A method and system for constructing an industrial heritage digitization platform based on a Kano-QFD model and an ant colony algorithm

Abstract

The application provides a kind of industrial heritage digitization platform construction method and system based on Kano-QFD model and ant colony algorithm.The method comprises the following steps: step 1, requirement analysis stage: obtaining and converting user requirements;Step 2, spatial analysis stage: constructing heritage geographic model and planning guide path;Step 3, platform development stage: realize front and rear system and core function module;Step 4, test and iteration stage: verification optimization and form sustainable operation scheme.The method and system can deeply integrate the front digital technology, integrate heritage resources and user requirements, design immersive and narrative interactive experience, and establish an evolutionary, scalable and sustainable operation framework, so as to comprehensively, vividly and durably realize the digitization inheritance and public dissemination of industrial heritage value.

Description

Technical Field

[0001] This invention relates to the field of digital preservation technology for cultural heritage, and in particular to a method and system for constructing a digital platform for industrial heritage based on the Kano-QFD model and ant colony algorithm. Specifically, it relates to a method and system for constructing a digital platform for industrial heritage that integrates user needs analysis, spatial path optimization, and immersive interaction. Background Technology

[0002] Industrial heritage, as tangible witnesses to the progress of industrial civilization, carries significant historical memory, technological knowledge, social change, and cultural identity—values ​​spanning multiple dimensions. However, with the transformation of industrial structures and the acceleration of urban renewal, a large number of industrial heritage sites face challenges such as physical damage, functional loss, and weakened value perception, necessitating innovative approaches to their protection and inheritance. In recent years, digital technologies such as 3D scanning, the Internet of Things, artificial intelligence, virtual reality (VR), and augmented reality (AR) have provided new pathways for the recording, preservation, and representation of industrial heritage. These technologies not only enable high-precision digital modeling of the heritage itself and its environment but also support the fusion of multi-source data and interactive presentation, thereby overcoming the limitations of traditional protection methods in terms of space, time, and form of expression.

[0003] However, existing digital display platforms for industrial heritage still generally suffer from several key problems. At the content level, most systems primarily rely on one-way information transmission, such as static displays of two-dimensional text, images, and videos, lacking a systematic overview and in-depth interpretation of industrial processes, technological principles, spatial organization, and human stories. This results in the cultural connotations and technological characteristics of the heritage not being effectively conveyed. At the experience level, the interactive design of existing platforms is often simplistic, lacking immersion and narrative, failing to stimulate the exploration interest and emotional resonance of users, especially younger generations. At the technology integration level, the functional modules of the platform often lack organic linkage, and the geographical distribution and logical connections between heritage sites are not effectively integrated in the digital space, affecting the logical coherence and cognitive completeness of the visit. Furthermore, most systems struggle to continuously update content and iterate functions based on user behavior data and feedback after completion, resulting in a lack of sustainable operational models.

[0004] Therefore, there is an urgent need to build a new digital display system for industrial heritage. This system should be able to deeply integrate cutting-edge digital technologies, systematically integrate heritage resources and user needs, design immersive and narrative interactive experiences, and establish an evolving, scalable, and sustainable operating framework, thereby comprehensively, vividly, and sustainably realizing the digital inheritance and public dissemination of the value of industrial heritage. Summary of the Invention

[0005] The purpose of this invention is to address the problems of inaccurate demand analysis, disordered spatial organization, and insufficient interactive experience in existing technologies, and to realize the digital revitalization and sustainable dissemination of industrial heritage. This invention proposes a method and system for constructing a digital platform for industrial heritage based on the Kano-QFD model and ant colony algorithm.

[0006] This invention is achieved through the following technical solution: This invention proposes a method for constructing a digital platform for industrial heritage based on the Kano-QFD model and ant colony algorithm, the method comprising: Step 1, Requirements Analysis Phase: Obtain and transform user requirements; Step 2, Spatial Analysis Stage: Constructing a heritage geographical model and planning guided routes; Step 3, Platform Development Phase: Implement the front-end and back-end systems and core functional modules; Step 4, Testing and Iteration Phase: Verify optimization and develop a sustainable operation plan.

[0007] Furthermore, step 1 specifically includes: Step 1.1: Design a Kano model questionnaire targeting the functions of the industrial heritage digitization platform; Step 1.2: Distribute questionnaires through online social media, on-site heritage sites, and professional seminars; Step 1.3: Process and classify the recovered data based on the Kano model analysis method; Step 1.4: Calculate the Better-Worse coefficient for each functional item, sort them according to the difference between (Better coefficient - |Worse coefficient|), and determine the priority sequence for platform functional development; Step 1.5: Transform the above classification and priority analysis results into a specific list of platform functional modules, interface interaction logic, and visual design specification documents.

[0008] Furthermore, step 2 specifically includes: Step 2.1: Select the research object and obtain its precise latitude and longitude coordinates through a geographic information system to form a set of points; Step 2.2: The ant colony optimization algorithm is implemented using the MATLAB software platform to solve the optimal traversal path between multiple heritage points; the key parameters of the algorithm are set as follows: number of ants m=20, pheromone importance factor α=1, heuristic function importance factor β=5, and pheromone volatility coefficient ρ=0.1. Step 2.3: Introduce actual terrain slope data as a resistance factor to correct the Euclidean distance matrix between heritage points and generate a cost distance matrix; Step 2.4: Run the ant colony algorithm. After iterative convergence, output the optimal traversal path. At the same time, the algorithm generates a heat map of the resource concentration of heritage sites and visualizes the planned guide path.

[0009] Furthermore, step 3 specifically includes: Step 3.1: The front-end development adopts the WeChat Mini Program framework, which includes: an integrated map navigation module, a 3D model display module, and a VR real-scene roaming module; Step 3.2: The backend service is deployed on a cloud server and uses a relational database to store and manage three types of core data: heritage ontology data, user behavior data, and user feedback data; Step 3.3: Implement the user co-creation function subsystem to provide users with the ability to upload content, post comments, participate in topic polls, and share content to social platforms; Step 3.4: Establish an independent administrator backend system with functions such as content review, data update and maintenance, system monitoring and user management.

[0010] Furthermore, step 4 specifically includes: Step 4.1: Invite the target user group to participate in a two-week platform prototype test, covering all core functions; Step 4.2: Collect quantitative data and qualitative feedback; Step 4.3: Based on the collected data and feedback, the Kano model is used again to analyze the satisfaction of needs and user satisfaction, and to identify the expected and attractive needs that need to be improved. Step 4.4: Based on the analysis results, optimize the platform user interface in detail, simplify key interaction processes, and perform performance tuning for system response speed and stability; Step 4.5: After multiple rounds of iterative cycles of "development-testing-analysis-optimization", a sustainable digital platform for industrial heritage is finally formed, which has stable functions, a good user experience, and the vitality of content updates and user interaction.

[0011] This invention also proposes a system for constructing a digital platform for industrial heritage based on the Kano-QFD model and ant colony algorithm. The system includes: a user demand collection and Kano-QFD fusion analysis unit, a heritage resource spatial analysis and path optimization unit, an immersive interactive platform design and development unit, and a platform testing, iteration, and sustainable operation unit. User Requirements Acquisition and Kano-QFD Fusion Analysis Unit: Used to acquire and transform user requirements; Heritage Resource Spatial Analysis and Route Optimization Unit: Used to construct heritage geographical models and plan guided routes; Immersive Interactive Platform Design and Development Unit: Used to implement the front-end and back-end systems and core functional modules; Platform Testing, Iteration and Sustainable Operations Unit: Used to validate optimizations and develop sustainable operation plans.

[0012] Furthermore, the user needs collection and Kano-QFD fusion analysis unit includes a structured questionnaire design module, a Kano needs classification module, a Better-Worse coefficient analysis module, and a QFD function transformation module. The structured questionnaire design module is responsible for designing questionnaires for industrial heritage digital services. The Kano needs classification module is responsible for classifying needs based on questionnaire data, identifying essential, expected, attractive, and undifferentiated needs. The Better-Worse coefficient analysis module is responsible for quantifying the contribution and impact of each function on user satisfaction through four-quadrant analysis. The QFD function transformation module is responsible for combining the quality function deployment method to transform the needs analysis results into platform function design parameters and priority ranking.

[0013] Furthermore, the heritage resource spatial analysis and path optimization unit includes a coordinate data processing module, a spatial clustering analysis module, a path optimization calculation module, and a visualization output module. The coordinate data processing module is responsible for collecting the geographic coordinate data of industrial heritage sites within the target area and completing the coordinate system unification process. The spatial clustering analysis module is responsible for performing spatial clustering analysis of heritage sites using the ant colony algorithm and introducing terrain resistance factors and UTM projection corrections. The path optimization calculation module is responsible for calculating the optimal traversal path and resource linear clustering degree through a pheromone positive feedback mechanism and a probability selection strategy. The visualization output module is responsible for generating a heat map of the spatial distribution of heritage sites and an optimal guide route map, providing spatial decision support for online and offline guides.

[0014] Furthermore, the immersive interactive platform design and development unit includes a system architecture construction module, a 3D scene reconstruction module, a multi-dimensional experience integration module, and a user co-creation support module. The system architecture construction module is responsible for designing and implementing the overall platform architecture, including a data layer, service layer, interaction layer, and presentation layer, based on preliminary requirements analysis and spatial data. The 3D scene reconstruction module is responsible for using 3D modeling and digital twin technology to complete the dynamic restoration and overall scene reconstruction of industrial heritage buildings and machinery. The multi-dimensional experience integration module is responsible for integrating VR / AR roaming, spatial audio, interactive narrative, and gamified learning functions to construct an immersive experience environment that integrates multiple senses. The user co-creation support module is responsible for developing functions that support users to upload content, comment, vote, share, and engage in social interaction, promoting the co-creation of platform content and community activity.

[0015] Furthermore, the platform testing, iteration, and sustainable operation unit includes a testing and evaluation module, a dynamic iteration module, an ecosystem expansion module, and an operation mechanism module. The testing and evaluation module is responsible for conducting multiple rounds of user testing and experience evaluation, and the system collects user behavior data and feedback. The dynamic iteration module is responsible for dynamically monitoring requirements and optimizing functions based on the Kano model analysis framework and real-time usage data. The ecosystem expansion module is responsible for establishing open API interfaces and standardized data services to support the access of third-party content and services, thereby expanding the platform ecosystem. The operation mechanism module is responsible for designing an incentive system for points, revenue sharing rules for cultural and creative products, and community operation strategies to ensure the long-term sustainable operation of the platform.

[0016] The beneficial effects of this invention are: This invention proposes a method and system for constructing a digital platform for industrial heritage based on the Kano-QFD model and ant colony algorithm. This method and system deeply integrate cutting-edge digital technologies, systematically combine heritage resources with user needs, design immersive and narrative interactive experiences, and establish an evolvable, scalable, and sustainable operational framework, thereby comprehensively, vividly, and sustainably realizing the digital inheritance and public dissemination of the value of industrial heritage. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0018] Figure 1 This is an overall flowchart of the method for constructing an industrial heritage digitization platform based on the Kano-QFD model and ant colony algorithm described in this invention.

[0019] Figure 2 This is an overall flowchart of the method of the present invention.

[0020] Figure 3 This is a schematic diagram of the Kano-QFD integrated requirements analysis model.

[0021] Figure 4 This is a flowchart of the ant colony algorithm path optimization process.

[0022] Figure 5 This is a system architecture diagram of the industrial heritage digital platform. Detailed Implementation

[0023] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] Specifically, in combination Figures 1-5 This invention proposes a method for constructing a digital platform for industrial heritage based on the Kano-QFD model and ant colony algorithm. The method includes: Step 1, Requirements Analysis Phase: Obtain and transform user requirements; Step 2, Spatial Analysis Stage: Constructing a heritage geographical model and planning guided routes; Step 3, Platform Development Phase: Implement the front-end and back-end systems and core functional modules; Step 4, Testing and Iteration Phase: Verify optimization and develop a sustainable operation plan.

[0025] Furthermore, step 1 specifically includes: Step 1.1: Design a Kano model questionnaire targeting the functions of the industrial heritage digitization platform; Step 1.2: Distribute questionnaires through online social media, on-site heritage sites, and professional seminars; Step 1.3: Process and classify the recovered data based on the Kano model analysis method; Step 1.4: Calculate the Better-Worse coefficient for each functional item, sort them according to the difference between (Better coefficient - |Worse coefficient|), and determine the priority sequence for platform functional development; Step 1.5: Transform the above classification and priority analysis results into a specific list of platform functional modules, interface interaction logic, and visual design specification documents.

[0026] Furthermore, step 2 specifically includes: Step 2.1: Select the research object and obtain its precise latitude and longitude coordinates through a geographic information system to form a set of points; Step 2.2: The ant colony optimization algorithm is implemented using the MATLAB software platform to solve the optimal traversal path between multiple heritage points; the key parameters of the algorithm are set as follows: number of ants m=20, pheromone importance factor α=1, heuristic function importance factor β=5, and pheromone volatility coefficient ρ=0.1. Step 2.3: Introduce actual terrain slope data as a resistance factor to correct the Euclidean distance matrix between heritage points and generate a cost distance matrix; Step 2.4: Run the ant colony algorithm. After iterative convergence, output the optimal traversal path. At the same time, the algorithm generates a heat map of the resource concentration of heritage sites and visualizes the planned guide path.

[0027] Furthermore, step 3 specifically includes: Step 3.1: The front-end development adopts the WeChat Mini Program framework, which includes: an integrated map navigation module, a 3D model display module, and a VR real-scene roaming module; Step 3.2: The backend service is deployed on a cloud server and uses a relational database to store and manage three types of core data: heritage ontology data, user behavior data, and user feedback data; Step 3.3: Implement the user co-creation function subsystem to provide users with the ability to upload content, post comments, participate in topic polls, and share content to social platforms; Step 3.4: Establish an independent administrator backend system with functions such as content review, data update and maintenance, system monitoring and user management.

[0028] Furthermore, step 4 specifically includes: Step 4.1: Invite the target user group to participate in a two-week platform prototype test, covering all core functions; Step 4.2: Collect quantitative data and qualitative feedback; Step 4.3: Based on the collected data and feedback, the Kano model is used again to analyze the satisfaction of needs and user satisfaction, and to identify the expected and attractive needs that need to be improved. Step 4.4: Based on the analysis results, optimize the platform user interface in detail, simplify key interaction processes, and perform performance tuning for system response speed and stability; Step 4.5: After multiple rounds of iterative cycles of "development-testing-analysis-optimization", a sustainable digital platform for industrial heritage is finally formed, which has stable functions, a good user experience, and the vitality of content updates and user interaction.

[0029] This invention also proposes a system for constructing a digital platform for industrial heritage based on the Kano-QFD model and ant colony algorithm. The system includes: a user demand collection and Kano-QFD fusion analysis unit, a heritage resource spatial analysis and path optimization unit, an immersive interactive platform design and development unit, and a platform testing, iteration, and sustainable operation unit. User Requirements Acquisition and Kano-QFD Fusion Analysis Unit: Used to acquire and transform user requirements; Heritage Resource Spatial Analysis and Route Optimization Unit: Used to construct heritage geographical models and plan guided routes; Immersive Interactive Platform Design and Development Unit: Used to implement the front-end and back-end systems and core functional modules; Platform Testing, Iteration and Sustainable Operations Unit: Used to validate optimizations and develop sustainable operation plans.

[0030] Furthermore, the user needs collection and Kano-QFD fusion analysis unit includes a structured questionnaire design module, a Kano needs classification module, a Better-Worse coefficient analysis module, and a QFD function transformation module. The structured questionnaire design module is responsible for designing questionnaires covering functional modules such as heritage tours, exhibitions, searches, virtual tours, and cultural and creative shops for industrial heritage digital services. The Kano needs classification module is responsible for classifying needs based on questionnaire data, identifying essential, expected, attractive, and undifferentiated needs. The Better-Worse coefficient analysis module is responsible for quantifying the contribution and impact of each function on user satisfaction through four-quadrant analysis. The QFD function transformation module is responsible for converting the needs analysis results into platform function design parameters and priority rankings by combining the Quality Function Deployment (QFD) method.

[0031] Furthermore, the heritage resource spatial analysis and path optimization unit includes a coordinate data processing module, a spatial clustering analysis module, a path optimization calculation module, and a visualization output module. The coordinate data processing module is responsible for collecting the geographic coordinate data of industrial heritage sites within the target area and completing the coordinate system unification process. The spatial clustering analysis module is responsible for performing spatial clustering analysis of heritage sites using the ant colony algorithm and introducing terrain resistance factors and UTM projection corrections. The path optimization calculation module is responsible for calculating the optimal traversal path and resource linear clustering degree through a pheromone positive feedback mechanism and a probability selection strategy. The visualization output module is responsible for generating a heat map of the spatial distribution of heritage sites and an optimal guide route map, providing spatial decision support for online and offline guides.

[0032] Furthermore, the immersive interactive platform design and development unit includes a system architecture construction module, a 3D scene reconstruction module, a multi-dimensional experience integration module, and a user co-creation support module. The system architecture construction module is responsible for designing and implementing the overall platform architecture, including a data layer, service layer, interaction layer, and presentation layer, based on preliminary requirements analysis and spatial data. The 3D scene reconstruction module is responsible for using 3D modeling and digital twin technology to complete the dynamic restoration and overall scene reconstruction of industrial heritage buildings and machinery. The multi-dimensional experience integration module is responsible for integrating VR / AR roaming, spatial audio, interactive narrative, and gamified learning functions to construct an immersive experience environment that integrates multiple senses. The user co-creation support module is responsible for developing functions that support users to upload content, comment, vote, share, and engage in social interaction, promoting the co-creation of platform content and community activity.

[0033] Furthermore, the platform testing, iteration, and sustainable operation unit includes a testing and evaluation module, a dynamic iteration module, an ecosystem expansion module, and an operation mechanism module. The testing and evaluation module is responsible for conducting multiple rounds of user testing and experience evaluation, and the system collects user behavior data and feedback. The dynamic iteration module is responsible for dynamically monitoring requirements and optimizing functions based on the Kano model analysis framework and real-time usage data. The ecosystem expansion module is responsible for establishing open API interfaces and standardized data services to support the access of third-party content and services, thereby expanding the platform ecosystem. The operation mechanism module is responsible for designing an incentive system for points, revenue sharing rules for cultural and creative products, and community operation strategies to ensure the long-term sustainable operation of the platform.

[0034] Example The present invention will be described in detail below with reference to specific embodiments: a method for constructing a digital platform for Harbin industrial heritage.

[0035] According to the overall concept of this invention, this embodiment provides a method for constructing an industrial heritage digitization platform based on the Kano-QFD model and ant colony algorithm. This method is driven by user needs and spatial analysis, and through systematic development and iteration, ultimately achieves the sustainable operation of the platform. Specifically, it includes the following steps: Step 1, Requirements Analysis Phase: Obtaining and Transforming User Needs Step 1 specifically involves: Step 1.1: Design a Kano model questionnaire for the functions of the industrial heritage digital platform. The questionnaire covers 20 specific function descriptions in dimensions such as "heritage information display", "virtual tour", "interactive experience", "social sharing" and "cultural and creative consumption".

[0036] Step 1.2: Questionnaires were distributed through online social media, on-site visits to heritage sites, and professional seminars, and a total of 201 valid questionnaires were collected.

[0037] Step 1.3: Process and classify the recovered data based on the Kano model analysis method. "Heritage Presentation" (i.e., basic graphic, audio-visual materials display) and "Dynamic Simulation" (such as animations of production processes) are identified as essential needs (M); "Live-Action Tours" (360° panoramic or model tours) and "Industrial Memories" (old photos, oral history collections) are identified as desired needs (O); "Heritage Guided Tours" (personalized route planning) and "Cultural and Creative Shops" (online purchase of derivative products) are identified as attractive needs (A).

[0038] Step 1.4: Calculate the Better-Worse coefficient for each function item, sort them according to the difference between (Better coefficient - |Worse coefficient|), and determine the priority sequence for platform function development.

[0039] Step 1.5: Transform the above classification and priority analysis results into a specific list of platform functional modules, interface interaction logic, and visual design specification documents.

[0040] Step 2, Spatial Analysis Stage: Constructing a Heritage Geographic Model and Planning Guide Routes Step 2 specifically involves: Step 2.1: Select 19 representative industrial heritage sites in Harbin as research objects, and obtain their precise latitude and longitude coordinates through Geographic Information System (GIS) to form a set of points P={P1, P2, ..., P19}.

[0041] Step 2.2: Implement the Ant Colony Optimization (ACO) algorithm using the MATLAB software platform to solve the optimal traversal path between multiple heritage points (Traveling Salesman Problem, TSP). The key parameters of the algorithm are set as follows: number of ants m=20, pheromone importance factor α=1, heuristic function importance factor β=5, and pheromone evaporation coefficient ρ=0.1.

[0042] Step 2.3: To improve the practicality of path planning, actual terrain slope data is introduced as a resistance factor to correct the Euclidean distance matrix between heritage points and generate a cost distance matrix.

[0043] Step 2.4: Run the ant colony algorithm. After iterative convergence, output the optimal traversal path. The total length of this path is calculated to be 3.67 × 10⁻⁶. 4 Meters. Simultaneously, the algorithm generates a heat map of the resource clustering density at heritage sites and visualizes the planned tour route.

[0044] Step 3, Platform Development Phase: Implementing the front-end and back-end systems and core functional modules. Step 3 specifically involves: Step 3.1: Front-end development uses the WeChat Mini Program framework, and the main modules include: Integrated map navigation module: Calls Tencent Map API to enable heritage site location, route navigation, and surrounding information query.

[0045] 3D Model Display Module: Renders lightweight 3D models of heritage buildings online, supporting interactive operations such as rotation and scaling.

[0046] VR Real-Scene Roaming Module: Constructs immersive virtual roaming scenes based on panoramic image sequences or point cloud data.

[0047] Step 3.2: The backend service is deployed on a cloud server, using a relational database to store and manage three types of core data: Heritage data includes architectural information, historical texts, and multimedia materials.

[0048] User behavior data: browsing history, dwell time, interaction history, etc.

[0049] User feedback data: comments, ratings, uploaded content, etc.

[0050] Step 3.3: Implement the user co-creation function subsystem to provide users with the ability to upload content (text, images, short videos), post comments, participate in topic polls, and share content to social platforms.

[0051] Step 3.4: Establish an independent administrator backend system with functions such as content review (user-generated content), data update and maintenance (addition, deletion and modification of heritage information), system monitoring and user management.

[0052] Step 4, Testing and Iteration Phase: Validate and optimize to develop a sustainable operation plan. Step 4 specifically involves: Step 4.1: Invite 50 people from the target user group, including cultural heritage enthusiasts, local residents and tourists, to conduct a two-week prototype test of the platform, covering all core functions.

[0053] Step 4.2: Collect quantitative data (such as click-through rate of each function, task completion rate, and user dwell time) and qualitative feedback (test questionnaires and interview records).

[0054] Step 4.3: Based on the collected data and feedback, the Kano model is used again to analyze the satisfaction of needs and user satisfaction, and to identify the expected and attractive needs that need to be improved.

[0055] Step 4.4: Based on the analysis results, optimize the platform user interface (UI) in detail, simplify key interaction processes, and perform performance tuning for system response speed and stability.

[0056] Step 4.5: After multiple rounds of iterative cycles of "development-testing-analysis-optimization", a sustainable digital platform for industrial heritage is finally formed, which has stable functions, a good user experience, and the vitality of content updates and user interaction.

[0057] The foregoing has provided a detailed description of the method and system for constructing an industrial heritage digitization platform based on the Kano-QFD model and ant colony algorithm proposed in this invention. Specific examples have been used to illustrate the principles and implementation methods of this invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of this invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this invention. Therefore, the content of this specification should not be construed as a limitation of this invention.

Claims

1. A method for constructing a digital platform for industrial heritage based on the Kano-QFD model and ant colony algorithm, characterized in that, The method includes: Step 1, Requirements Analysis Phase: Obtain and transform user requirements; Step 2, Spatial Analysis Stage: Constructing a heritage geographical model and planning guided routes; Step 3, Platform Development Phase: Implement the front-end and back-end systems and core functional modules; Step 4, Testing and Iteration Phase: Verify optimization and develop a sustainable operation plan.

2. The method according to claim 1, characterized in that, Step 1 specifically includes: Step 1.1: Design a Kano model questionnaire targeting the functions of the industrial heritage digitization platform; Step 1.2: Distribute questionnaires through online social media, on-site heritage sites, and professional seminars; Step 1.3: Process and classify the recovered data based on the Kano model analysis method; Step 1.4: Calculate the Better-Worse coefficient for each functional item, sort them according to the difference between (Better coefficient - |Worse coefficient|), and determine the priority sequence for platform functional development; Step 1.5: Transform the above classification and priority analysis results into a specific list of platform functional modules, interface interaction logic, and visual design specification documents.

3. The method according to claim 1, characterized in that, Step 2 specifically includes: Step 2.1: Select the research object and obtain its precise latitude and longitude coordinates through a geographic information system to form a set of points; Step 2.2: The ant colony optimization algorithm is implemented using the MATLAB software platform to solve the optimal traversal path between multiple heritage points; the key parameters of the algorithm are set as follows: number of ants m=20, pheromone importance factor α=1, heuristic function importance factor β=5, and pheromone volatility coefficient ρ=0.

1. Step 2.3: Introduce actual terrain slope data as a resistance factor to correct the Euclidean distance matrix between heritage points and generate a cost distance matrix; Step 2.4: Run the ant colony algorithm. After iterative convergence, output the optimal traversal path. At the same time, the algorithm generates a heat map of the resource concentration of heritage sites and visualizes the planned guide path.

4. The method according to claim 1, characterized in that, Step 3 specifically includes: Step 3.1: The front-end development adopts the WeChat Mini Program framework, which includes: an integrated map navigation module, a 3D model display module, and a VR real-scene roaming module; Step 3.2: The backend service is deployed on a cloud server and uses a relational database to store and manage three types of core data: heritage ontology data, user behavior data, and user feedback data; Step 3.3: Implement the user co-creation function subsystem to provide users with the ability to upload content, post comments, participate in topic polls, and share content to social platforms; Step 3.4: Establish an independent administrator backend system with functions such as content review, data update and maintenance, system monitoring and user management.

5. The method according to claim 1, characterized in that, Step 4 specifically includes: Step 4.1: Invite the target user group to participate in a two-week platform prototype test, covering all core functions; Step 4.2: Collect quantitative data and qualitative feedback; Step 4.3: Based on the collected data and feedback, the Kano model is used again to analyze the satisfaction of needs and user satisfaction, and to identify the expected and attractive needs that need to be improved. Step 4.4: Based on the analysis results, optimize the platform user interface in detail, simplify key interaction processes, and perform performance tuning for system response speed and stability; Step 4.5: After multiple rounds of iterative cycles of "development-testing-analysis-optimization", a sustainable digital platform for industrial heritage is finally formed, which has stable functions, a good user experience, and the vitality of content updates and user interaction.

6. A system for constructing a digital platform for industrial heritage based on the Kano-QFD model and ant colony algorithm, characterized in that, The system includes: a user needs collection and Kano-QFD fusion analysis unit, a heritage resource spatial analysis and path optimization unit, an immersive interactive platform design and development unit, and a platform testing, iteration, and sustainable operation unit; User Requirements Acquisition and Kano-QFD Fusion Analysis Unit: Used to acquire and transform user requirements; Heritage Resource Spatial Analysis and Route Optimization Unit: Used to construct heritage geographical models and plan guided routes; Immersive Interactive Platform Design and Development Unit: Used to implement the front-end and back-end systems and core functional modules; Platform Testing, Iteration and Sustainable Operations Unit: Used to validate optimizations and develop sustainable operation plans.

7. The system according to claim 6, characterized in that, The user needs collection and Kano-QFD fusion analysis unit includes a structured questionnaire design module, a Kano needs classification module, a Better-Worse coefficient analysis module, and a QFD function transformation module. The structured questionnaire design module is responsible for designing questionnaires for industrial heritage digitization services. The Kano needs classification module is responsible for categorizing needs based on questionnaire data, identifying essential, expected, attractive, and undifferentiated needs. The Better-Worse coefficient analysis module is responsible for quantifying the contribution and impact of missing functions on user satisfaction through four-quadrant analysis. The QFD function transformation module is responsible for combining the Quality Function Deployment (QFD) method to transform the needs analysis results into platform function design parameters and priority ranking.

8. The system according to claim 6, characterized in that, The heritage resource spatial analysis and path optimization unit includes a coordinate data processing module, a spatial clustering analysis module, a path optimization calculation module, and a visualization output module; the coordinate data processing module is responsible for collecting the geographic coordinate data of industrial heritage sites within the target area and completing the coordinate system unification processing; The spatial clustering analysis module is responsible for performing spatial clustering analysis on heritage sites using the ant colony algorithm, and introducing terrain resistance factors and UTM projection corrections; the path optimization calculation module is responsible for calculating the optimal traversal path and resource linear clustering degree through a pheromone positive feedback mechanism and a probability selection strategy; the visualization output module is responsible for generating heat maps of the spatial distribution of heritage sites and optimal guide routes, providing spatial decision support for online and offline guides.

9. The system according to claim 6, characterized in that, The immersive interactive platform design and development unit includes a system architecture construction module, a 3D scene reconstruction module, a multi-dimensional experience integration module, and a user co-creation support module. The system architecture construction module is responsible for designing and implementing the overall platform architecture, which includes a data layer, a service layer, an interaction layer, and a presentation layer, based on preliminary requirements analysis and spatial data. The 3D scene reconstruction module is responsible for using 3D modeling and digital twin technology to complete the dynamic restoration and overall scene reconstruction of industrial heritage buildings and machinery. The multi-dimensional experience integration module is responsible for integrating VR / AR roaming, spatial audio, interactive narrative, and gamified learning functions to construct an immersive experience environment that integrates multiple senses. The user co-creation support module is responsible for developing functions that support users to upload content, comment, vote, share, and interact socially, thereby promoting the co-creation of platform content and community activity.

10. The system according to claim 6, characterized in that, The platform testing, iteration, and sustainable operation unit includes a testing and evaluation module, a dynamic iteration module, an ecosystem expansion module, and an operation mechanism module. The testing and evaluation module is responsible for conducting multiple rounds of user testing and experience evaluation, and the system collects user behavior data and feedback. The dynamic iteration module is responsible for dynamically monitoring requirements and optimizing functions based on the Kano model analysis framework and real-time usage data. The ecosystem expansion module is responsible for establishing open API interfaces and standardized data services to support the access of third-party content and services, thereby expanding the platform ecosystem. The operation mechanism module is responsible for designing an incentive system, revenue-sharing rules for cultural and creative products, and community operation strategies to ensure the long-term sustainable operation of the platform.

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