Intelligent Sensing-Based Data Ownership Confirmation and Digital Asset Operation Platform and Method

Abstract

This invention provides a data ownership confirmation and digital asset operation platform and method based on intelligent sensing, comprising: a unified sensing access module for protocol adaptation, identity registration, edge preprocessing, and standardized data conversion of multi-source sensing devices; a full lifecycle data storage module for forming an immutable, trusted data chain throughout the entire lifecycle; a data ownership confirmation engine module for generating ownership confirmation certificates with unique ownership identifiers; a digital asset modeling module for converting the confirmed data into standardized digital assets; and an operation service module for providing standardized interfaces for asset query, traceability verification, regulatory integration, and value assessment. Each module is implemented based on StarSpark global self-organizing network communication, national cryptographic encryption, blockchain notarization, and a CIM 3D central control base. This invention aims to achieve unified access for multi-source sensing devices, trusted notarization of data throughout the entire lifecycle, dynamic technical ownership confirmation, and automated generation and market-oriented operation of digital assets.

Description

Technical Field

[0001] This invention relates to the field of digital asset operation technology, and in particular to a data ownership confirmation and digital asset operation platform and method based on intelligent sensing. Background Technology

[0002] With the rapid development of new-generation information technologies such as the Internet of Things, 5G, and blockchain, the field of urban infrastructure monitoring has undergone generational evolution from manual inspection to automatic data collection, and from single-point monitoring to ubiquitous sensing. In the early stages, urban gas, water supply, drainage, and fire protection systems each built independent monitoring platforms, using dedicated protocols and private data formats to achieve basic data collection and anomaly alarm functions. In recent years, with the advancement of urban lifeline safety projects, various regions have begun to try to aggregate data from multiple industries into a unified regulatory platform, but overall it is still in the rudimentary stage of data dashboards and simple statistical analysis. Regarding data ownership, existing solutions generally lack effective means to technically confirm data ownership. Most platforms only declare data ownership through user account binding or manual registration, which cannot guarantee the authenticity of the data source and the integrity of the collection chain, leading to frequent disputes over data ownership. In terms of digital asset operation, although data has been listed as the fifth major factor of production, a large amount of urban sensing data remains dormant. That is, existing systems use monitoring data only for routine supervision and viewing, without establishing a standardized, quantifiable, and tradable data asset model, and the data value cannot be effectively converted. At the same time, platforms in various industries are built independently, and the underlying sensing access, data processing, security encryption, evidence storage and traceability capabilities cannot be reused, resulting in serious duplication of construction, poor system scalability, and low overall return on investment. Therefore, there is an urgent need in this field for a data ownership confirmation and digital asset operation platform and method based on intelligent perception to solve the above-mentioned technical problems. Summary of the Invention

[0003] This invention provides a data ownership confirmation and digital asset operation platform and method based on intelligent sensing, aiming to achieve unified access of multi-source sensing devices, reliable data storage throughout the entire life cycle, dynamic technical ownership confirmation, and automated generation and market operation of digital assets.

[0004] On the one hand, this invention provides a data ownership confirmation and digital asset operation platform based on intelligent sensing, comprising: The unified sensing access module is used to realize protocol adaptation, identity registration, edge preprocessing and standardized data conversion of multi-source sensing devices; The full lifecycle data storage module is connected to the unified sensing access module and is used to store the identity identifier, timestamp, spatial location, link signature, operating status data, compliance supervision data, energy efficiency management data, safety monitoring data and maintenance records of the sensing device, forming an immutable full lifecycle trusted data chain; The data ownership confirmation engine module is connected to the full lifecycle data storage module and is used to perform multi-dimensional trusted binding based on the identity identifier, timestamp, spatial location and link signature to generate ownership confirmation certificate with unique ownership identifier. The digital asset modeling module, connected to the data ownership confirmation engine module, is used to convert the confirmed operational status data, compliance supervision data, energy efficiency control data, and safety monitoring data into standardized digital assets and establish a real-time update mechanism. The operation service module, connected to the digital asset modeling module, is used to provide standardized interfaces for asset query, traceability verification, regulatory docking, and value assessment. In addition, the StarSpark global self-organizing network communication module, the national cryptographic full-link encryption module, the blockchain global evidence storage module, and the CIM three-dimensional master control base module are respectively connected to the above modules.

[0005] On the other hand, the present invention provides a method for data ownership confirmation and digital asset operation based on intelligent sensing, comprising the following steps: Step S1: Register, authenticate, and bind the unique identities of various sensing devices; Step S2: Multi-dimensional real-time data acquisition and edge preprocessing, with the addition of timestamps, spatial locations, and full-link national cryptographic signatures; Step S3: Construct a trusted data chain for the entire lifecycle of the equipment, storing at least the identity identifier, timestamp, spatial location, link signature, operating status data, compliance and regulatory data, energy efficiency management data, safety monitoring data, and maintenance records, and complete blockchain notarization; Step S4: Conduct technical rights confirmation based on device identity, timestamp, link signature, spatial location, and dynamic contribution, and generate rights confirmation certificates; Step S5: Automatically generate corresponding standardized digital assets based on the confirmed operational status data, compliance and regulatory data, energy efficiency management data, and safety monitoring data; Step S6: Provide digital asset traceability, verification, and market-oriented operation services to external parties.

[0006] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: 1. This invention achieves compatibility and standardized conversion of multi-protocol devices through a unified perception access layer, thereby reducing device access costs and improving platform scalability.

[0007] 2. This invention establishes a trusted data chain for the entire lifecycle of equipment, combining blockchain notarization with CIM spatiotemporal indexing to ensure data continuity, integrity, and immutability.

[0008] 3. This invention is based on a dynamic contribution-based rights determination algorithm that considers signature pass rate, information entropy, on-chain latency, and spatial uniqueness, thereby achieving fair, quantitative, and dynamic data ownership determination from a technical perspective.

[0009] 4. This invention automatically transforms the operational, compliance, energy efficiency, and safety data after ownership confirmation into standardized digital assets, releasing the value of data elements.

[0010] 5. The StarFlash networking, national cryptographic encryption, blockchain, and CIM technologies of this invention can be deployed once and simultaneously support upper-level applications in multiple industries such as gas, water supply, fire protection, and elevators, avoiding redundant construction.

[0011] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0012] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention, but do not constitute a limitation thereof; in the drawings: Figure 1 This is a schematic diagram of the structure of a data ownership confirmation and digital asset operation platform based on intelligent sensing provided by the present invention; Figure 2 This is a flowchart illustrating a data ownership confirmation and digital asset operation method based on intelligent sensing provided by the present invention. Detailed Implementation

[0013] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention. This embodiment provides a data ownership confirmation and digital asset operation platform and method based on intelligent sensing, targeting industries including but not limited to building fire protection, sewage and grease treatment, urban gas, secondary water supply, urban drainage, urban heating, electromechanical elevators, building power distribution, and building facility interconnection. It provides unified underlying technical support to solve the problems of existing technologies that can only achieve data collection, simple on-chaining, or manual ownership confirmation, but cannot achieve unified access and standardized conversion of multi-source sensing devices, cannot achieve fair, quantitative, and automated ownership confirmation through dynamic contribution algorithms, and cannot automatically generate standardized digital assets from ownership data for market-oriented operation. Thus, it realizes an ownership confirmation structure that separates the rights of data resource holding, data processing and use, and data product operation, making the ownership clear, divisible, tradable, and regulated.

[0014] Example 1: Please refer to Figure 1 A data ownership confirmation and digital asset operation platform based on intelligent sensing, comprising: The unified sensing access module is used to realize protocol adaptation, identity registration, edge preprocessing and standardized data conversion of multi-source sensing devices; The full lifecycle data storage module, connected to the unified sensing access module, is used to store the identity identifier, timestamp, spatial location, link signature, operating status data, compliance and regulatory data, energy efficiency management data, safety monitoring data, and maintenance records of sensing devices, forming an immutable, trusted full lifecycle data chain. The data ownership confirmation engine module is connected to the full lifecycle data storage module. It is used to perform multi-dimensional trusted binding based on identity, timestamp, spatial location and link signature, and generate ownership confirmation certificates with unique ownership identifiers. The digital asset modeling module, connected to the data ownership confirmation engine module, is used to transform the confirmed operational status data, compliance and regulatory data, energy efficiency management data, and safety monitoring data into standardized digital assets and establish a real-time update mechanism. The operation service module, connected to the digital asset modeling module, provides standardized interfaces for asset inquiry, traceability verification, regulatory coordination, and value assessment. In addition, the StarSpark global self-organizing network communication module, the national cryptographic full-link encryption module, the blockchain global evidence storage module, and the CIM three-dimensional master control base module are respectively connected to the above modules.

[0015] Specifically, the platform is divided into a technical support layer and a business processing layer. The technical support layer includes: a StarSpark full-domain self-organizing network communication module, a national cryptographic full-link encryption module, a blockchain full-domain evidence storage module, and a CIM 3D central control base module. The business processing layer includes: a unified perception access module, a full lifecycle data storage module, a data ownership confirmation engine module, a digital asset modeling module, and an operation service module. The technical support layer provides the business processing layer with unified communication connectivity, data encryption, trusted evidence storage, and 3D spatial mapping capabilities, ensuring that all business modules operate on a secure, reliable, and traceable underlying foundation.

[0016] The unified sensing access module is responsible for connecting sensing devices from different manufacturers and using different communication protocols (such as gas pressure sensors, water immersion sensors, elevator vibration sensors, smoke detectors, grease concentration sensors, etc.) to the platform. This module has a built-in scalable protocol stack that supports Near Link, Wi-Fi, ZigBee, LoRa, Modbus, and various industry-specific protocols. It completes device identity registration, edge data cleaning, and format unification to ensure that data from heterogeneous devices can be transmitted upwards in a standardized form. The full lifecycle data storage module receives structured data from the unified sensing access module and establishes an independent data record for each sensing device based on a distributed ledger or time-series database. This record includes at least: a unique identifier assigned during device registration (such as a DID string), a high-precision timestamp, spatial location (latitude, longitude, elevation, and grid code) obtained from the CIM 3D central control base, a national cryptographic link signature (i.e., SM2 signature value), device operating status data (such as pressure, temperature, and vibration amplitude), compliance and regulatory data (such as whether there are alarms for exceeding standards or whether the device meets national standard thresholds), energy efficiency management data (such as energy consumption per unit time and efficiency coefficient), safety monitoring data (such as elevator door lock status and gas leak concentration), and maintenance records (such as calibration time and repair / replacement parts). Once the above data is written, it is guaranteed to be tamper-proof through blockchain technology, forming a trusted data chain throughout the entire lifecycle of the device from commissioning to scrapping. The data ownership confirmation engine module reads the identity identifier, timestamp, spatial location, and link signature from the storage module. First, it verifies the authenticity of the link signature (using SM2 public key verification) to confirm that the data has not been tampered with during transmission. Then, it hashes and binds the identity identifier (device DID), timestamp, and spatial coordinates with the data content to generate a unique spatiotemporal identity fingerprint. This fingerprint serves as the core of the ownership confirmation credential, clarifying which device generated the data, when, and where, and ensuring that the data source link is complete and trustworthy. The digital asset modeling module receives various types of data after ownership confirmation. It automatically maps four types of data—operation status, compliance supervision, energy efficiency management, and safety monitoring—to asset attribute values ​​according to the predefined asset models of each industry (for example, the urban gas industry can define "gas pipeline pressure fluctuation index asset", and the building fire protection industry can define "fire protection facility integrity rate asset"). It also generates a unique asset code, ownership information, validity period, and value anchor hash for each asset, forming standardized digital assets that meet the listing requirements of data exchanges. The operation service module provides a set of standardized interfaces: asset query interface (supports searching by device ID, time range, geographical region, and asset type), traceability verification interface (inputs data hash and returns blockchain evidence), regulatory docking interface (automatically pushes compliant data to the city lifeline regulatory platform after anonymization), value assessment interface (can be connected to third-party assessment models to output asset valuation), and revenue sharing interface (automatically distributes revenue according to subsequent confirmation weights). The StarSpark global self-organizing network communication module is responsible for the self-organizing network and low-latency transmission of massive sensing devices. The national cryptographic full-link encryption module performs SM2 / SM3 / SM4 full-process encryption and signing of data from the device end to the platform end. The blockchain global evidence storage module stores information such as device registration, data collection hash, and confirmation certificate on the chain. The CIM 3D master control base module provides city-level geographic information, building information model, IoT device spatial mapping, and one-map command capability.

[0017] In one implementation, the unified perception access module includes: Multi-protocol adapter unit for compatibility with StarFlash, Wi-Fi, ZigBee, LoRa, Modbus and industry-customized protocols; The device identity registration unit is used to generate a globally unique identity identifier based on DID technology for each sensing device and to complete key distribution and binding; The edge data preprocessing unit is used to filter, deduplicate, remove anomalies, and align timestamps on the raw sensing data. The protocol standardization conversion unit is used to convert data from different protocols into a unified internal data format. The internal data format includes at least device identification, timestamp, spatial location, national cryptographic link signature, and sensing data payload.

[0018] Specifically, the multi-protocol adaptation unit adopts a plug-in architecture. For the StarFlash protocol, it uses the Near Link SDK provided by the StarFlash Alliance to parse broadcast frames; for Wi-Fi, it uses Socket programming to parse TCP / UDP packets; for ZigBee and LoRa, it uses the serial port or MQTT protocol of the corresponding gateway; for Modbus, it uses the standard RTU / ASCII parsing library; for industry-customized protocols (such as the private binary protocol of a certain brand of gas meter), users are allowed to upload protocol description files (XML or JSON format), and the system compiles the parser. After receiving the raw data packet, the unit first identifies the protocol type, and then extracts fields such as the original device ID, time, and data value according to the corresponding rules. The device identity registration unit is based on distributed identity (DID) technology. When a sensing device connects for the first time, the platform uses the national cryptographic algorithm SM2 to generate a public-private key pair for the device. The public key is hashed to generate the device DID (format:did:sm:123456789abcdef). The private key is securely burned into the device's trusted execution environment (or security chip). The unit also records the device's physical characteristics (MAC address, serial number), installation location (latitude and longitude obtained from CIM), and ownership entity (e.g., a gas company, a property management company), and binds this information to the DID for on-chain storage. For each subsequent data report, the device must sign the data packet using its private key, and the platform verifies the signature using the public key corresponding to the DID. The edge data preprocessing unit is deployed on an edge gateway or platform close to the device. The filtering uses median filtering or moving average filtering to remove sensor spike noise. Deduplication is achieved by maintaining a sliding window (e.g., only the first value reported by the same device in the last 5 seconds is retained). Anomaly removal is based on the 3σ criterion or industry thresholds (e.g., gas pressure exceeding 6 kPa is considered invalid). Timestamp alignment refers to writing the unified reference time (microsecond level) after synchronizing the device's local time with the star flash / network time into the data packet to ensure the consistency of the time reference of multi-source data. The protocol standardization conversion unit maps the preprocessed data to a unified data structure (Protobuf or JSON Schema) within the platform. This structure includes at least: device identification (DID string), timestamp (Unix microseconds), spatial location (longitude, latitude, elevation, CIM grid code), national cryptographic link signature (SM2 signature value Base64 encoded), and sensing data payload (a list of key-value pairs, such as {"metric":"pressure","value":101.3,"unit":"kPa"}). The converted data packet is then sent to the full lifecycle data storage module.

[0019] In one implementation, the lifecycle data storage module includes: The equipment history storage unit is used to record all events throughout the entire process of equipment installation, commissioning, operation, maintenance, calibration and scrapping; The on-chain evidence storage unit is used to store device identity, timestamp, spatial location, link signature, operating status data, compliance and regulatory data, energy efficiency control data, safety monitoring data, maintenance records, and the hash values ​​of the above data on the blockchain through the blockchain full-domain evidence storage module. The spatiotemporal indexing unit is used to bind three-dimensional spatial coordinates and timestamps to each piece of data based on the CIM three-dimensional master control base module, forming a traceable spatiotemporal data chain.

[0020] Specifically, the device history storage unit uses an immutable log database (such as InfluxDB or Kafka+Parquet) to record the lifecycle events of each sensing device. Event types include: device registration (recording DID, registration time, and initial location), installation events (recording installer, installation location photo hash), calibration events (recording parameters before and after calibration, calibration certificate hash), alarm events (recording alarm type, threshold, and actual value), maintenance events (recording maintenance content and replacement part number), and scrapping events (recording scrapping reason and recycling certificate). Each event has a device DID and a timestamp, and they are strung together in chronological order to form the device history. The on-chain evidence storage unit periodically (e.g., every minute or every 100 data entries) calculates the hash values ​​of the aforementioned data types in batches (using the SM3 algorithm). The hash calculation method is as follows: the device identity identifier, timestamp, spatial location, link signature, operating status data, compliance and regulatory data, energy efficiency management data, safety monitoring data, and maintenance records are concatenated into a byte stream in a fixed order, and then SM3 hashing is performed to obtain a 256-bit hash value. This hash value, along with the corresponding start and end time range and device DID, is packaged into a blockchain transaction and submitted to the consortium blockchain (such as Hyperledger Fabric or FISCOBCOS) through the blockchain global evidence storage module. After the blockchain consensus node verifies the transaction, it is packaged into a block and the transaction ID and block height are returned. The original data itself can be stored in an off-chain distributed database (such as IPFS or Ceph), and only the hash value and timestamp are stored on the chain, which ensures that the data is immutable and reduces storage costs. The spatiotemporal index unit is tightly integrated with the CIM 3D master control base. Since the CIM base divides the city into multi-level grids (e.g., 1km×1km, 100m×100m, 10m×10m), when each piece of sensing data is written to the storage module, the finest-grained grid code is calculated based on its spatial coordinates, while retaining the timestamp. The spatiotemporal index unit automatically creates an inverted index for this data with the grid code and timestamp as prefixes. When users need to trace back all sensing data of a certain spatial area within a certain time period, they can quickly locate it. The spatiotemporal index also supports spatiotemporal range queries, such as querying all pressure data within 100 meters of a gas leak point and 10 minutes before and after the leak. This unit ensures the spatiotemporal traceability of the data, providing a data organization foundation for subsequent rights confirmation and assetization.

[0021] In one implementation, the data ownership confirmation engine module includes: The device identity binding unit is used to bind the device's globally unique identity identifier with physical device characteristics, installation location, and owner; The spatiotemporal information fusion unit is used to generate an irrefutable spatiotemporal fingerprint by combining timestamps, spatial locations, and data content. The link signature verification unit is used to verify the national cryptographic signature of the entire link from the sensing end to the platform end to ensure that the data has not been tampered with; The dynamic contribution calculation unit is used to calculate the data weighting of each sensing device within a preset time window. This unit is calculated using the following formula: in, This represents the total number of currently active sensing devices. To prevent division by zero decimals; For sensing devices The pass rate of national cryptographic signature verification within the time window is the ratio of the number of reports that passed verification to the total number of reports. For sensing devices Information entropy of reported data, according to calculate, For sensing devices The reported data value falls on the first Frequency within a quantization interval; Information entropy of all sensing devices within the current time window The arithmetic mean; For sensing devices Average on-chain latency of reported data; This is the arithmetic mean of the average on-chain latency of all sensing devices within the current time window; For sensing devices Spatial uniqueness contribution, according to Calculation, where For sensing devices Data feature vectors within the time window, Iterate through other devices whose spatial distance from the sensing device is less than a preset threshold. The number of neighboring devices; The arithmetic mean of the contributions of all sensing devices to the spatial uniqueness within the current time window; The certificate generation unit is used to generate certificates based on the certificate weight. In addition, device identification, timestamp, and data hash are used to generate cascaded dynamic ownership certificates.

[0022] Specifically, after the sensing device completes DID registration, the device identity binding unit binds the DID with the device's physical characteristics (such as CPU serial number, security chip ID, MAC address), installation location (three-dimensional coordinates obtained from the CIM base and the ID of the building / pipeline segment to which it belongs), ownership entity (such as the organization code of "XX City Gas Group"), and the ownership declaration agreed in the smart contract. The binding relationship is permanently notified through a single blockchain transaction, and the binding information is directly referenced when confirming data ownership in the future, ensuring that the ownership of data resources is clear. For a piece of raw data reported from a sensing device, the spatiotemporal information fusion unit concatenates its timestamp, spatial location (longitude, latitude, elevation, and CIM grid code), and data content (standardized payload data) into a string in a predetermined order. Then, it uses the SM3 algorithm to calculate the hash value of the string, which is the spatiotemporal fingerprint. Since the timestamp and spatial location are unique and the data content is unpredictable, this fingerprint can uniquely identify the data generated by a device at a specific spatiotemporal point and has non-repudiation. When a device reports data, the link signature verification unit uses its private key to perform an SM2 signature on the data packet (including timestamp, location, payload, etc.). After receiving the data, the platform retrieves the public key from the public key file corresponding to the device's DID and verifies the signature. If the verification passes, it indicates that the data has not been tampered with during transmission and indeed originates from that device; otherwise, it rejects the data. The verification pass rate is [not specified in the original text]. That is, the number of verified reports divided by the total number of reports is used as an important indicator of device reliability; The dynamic contribution calculation unit quantifies the relative contribution of each sensing device to the platform's data value within a specific time window, avoiding the unfairness caused by static weighting, such as the defect of giving the same weight to faulty data from older devices and high-quality data from high-performance devices. In the formula, the preset time window length can be configured according to industry needs; for example, it can be set to 1 hour for urban gas monitoring and 24 hours for building fire protection. The window sliding step is half the window length, achieving continuous dynamic updates. (Signature verification pass rate) This reflects the device's communication reliability and data authenticity, and is highly reliable. This means the device's communication is stable and it has not been attacked, making its data more reliable; information entropy The process involves dividing the continuous data values ​​reported by the equipment (e.g., pressure values ​​ranging from 0 to 100 kPa) into K equal intervals (K can be 10 or 20), counting the frequency of data values ​​falling within each interval within a time window, and then calculating the Shannon entropy. A higher entropy value indicates greater data fluctuation and richer information; conversely, if the equipment consistently reports a constant value (e.g., due to a malfunction or jamming), the entropy is close to 0, resulting in low contribution. The formula uses... The format allows devices with higher-than-average information entropy to receive higher weights; average on-chain latency It is the time difference, measured in milliseconds, between the timestamp of data generation by the device and the timestamp of the corresponding blockchain transaction confirmation. A smaller delay indicates faster data transmission, more timely platform processing, and higher data timeliness value. In the formula... It is an exponentially decaying function, meaning the greater the delay, the smaller the weight; spatial uniqueness contribution. To measure the data non-displaceability of a device within its spatial domain, firstly, for each device i, its data feature vector within a time window is extracted. For example, it can include five dimensions: mean, standard deviation, kurtosis coefficient, maximum value, and minimum value (all of which can be calculated in real time); then, the spatial coordinates of device i are obtained using the CIM base, and all other devices (neighborhood devices) within a radius R (e.g., 50 meters) are identified; for each device m in the neighborhood, the Euclidean distance between the feature vectors is calculated. Finally, the average is taken to obtain ; The larger the value, the more significantly the data characteristics of this device differ from those of its neighboring devices. It provides unique information that is difficult to replace, and therefore should receive a higher weight. The formula uses... Achieve gains with relatively high uniqueness; To obtain the smallest positive number, it is only used to prevent division by zero when the denominator is exactly zero, and has no substantial impact on the calculation result; the sum of the numerators of all devices normalizes the weights to the (0,1] interval, so that the sum of all weights is 1, which facilitates subsequent accounting and asset pricing.

[0023] The certificate generation unit outputs the certificate based on the dynamic contribution calculation unit. Combining the device identifier (DID), the timestamp of data generation, and the original data hash (i.e., spatiotemporal fingerprint), a smart contract is invoked to generate a JSON-formatted ownership certificate. The certificate content includes: a unique certificate ID, the device DID, the start and end times of the time window, and the ownership weight. The data hash, certificate generation time, and platform digital signature are used to form a three-level binding relationship between data, weight, and certificate. This certificate can serve as the technical basis for subsequent digital asset transactions, pledging, and financing.

[0024] In one implementation, the digital asset modeling module includes: The asset definition unit is used to define the asset type, unit of measurement, and quality grade of the data after ownership confirmation in accordance with industry standards. The automatic mapping unit is used to automatically map real-time perceived data streams into asset attribute values ​​according to preset rules; The real-time update unit is used to synchronously update the value index and certificate information of digital assets when data is refreshed; The asset certificate generation unit is used to generate standardized digital asset certificates that meet the requirements of the data exchange, including unique asset codes, ownership information, data source fingerprints, validity periods, and value anchor hashes.

[0025] Specifically, the asset definition unit includes built-in asset definition templates for various industries. For example, for the urban gas industry, a digital asset called "Gas Pipeline Pressure Fluctuation Risk Index" can be defined, with its unit of measurement being a risk score (0-100) and quality levels divided into Grade A (data latency <1 second, integrity >99%) and Grade B (latency <5 seconds, integrity >95%). For the building fire protection industry, a "Fire Hydrant Water Pressure Health Asset" can be defined, with its unit of measurement being kPa·h, and its quality level being determined based on the validity period of the sensor calibration certificate. Users can customize new asset types through the management interface, specifying the required sensing data fields, calculation formulas, and quality constraints. The automatic mapping unit monitors newly added ownership data in the full lifecycle data storage module. When it receives a piece of operating status data with ownership certificate (such as gas pressure value 0.8MPa), it executes the preset mapping rules according to the industry type and asset definition associated with its equipment DID. The mapping rules can be simple direct numerical conversion (such as pressure value → risk index). The mapping result generates asset attribute values, such as "2025-03-01 10:00:00, equipment DID:xxx, gas pressure risk index = 37.2". As sensing devices continuously report new data, the real-time update unit updates the attribute values ​​of the corresponding digital assets using streaming computing (using Apache Flink or Spark Streaming), and recalculates the asset's value index, for example, based on a weighted average of the most recent N time points; the validity period and value anchor hash in the asset certificate are also updated synchronously, and the update record is recorded on the blockchain to ensure that the asset status is real-time and reliable. The asset certificate generation unit follows the listing standards of data exchanges to generate standardized certificates for each digital asset; the certificate data structure is as follows: 1. The asset has a unique code, a UUID assigned by the platform, which conforms to the coding rules of the data exchange; 2. Ownership information, namely the equipment owner and platform operator in the certificate of ownership, which declares the data resource holding rights, data processing and usage rights and data product operation rights by means of digital signature; 3. Data source fingerprint, i.e., the SM3 hash value of the original dataset, and the weights used for weight determination. The corresponding signature; 4. Validity period, which is the time frame during which an asset can be traded, is usually consistent with the time window covered by the perceived data; 5. Value anchor hash, which is the hash value calculated by concatenating all the above fields, used as a unique digital fingerprint of the asset when registering it on the exchange; The generated asset certificates can be published externally through the API of the operations service module.

[0026] In one implementation, the operation service module includes: The asset query interface unit is used to provide RESTful APIs or streaming data interfaces to the outside world, supporting the retrieval of digital assets by device, time, region, and asset type; The traceability and verification unit is used to verify the authenticity of the source, the integrity of the time, and the clarity of ownership of any piece of perceived data through the blockchain's stored hash value; The regulatory docking unit is used to submit compliant data to the city lifeline regulatory platform according to preset data anonymization rules. The valuation interface unit is used to connect to third-party valuation models and output a reference valuation range for digital assets. Multi-entity revenue sharing unit, used to determine the weight of each sensing device. The system automatically calculates and allocates the revenue share of each data provider, platform operator, and equipment owner based on the total transaction amount of assets.

[0027] Specifically, the operations service module serves as the gateway for realizing the commercial monetization of digital assets; the asset query interface unit provides a RESTful API (Representative State Transfer Application Programming Interface) based on a web service framework, supporting HTTP GET / POST requests and returning JSON format data; interface parameters include: device DID (multiple selections possible), time range (start timestamp, end timestamp), geographical region (CIM grid code list or circular / rectangular area), and asset type (predefined asset type code); it also provides a web streaming interface, allowing clients to subscribe to real-time asset updates for a specific asset type or region; interface permissions are controlled by the authorizing party. The traceability verification unit provides a unified traceability entry point. Users input the hash value of a piece of sensory data (or the hash in an asset certificate). Internally, the unit calls the query interface of the blockchain full-domain evidence storage module to obtain the evidence storage record corresponding to the hash (including transaction ID, block height, and evidence storage time). If the record returned by the blockchain matches the hash provided by the user, it proves that the data is real and has not been tampered with. At the same time, the device DID and timestamp can be read from the evidence storage record, and then the ownership can be verified through the device identity binding unit to achieve triple verification of source authenticity, time integrity, and ownership clarity. The regulatory docking unit automatically anonymizes compliant regulatory data (such as gas leak alarms, insufficient fire sprinkler pressure alarms, and excessive drainage network liquid levels) according to the data format and transmission protocol (such as GB / T35648-2017 standard, MQTT or HTTPS) required by the urban lifeline regulatory platform (such as the Ministry of Housing and Urban-Rural Development's Urban Comprehensive Management Service Platform). This process removes sensitive information such as specific user names and precise house numbers, while retaining the time and location grid codes. The data is then pushed to the regulatory platform periodically or in real-time. The docking unit is also responsible for receiving instructions from the regulatory platform (such as requiring devices in a certain area to upload historical data) and forwarding them to the platform's internal system. The valuation interface unit provides two valuation modes: one is a built-in simple valuation model, which calculates a reference valuation based on factors such as the asset's historical average transaction price, data freshness, and equipment density: Valuation = Benchmark Price × (1 + 0.1 × Freshness Level + 0.05 × Spatial Coverage); the other is an open interface that allows access to third-party professional valuation models, such as market-based models developed by asset valuation companies. These models take into account parameters such as asset type, transaction volume, and quality level, and output a valuation range. The interface uses a unified data exchange format, and third-party models can be invoked by registering a callback URL. The multi-entity revenue sharing unit is implemented based on smart contracts. Whenever a digital asset transaction occurs (for example, a data product is purchased for P yuan), the ownership weights of all sensing devices corresponding to that asset within the corresponding time window are obtained. Let the total transaction amount be Total, then the revenue that the owner of each device i should receive is Total × The allocation ratio can be adjusted through pre-configured rules, such as the allocation to the device owner. Of the 70% of the revenue, the platform operator takes 20% and the equipment maintenance provider takes 10%. This unit calls the blockchain's revenue sharing contract to automatically transfer digital currency (or points) from the buyer's account to the recipient's account, and records the revenue sharing on the blockchain to ensure fairness and transparency.

[0028] In one implementation, the StarScan global self-organizing network communication module includes: Dynamic topology units are used to automatically discover devices and establish StarFlash NearLink communication links in scenarios with tens of thousands of concurrent terminals. The congestion control unit is used to dynamically adjust the transmit power and data retransmission strategy based on channel quality. The time synchronization unit is used to provide a microsecond-level time synchronization reference for all devices in the network, ensuring that the timestamps of multi-source data are consistent.

[0029] Specifically, Near Link is a new generation of wireless short-range communication standard with features such as low latency, high concurrency, and precise synchronization. This module uses Near Link technology to realize a self-organizing network of massive sensing devices. The dynamic topology unit adopts the dynamic centralized networking mode in the StarSpark protocol. In each area (such as a building or a section of pipeline), a StarSpark gateway (G node) is deployed. After all sensing devices (T nodes) are started, they automatically broadcast discovery requests, and the gateway responds and assigns short addresses. When devices move or signals change, the unit automatically adjusts the topology structure according to signal strength, load, etc., and supports relay transmission, that is, devices can be relayed to the gateway through other devices. Through the hybrid scheduling of Time Division Multiple Access (TDMA) and Frequency Division Multiple Access (FDMA), it can theoretically support a single gateway to access hundreds of thousands of concurrent terminals. The congestion control unit monitors the channel occupancy rate, retransmission rate, and packet loss rate of each communication node in real time. When the channel occupancy rate exceeds a threshold (e.g., 70%) or the retransmission rate increases, the following measures are dynamically taken: 1. Adjust the transmission power to reduce co-channel interference; 2. Change the modulation and coding scheme (MCS) to reduce the code rate and improve anti-interference capability; 3. Activate the backoff algorithm, prioritizing the transmission of high-priority data (e.g., gas leak alarms) and queuing or downsampling ordinary inspection data. Through the above mechanisms, the real-time and reliable transmission of critical data is ensured. The time synchronization unit is based on the high-precision time synchronization mechanism built into the StarScan protocol. The gateway node acts as the master clock and periodically sends synchronization frames (once per second). After receiving the frames, the sensing devices calibrate their local clocks, achieving synchronization accuracy down to the microsecond level. At the same time, all devices periodically perform absolute time calibration with the Network Time Protocol (NTP) server or the Global Navigation Satellite System (GNSS) to ensure that the timestamps of the reported data are consistent with UTC (Coordinated Universal Time). In this way, data from different devices and different regions can be accurately compared and fused for analysis in the same time coordinate system.

[0030] In one implementation, the national cryptographic full-link encryption module uses the SM2 elliptic curve public key cryptography algorithm for device authentication and digital signature, the SM3 cryptographic hash algorithm to generate data integrity verification values, and the SM4 block cipher algorithm to encrypt and transmit the sensed data payload. The blockchain-based full-domain evidence storage module uses a consensus mechanism to store device registration events, data collection hashes, ownership certificates, and their change records. The CIM 3D master control base module includes a city-level geographic information unit, a building information model unit, an IoT device spatial mapping unit, and a command and interaction unit.

[0031] Specifically, the SM2 algorithm is a national standard elliptic curve public-key cryptography algorithm (GB / T32918-2016). The platform generates an SM2 key pair for each sensing device (private key length 256 bits, public key is a point on the elliptic curve). The device's private key is stored in a secure chip, and the platform stores the public key. When reporting data, the device uses its private key to sign the entire data packet (including timestamp, location, and payload), and the platform uses the public key to verify the signature, confirming identity and integrity. Key management follows relevant standards and supports certificate authentication. The SM3 algorithm is a Chinese national cryptographic hash algorithm (GB / T32905-2016), which outputs a 256-bit hash value. It is used to calculate data integrity verification values, such as calculating the SM3 hash of concatenated data content as a fingerprint for on-chain evidence storage, and calculating the hash of the confirmation certificate, etc. The SM4 algorithm is a national standard block cipher algorithm (GB / T32907-2016), with a block length of 128 bits and a key length of 128 bits. During data transmission, SM4 is used to encrypt the sensed data payload to prevent eavesdropping. Key negotiation is completed through the SM2 key exchange protocol to ensure the security of the session key. The blockchain full-domain evidence storage module adopts conventional blockchain technology. The types of data stored include: device registration events (DID, public key, ownership entity, etc.), data collection hash (SM3 hash array for each batch uploaded to the chain), ownership certificates and their change records (hash of ownership certificates for each version). Each evidence storage transaction is marked with a timestamp and the signature of the transaction initiator. The on-chain query interface can return complete evidence storage proof, which can be used for judicial evidence. In the CIM 3D master control module, the city-level geographic information unit, based on the GIS engine, loads basic geographic data such as digital orthophotos, digital elevation models, administrative divisions, roads, and rivers of the city; the building information model unit is used to import BIM models of important buildings, bridges, and pipelines in the city to achieve a refined 3D display of components; the building information model unit also stores attribute information such as structural parameters, fire compartments, and pipeline routes of buildings; the IoT device spatial mapping unit binds the DID, real-time status, and historical data of each sensing device to its specific location (coordinates + elevation + angle) in 3D space. In the 3D scene, the devices are displayed as overlaid icons, and clicking the icon will pop up the device's real-time data card and historical curves; the command and interaction unit provides a visual command interface, supporting a single image display of the operating status of all devices (green normal, yellow warning, red alarm). When an alarm event occurs, it automatically locates the event location, displays information on surrounding devices, emergency plans, and the location of personnel in charge, and supports collaborative command functions such as voice calls and task assignment.

[0032] Example 2, please refer to Figure 2 This embodiment provides a method for data ownership confirmation and digital asset operation based on intelligent sensing, including the following steps: Step S1: Register, authenticate, and bind the unique identities of various sensing devices; Step S2: Multi-dimensional real-time data acquisition and edge preprocessing, with the addition of timestamps, spatial locations, and full-link national cryptographic signatures; Step S3: Construct a trusted data chain for the entire lifecycle of the equipment, storing at least the identity identifier, timestamp, spatial location, link signature, operating status data, compliance and regulatory data, energy efficiency management data, safety monitoring data, and maintenance records, and complete blockchain notarization; Step S4: Conduct technical rights confirmation based on device identity, timestamp, link signature, spatial location, and dynamic contribution, and generate rights confirmation certificates; Step S4 further includes: S41: Bind a DID identity, physical characteristics, and spatial location to each sensing device; S42: When collecting data, add timestamps, spatial locations, and full-link national cryptographic signatures; S43: Within the preset time window, calculate the following formula: Data weighting of individual sensing devices : in, This represents the total number of currently active sensing devices. To prevent division by zero decimals; For sensing devices The pass rate of national cryptographic signature verification within the time window is the ratio of the number of reports that passed verification to the total number of reports. For sensing devices Information entropy of reported data, according to calculate, For sensing devices The reported data value falls on the first Frequency within a quantization interval; Information entropy of all sensing devices within the current time window The arithmetic mean; For sensing devices Average on-chain latency of reported data; This is the arithmetic mean of the average on-chain latency of all sensing devices within the current time window; For sensing devices Spatial uniqueness contribution, according to Calculation, where For sensing devices Data feature vectors within the time window, Iterate through other devices whose spatial distance from the sensing device is less than a preset threshold. The number of neighboring devices; The arithmetic mean of the contributions of all sensing devices to the spatial uniqueness within the current time window; S44: Based on the weight of confirmation The system generates a dynamic ownership certificate with a unique ownership identifier by combining the device identity, timestamp, and link signature, and then hashes the certificate and stores it on the blockchain.

[0033] Step S5: Automatically generate corresponding standardized digital assets based on the confirmed operational status data, compliance and regulatory data, energy efficiency management data, and safety monitoring data; Step S6: Provide digital asset traceability, verification, and market-oriented operation services to external parties.

[0034] Specifically, the workflow of the above method consists of five stages: The first phase involves device registration and identity anchoring. When various sensing devices are connected for the first time, a globally unique distributed identity identifier is generated based on DID technology and the SM2 national cryptographic algorithm. This identifier is then technically bound to the device's physical characteristics, installation location (from the CIM base), and the owner. The registration information is then stored on the blockchain. The second stage involves data collection and trusted on-chain uploading. Devices collect data on operating status, compliance supervision, energy efficiency control, and safety monitoring at a set frequency. After filtering, deduplication, anomaly removal, and timestamp alignment are completed at the edge, microsecond-level timestamps, CIM spatial locations, and full-link SM2 signatures are added and uploaded through the StarShine global self-organizing network module. After the platform verifies the signature, it batch calculates SM3 hash values ​​for identity identifiers, timestamps, spatial locations, link signatures, and various sensing data and uploads them to the blockchain for evidence storage, forming an immutable full-lifecycle data chain. The third stage is dynamic contribution confirmation; within each preset time window, the data confirmation engine module calculates the dynamic confirmation weight based on four real-time indicators: signature verification pass rate, data information entropy, average on-chain latency, and spatial uniqueness contribution of each device; then the weight is bound to the device DID, timestamp, and data hash to generate cascaded dynamic confirmation certificates and put them on the chain. The fourth stage is standardized digital asset modeling; the digital asset modeling module automatically maps various types of data after ownership confirmation to asset attributes based on predefined asset models of various industries, generates standardized asset certificates that meet the requirements of data exchanges, including unique asset codes, ownership information, data source fingerprints, validity periods and value anchor hashes, and establishes a real-time update mechanism. The fifth stage is market-oriented operation; the operation service module provides asset inquiry, traceability verification, government supervision connection and value assessment services through interfaces; third parties can purchase assets or access the assessment model through interfaces; the multi-entity revenue sharing unit automatically calculates the revenue share of each data provider, platform operator and equipment owner based on dynamic rights confirmation weights, and completes automatic revenue sharing through smart contracts.

[0035] Compared to existing urban infrastructure monitoring platforms, this embodiment solves the problem of protocol heterogeneity by using multi-protocol adaptation units and standardized data conversion mechanisms to be compatible with protocols such as StarFlash, Wi-Fi, ZigBee, LoRa, Modbus, and industry-customized protocols. All events and collected data hashes from equipment installation, operation, maintenance to scrapping are stored on the blockchain for evidence. Combined with CIM spatiotemporal indexing, it achieves precise location and tamper-proof verification of any historical data. Based on the adaptive ownership weight of four-dimensional indicators of signature pass rate, information entropy, on-chain latency, and spatial uniqueness, it can objectively reflect the data quality and value contribution of each device at different times, upgrading ownership determination from static registration to dynamic quantification. The operation, compliance, energy efficiency, and safety data after ownership confirmation are automatically converted into standardized digital assets, supporting data trading, listing, trading, pledging, and financing, transforming data that was originally only used for supervision into quantifiable and operable assets.

[0036] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A data ownership confirmation and digital asset operation platform based on intelligent sensing, characterized in that: include: The unified sensing access module is used to realize protocol adaptation, identity registration, edge preprocessing and standardized data conversion of multi-source sensing devices; The full lifecycle data storage module is connected to the unified sensing access module and is used to store the identity identifier, timestamp, spatial location, link signature, operating status data, compliance supervision data, energy efficiency management data, safety monitoring data and maintenance records of the sensing device, forming an immutable full lifecycle trusted data chain; The data ownership confirmation engine module is connected to the full lifecycle data storage module and is used to perform multi-dimensional trusted binding based on the identity identifier, timestamp, spatial location and link signature to generate ownership confirmation certificate with unique ownership identifier. The digital asset modeling module, connected to the data ownership confirmation engine module, is used to convert the confirmed operational status data, compliance supervision data, energy efficiency control data, and safety monitoring data into standardized digital assets and establish a real-time update mechanism. The operation service module, connected to the digital asset modeling module, is used to provide standardized interfaces for asset query, traceability verification, regulatory docking, and value assessment. In addition, the StarSpark global self-organizing network communication module, the national cryptographic full-link encryption module, the blockchain global evidence storage module, and the CIM three-dimensional master control base module are respectively connected to the above modules.

2. The platform according to claim 1, characterized in that, The unified perception access module includes: Multi-protocol adapter unit for compatibility with StarFlash, Wi-Fi, ZigBee, LoRa, Modbus and industry-customized protocols; The device identity registration unit is used to generate a globally unique identity identifier based on DID technology for each of the sensing devices, and to complete key distribution and binding; The edge data preprocessing unit is used to filter, deduplicate, remove anomalies, and align timestamps on the raw sensing data. The protocol standardization conversion unit is used to convert data from different protocols into a unified internal data format. The internal data format includes at least device identification, timestamp, spatial location, national cryptographic link signature, and sensing data payload.

3. The platform according to claim 2, characterized in that, The full lifecycle data storage module includes: The equipment history storage unit is used to record all events throughout the entire process of equipment installation, commissioning, operation, maintenance, calibration and scrapping; The on-chain evidence storage unit is used to store device identity, timestamp, spatial location, link signature, operating status data, compliance and regulatory data, energy efficiency control data, safety monitoring data, maintenance records, and the hash values ​​of the above data on the blockchain through the blockchain full-domain evidence storage module. The spatiotemporal indexing unit is used to bind three-dimensional spatial coordinates and timestamps to each piece of data based on the CIM three-dimensional master control base module, forming a traceable spatiotemporal data chain.

4. The platform according to claim 3, characterized in that, The data ownership confirmation engine module includes: The device identity binding unit is used to bind the device's globally unique identity identifier with physical device characteristics, installation location, and owner; The spatiotemporal information fusion unit is used to generate an irrefutable spatiotemporal fingerprint by combining timestamps, spatial locations, and data content. The link signature verification unit is used to verify the national cryptographic signature of the entire link from the sensing end to the platform end to ensure that the data has not been tampered with; The dynamic contribution calculation unit is used to calculate the data weighting of each sensing device within a preset time window. This unit is calculated using the following formula: in, This represents the total number of currently active sensing devices. To prevent division by zero decimals; For sensing devices The national cryptographic signature verification pass rate within the time window is the ratio of the number of reports that passed verification to the total number of reports. For sensing devices Information entropy of reported data, according to calculate, For sensing devices The reported data value falls on the first Frequency within a quantization interval; Information entropy of all sensing devices within the current time window The arithmetic mean; For sensing devices Average on-chain latency of reported data; This is the arithmetic mean of the average on-chain latency of all sensing devices within the current time window; For sensing devices Spatial uniqueness contribution, according to Calculation, where For sensing devices Data feature vectors within the time window, Iterate through other devices whose spatial distance from the sensing device is less than a preset threshold. The number of neighboring devices; The arithmetic mean of the contributions of all sensing devices to the spatial uniqueness within the current time window; The certificate generation unit is used to generate the certificate based on the certificate weight. In addition, device identification, timestamp, and data hash are used to generate cascaded dynamic ownership certificates.

5. The platform according to claim 4, characterized in that, The digital asset modeling module includes: The asset definition unit is used to define the asset type, unit of measurement, and quality grade of the data after ownership confirmation in accordance with industry standards. The automatic mapping unit is used to automatically map real-time perceived data streams into asset attribute values ​​according to preset rules; The real-time update unit is used to synchronously update the value index and certificate information of digital assets when data is refreshed; The asset certificate generation unit is used to generate standardized digital asset certificates that meet the requirements of the data exchange, including unique asset codes, ownership information, data source fingerprints, validity periods, and value anchor hashes.

6. The platform according to claim 5, characterized in that, The operation service module includes: The asset query interface unit is used to provide RESTful APIs or streaming data interfaces to the outside world, supporting the retrieval of digital assets by device, time, region, and asset type; The traceability and verification unit is used to verify the authenticity of the source, the integrity of the time, and the clarity of ownership of any piece of perceived data through the blockchain's stored evidence hash value; The regulatory docking unit is used to submit compliant data to the city lifeline regulatory platform in accordance with preset data anonymization rules; The valuation interface unit is used to connect to third-party valuation models and output a reference valuation range for digital assets. Multi-entity revenue sharing unit, used to determine the weight of each sensing device. The system automatically calculates and allocates the revenue share of each data provider, platform operator, and equipment owner based on the total transaction amount of assets.

7. The platform according to claim 1, characterized in that, The StarScan global self-organizing network communication module includes: Dynamic topology units are used to automatically discover devices and establish StarFlash Near Link communication links in scenarios with tens of thousands of concurrent terminals. The congestion control unit is used to dynamically adjust the transmit power and data retransmission strategy based on channel quality. The time synchronization unit is used to provide a microsecond-level time synchronization reference for all devices in the network, ensuring that the timestamps of multi-source data are consistent.

8. The platform according to claim 1, characterized in that, The national cryptographic full-link encryption module uses the SM2 elliptic curve public key cryptography algorithm for device authentication and digital signature, the SM3 cryptographic hash algorithm to generate data integrity verification values, and the SM4 block cipher algorithm to encrypt and transmit the sensed data payload. The blockchain-based global evidence storage module uses a consensus mechanism to store device registration events, data collection hashes, ownership certificates, and their change records. The CIM 3D master control base module includes a city-level geographic information unit, a building information model unit, an IoT device spatial mapping unit, and a command and interaction unit.

9. A method for data ownership confirmation and digital asset operation based on intelligent sensing, characterized in that, Includes the following steps: Step S1: Register, authenticate, and bind the unique identities of various sensing devices; Step S2: Multi-dimensional real-time data acquisition and edge preprocessing, with the addition of timestamps, spatial locations, and full-link national cryptographic signatures; Step S3: Construct a trusted data chain for the entire lifecycle of the equipment, storing at least the identity identifier, timestamp, spatial location, link signature, operating status data, compliance and regulatory data, energy efficiency management data, safety monitoring data, and maintenance records, and complete blockchain notarization; Step S4: Conduct technical rights confirmation based on device identity, timestamp, link signature, spatial location, and dynamic contribution, and generate rights confirmation certificates; Step S5: Automatically generate corresponding standardized digital assets based on the confirmed operational status data, compliance and regulatory data, energy efficiency management data, and safety monitoring data; Step S6: Provide digital asset traceability, verification, and market-oriented operation services to external parties.

10. The method according to claim 9, characterized in that, Step S4 further includes: S41: Bind a DID identity, physical characteristics, and spatial location to each sensing device; S42: When collecting data, add timestamps, spatial locations, and full-link national cryptographic signatures; S43: Within the preset time window, calculate the following formula: Data weighting of individual sensing devices : in, This represents the total number of currently active sensing devices. To prevent division by zero decimals; For sensing devices The national cryptographic signature verification pass rate within the time window is the ratio of the number of reports that passed verification to the total number of reports. For sensing devices Information entropy of reported data, according to calculate, For sensing devices The reported data value falls on the first Frequency within a quantization interval; Information entropy of all sensing devices within the current time window The arithmetic mean; For sensing devices Average on-chain latency of reported data; This is the arithmetic mean of the average on-chain latency of all sensing devices within the current time window; For sensing devices Spatial uniqueness contribution, according to Calculation, where For sensing devices Data feature vectors within the time window, Iterate through other devices whose spatial distance from the sensing device is less than a preset threshold. The number of neighboring devices; The arithmetic mean of the contributions of all sensing devices to the spatial uniqueness within the current time window; S44: Based on the aforementioned weight determination The system generates a dynamic ownership certificate with a unique ownership identifier by combining the device identity, timestamp, and link signature, and then hashes the certificate and stores it on the blockchain.

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