thereby completing the museum guide.

[0053] In some embodiments, the processor can use positioning prediction data to determine the current and future browsing behavior of tourists, adjust the commentary, obtain museum tour data, and transmit the final museum tour data back to the client to complete the museum tour.

[0054] In some embodiments of this specification, a museum tour method and system based on indoor positioning technology is provided. (1) By utilizing a retrieval-enhanced generation model and precise indoor positioning, the location of visitors can be sensed, and combined with factors such as their age, interests, and cultural background, explanation content that is more tailored to individual needs can be generated in real time, thereby improving the interactive experience and greatly reducing manual dependence. (2) By utilizing real-time indoor positioning technology, the trajectory information of visitors' movements in the indoor location can be obtained, and the commentary can be flexibly adjusted to enhance the audience's immersion and interactivity. (3) There is no need to replace hardware equipment on a large scale, and the system has higher scalability and flexibility.

Claims

1. A museum tour guide method based on indoor positioning technology, characterized in that: include: S1: Obtain tourist basic data and tourist location data; S2: Based on the tourist positioning data, use indoor positioning technology to calculate the tourist movement situation in real time to obtain positioning prediction data; S3: Analyze the basic data of tourists using the retrieval enhancement generation model to obtain commentary data; S4: Based on the positioning prediction data, the commentary data is adjusted to obtain museum guide data, thereby completing the museum guide.

2. The museum tour guide method based on indoor positioning technology according to claim 1, characterized in that: The S2 includes: Based on the visitor positioning data, indoor positioning technology is used to calculate the visitor's movement in real time to obtain position update data and acceleration data; Normalizing and error-correcting the acceleration data to obtain acceleration-corrected data; Predicting the position update data using the acceleration correction data to obtain initial positioning prediction data; The initial positioning prediction data is corrected based on the state transfer matrix and the measurement noise matrix to obtain positioning prediction data.

3. The museum tour guide method based on indoor positioning technology according to claim 2, characterized in that: The expression of the position update data is: ； in, express The horizontal axis of tourists at the time, express The horizontal axis of tourists at the time, Indicates from Time has come The distance moved at any moment, express Time direction, express The vertical coordinate of tourists at the moment.

4. The museum tour guide method based on indoor positioning technology according to claim 2, characterized in that: The expression of the acceleration correction data is: ； ； ； in, represents the normalized acceleration, represents the lateral acceleration, represents the longitudinal acceleration, Represents the acceleration influence vector in the horizontal and vertical coordinate systems, Represents the rotation matrix from the navigation coordinate system to the horizontal and vertical coordinate systems, Represents the acceleration influence vector in the navigation coordinate system, Indicates acceleration correction data.

5. The museum tour guide method based on indoor positioning technology according to claim 2, characterized in that: The expression of the state transfer matrix is: ； in, represents the state transition matrix, Indicates from Time has come The distance moved at any moment, express Time direction; The expression of the measurement noise matrix is: ； in, represents the measurement noise matrix, represents the measurement noise variance in the east direction, represents the measurement noise variance in the north direction, Represents the measurement noise variance of the heading angle.

6. The museum tour guide method based on indoor positioning technology according to claim 1, characterized in that: The S3 includes: Inputting the cultural relic corpus and the basic tourist data into the retrieval enhancement generation model to obtain initial commentary data and corresponding preference weights; The initial commentary data is sorted from high to low according to preference weight to obtain commentary data.

7. A museum tour guide system based on indoor positioning technology, used to execute the museum tour guide method based on indoor positioning technology according to any one of claims 1 to 6, characterized in that: include: Acquisition module, used to obtain basic data and location data of tourists; A positioning module is used to calculate the movement of tourists in real time based on the tourist positioning data using indoor positioning technology to obtain positioning prediction data; A commentary generating module is used to analyze the basic data of tourists by using a search-enhanced generation model to obtain commentary data; The navigation module is used to adjust the commentary data based on the positioning prediction data to obtain museum navigation data and complete the museum navigation.

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