Block chain-based three-dimensional parking space access record evidence storage and traceability system

Abstract

The invention provides a three-dimensional parking space access record evidence storage and traceability system based on a block chain, and relates to the technical field of parking space access record evidence storage. Comprising a data acquisition module for acquiring multi-dimensional parking lot data in real time and preprocessing the acquired data; the block chain evidence storage module verifies a standard, packages the standard to generate a chain block, stores the chain block to an alliance chain node by using a Raft algorithm, links a video data hash value and parking lot access record data, and stores a video in an OSS; the business logic automation module is used for automatically associating the whole process to generate a complete record based on the chain type block data and the video association information; and the traceability query module supports any condition query, calls a complete record and forms a complete evidence chain in combination with the distributed block data. According to the invention, by calculating the hash values of the parking lot data and the video data, the whole-process record is calculated, and the quality and credibility of the overall operation management of the three-dimensional parking space are improved.

Description

Technical Field

[0001] This invention relates to the field of parking space access record storage technology, and in particular to a blockchain-based three-dimensional parking space access record storage and traceability system. Background Technology

[0002] Traditional systems have limited dimensions, often recording only basic information such as license plate numbers and approximate entry and exit times. They struggle to comprehensively collect multi-dimensional data, including vehicle parking accuracy, equipment operating status, and full-process video recordings. This results in insufficient evidence for traceability, and the accuracy and timeliness of the data are poor, prone to bias and omissions. Traditional systems often rely on centralized storage, making them susceptible to tampering; storage device failures can lead to data loss. Blockchain systems, however, employ a consortium blockchain architecture and consensus mechanisms to achieve distributed backup, eliminating such risks. Furthermore, traditional methods of managing video data are inconvenient, unlike blockchain systems which can balance relevance with secure and convenient storage. Summary of the Invention

[0003] This invention provides a blockchain-based system for storing and tracing records of access to three-dimensional parking spaces, which addresses the shortcomings of existing technologies in terms of the timeliness and accuracy of early warnings due to the single warning threshold.

[0004] On the one hand, this invention provides a blockchain-based system for storing and tracing records of access to multi-level parking spaces, including: The data acquisition module is used to collect multi-dimensional parking lot data in real time, preprocess the collected data, and obtain a hash value dataset.

[0005] The equipment adaptation module is used to develop dedicated adaptation interfaces for the communication protocols of different types of automated parking systems, and automatically converts the hash value dataset format to standard hash data.

[0006] The blockchain evidence storage module verifies standard hash data and packages it into chain blocks. It uses the Raft algorithm to store the chain blocks to consortium blockchain nodes, puts the video data hash value and parking lot access record data on the blockchain, and stores the video in OSS to obtain distributed block data and video-related data.

[0007] The business logic automation module, based on chained block data and video association information, automatically associates the entire process to form records, triggers alarms, calculates costs, and generates complete records, logs, and details.

[0008] The traceability query module supports querying based on any conditions, retrieving records from smart contracts, and combining them with distributed block data to form a complete chain of evidence.

[0009] According to the blockchain-based three-dimensional parking space access record storage and traceability system provided by the present invention, the specific steps for obtaining the hash value dataset in the data acquisition module are as follows: The raw data acquisition unit is used to collect basic vehicle information, equipment operating status, parking space occupancy, and video of the storage and retrieval process in real time, obtaining multi-dimensional raw data.

[0010] The raw data preprocessing unit performs format standardization conversion according to unified specifications, filters out duplicate and abnormal information, and obtains standardized datasets and corresponding video clips.

[0011] The hash value calculation unit is used to apply hash algorithms to the standardized dataset and each video segment to calculate hash values, generate hash results corresponding to the data, and obtain a hash value dataset.

[0012] According to the blockchain-based three-dimensional parking space access record storage and traceability system provided by the present invention, the specific steps for calculating the hash value of the standardized dataset are as follows: The register is initialized by assigning a value to the register according to the fixed initial hash value preset by the hash algorithm.

[0013] The hash value dataset byte stream is divided into blocks according to the fixed length of the hash algorithm to obtain hash data blocks.

[0014] The hash data block is subjected to multiple rounds of compression function calculations to update the value of the initialized register. During the calculation process, intermediate variables are first generated based on different conditions through message expansion, and then the register state is continuously updated through the main compression loop with the help of logical operations to obtain the updated register.

[0015] After processing all data blocks, the updated register values ​​are concatenated in order to obtain the first set of standardized hash values.

[0016] According to the blockchain-based three-dimensional parking space access record storage and traceability system provided by the present invention, the specific steps for calculating the hash value of video segments are as follows: Convert the segmented video clips into hash values ​​to be calculated in byte stream format.

[0017] The hash buffer of the hash algorithm is initialized, the video segment byte stream is divided into blocks of fixed length, the parts that are not long enough are padded, the length information of the original video segment is recorded, and the processed video data block is obtained.

[0018] The input video data blocks are processed, and multiple rounds of iterative calculations are performed according to the compression function calculation rules of the hash algorithm. The values ​​of the registers are continuously updated. After all video data blocks have been processed, the register values ​​are concatenated in order to obtain the hash value dataset two.

[0019] The blockchain-based automated parking space access record storage and traceability system provided by the present invention includes an equipment adaptation module comprising: The protocol information identification unit is used to collect communication protocol information of different types of automated parking systems, identify the protocol type and data transmission rules of various types of equipment, and output a list of equipment communication protocol types.

[0020] The adapter interface development unit is used to develop corresponding dedicated adapter interfaces for each protocol's syntax and data structure based on the device communication protocol type list, clarify the data interaction logic between the interface and the device, and between the interface and subsequent modules, and output a set of dedicated adapter interfaces.

[0021] The hash value dataset access unit is used to take the hash value dataset as input data for a dedicated adapter interface and output the hash value dataset to be formatted.

[0022] The data format conversion unit is used to perform protocol parsing on the hash value dataset to be converted using a dedicated set of adaptation interfaces, convert it into a standard data format that conforms to the evidence storage system specifications, and output preliminary standard hash data.

[0023] The standard data verification unit is used to verify standard hash data and output standard hash data.

[0024] According to the blockchain-based automated parking space access record storage and traceability system provided by the present invention, the blockchain storage module includes: The data verification unit is used to verify the data integrity, hash value matching degree, and logical correlation of a dataset containing the original data hash values.

[0025] The data block generation unit is used to package the verified dataset according to the block structure to form a chain of blocks that can be uploaded to the blockchain.

[0026] The distributed consensus unit is used to synchronize and store blocks to all nodes of the consortium blockchain using the Raft algorithm.

[0027] The data association unit is used to process excessively large video files by using video data hash values ​​to be uploaded to the blockchain and video files to be stored in a distributed manner.

[0028] According to the blockchain-based three-dimensional parking space access record storage and traceability system provided by the present invention, the data block generation unit includes: The block structure definition sub-unit presets the standard structure of blockchain blocks and outputs a standardized block structure template.

[0029] The data integration and packaging subunit is used to classify the dataset according to the verification dataset and the block structure template, populate the block body, write the timestamp and the hash value of the previous block in the block header, and output the initial block.

[0030] The blockchain-style associated sub-unit is used to calculate the hash value of the current block based on the initial block, write it into the block header of the next block, form a chain association, and output a chain block that can be uploaded to the chain.

[0031] According to the blockchain-based three-dimensional parking space access record storage and traceability system provided by the present invention, the distributed consensus unit includes: In the leader election subunit, consortium chain nodes periodically initiate elections, using a heartbeat mechanism and voting logic to determine the leader node responsible for block synchronization, and output the identifier of the elected leader node.

[0032] The log replication subunit, based on the leader node identifier and the chained blocks, has the leader node send the blocks sequentially to all follower nodes in the consortium chain. After the follower nodes confirm receipt, they return a response to the leader and output a confirmation message that the block replication is complete.

[0033] The security assurance subunit is used to verify whether the block content stored by all nodes is consistent based on the confirmation information of block replication completion. When more than half of the nodes confirm consistency, the block is marked as committed and the block data of distributed storage is output.

[0034] The blockchain-based automated parking space access record storage and traceability system provided by this invention includes a business logic automation module comprising: The data access unit is used to adapt the data format according to the chained block data and video association information to obtain standard block and video association data packets.

[0035] The end-to-end information association unit is used to extract vehicle information, equipment status, parking space data, timestamps and video hash values ​​from standard blocks and video-associated data packets, automatically associate information across all stages according to the access timeline, and output preliminary vehicle access records.

[0036] The anomaly rule matching unit is used to compare the device data in the preliminary vehicle access record with the parking time to determine whether it is greater than a preset time. If it is, an anomaly alarm log is generated, and the anomaly marked access record and anomaly alarm log are output.

[0037] The parking fee calculation unit is used to extract the vehicle entry time and exit time from the abnormal entry and exit records, automatically calculate the parking fee according to the charging standard, generate fee details, and output complete entry and exit records with fee details and abnormal alarm logs.

[0038] The blockchain-based automated parking space access record storage and traceability system provided by this invention includes a traceability query module comprising: The query condition receiving and processing unit is used to perform format validation and standardization processing on any query condition input by the user, and output standard query parameters.

[0039] The smart contract record retrieval unit is used to accurately match the associated complete access records, abnormal alarm logs, and fee details stored in the smart contract according to standard query parameters, retrieve the target record set corresponding to the query conditions, and output the associated records.

[0040] The distributed block data acquisition and integration unit is used to acquire distributed storage chain block data corresponding to associated records from each node of the consortium blockchain, and integrate the chain block data with the associated records by aligning the fields through the unique identifier in the record, and output the integrated block contract data.

[0041] The evidence chain information supplement unit is used to extract the video hash value from the integrated data of the block contract, associate the video data association information, supplement the acquisition path and verification method of the video file, and output a preliminary evidence chain.

[0042] The evidence chain verification and output unit is used to verify the completeness and logical consistency of the preliminary evidence chain. After the verification is passed, the data is sorted out according to the access timeline and the complete evidence chain is output.

[0043] The blockchain-based three-dimensional parking space access record storage and traceability system provided by this invention calculates the entire process record by calculating the hash value of parking lot data and video data.

[0044] The beneficial effects achieved are as follows: This invention comprehensively collects information related to multi-level parking spaces using multiple types of sensing devices, covering various dimensions such as basic vehicle information, equipment operating status, parking space status, and video recordings of the access process. Coupled with millisecond-accurate timestamp recordings, every detail of the access process is precisely captured, providing extremely detailed and reliable data support for subsequent evidence preservation and traceability. Simultaneously, the invention utilizes hash algorithms to calculate the hash value of the data and standardizes the original data, ensuring data integrity, uniqueness, and format standardization. This effectively prevents data tampering and facilitates rapid and accurate subsequent verification and retrieval of data.

[0045] In terms of system compatibility, it has a dedicated equipment adaptation module that can develop adaptable interfaces for various equipment communication protocols in different multi-level parking lots, converting data into standard formats, overcoming compatibility problems caused by equipment differences, ensuring that the system can operate stably in diverse parking lot environments, and is widely applicable to various practical scenarios.

[0046] By employing a consortium blockchain architecture combined with the Raft consensus mechanism for evidence storage, and involving multiple nodes such as parking lot management, regulatory agencies, and third-party witnessing institutions, distributed data storage is achieved. This distributed backup model eliminates the risk of single points of failure, fundamentally ensuring the security and immutability of the stored data, and guaranteeing the authenticity and reliability of the records over long-term storage. For video data, a hash value-based on-chain and distributed storage approach is adopted, which not only ensures the correlation between video and other recorded data but also solves the problems of inconvenient storage and easy loss of large amounts of video data, further improving the content of the evidence storage.

[0047] The automation of business logic has brought great convenience. The system can automatically sort out the entire process based on chained block data and video correlation information, link each link to form a complete record, and can also monitor and automatically identify equipment abnormalities, overtime parking and other situations in real time, automatically trigger alarms and accurately calculate parking fees, generate detailed information, greatly improve management efficiency, reduce the tediousness of manual operation and possible errors, and make the management of the entire multi-level parking space more standardized and orderly.

[0048] The traceability query function allows users to perform multi-dimensional searches based on various conditions, enabling them to quickly and accurately retrieve the required storage and retrieval records and other relevant information. It can also integrate data from various aspects to form a complete chain of evidence and supports exporting to a specified format. Whether it is for parking lot operators to conduct internal management and audits, car owners to have questions about storage and retrieval and need to trace and verify, or regulatory departments to perform their supervisory duties, they can obtain strong and comprehensive evidence, effectively protecting the rights and interests of all parties and improving the overall quality and credibility of the operation and management of multi-level parking spaces. Attached Figure Description

[0049] To more clearly illustrate the technical solutions in this 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 some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0050] Figure 1 This is a schematic diagram of a blockchain-based three-dimensional parking space access record storage and traceability system provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the process for calculating the hash value of a standardized dataset in this invention. Detailed Implementation

[0051] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0052] The following is combined with Figures 1-2 This invention describes a blockchain-based system for storing, recording, and tracing access to three-dimensional parking spaces.

[0053] like Figures 1-2 As shown in the embodiment of the present invention, a blockchain-based system for storing, recording, and tracing access to multi-level parking spaces includes: Data Acquisition Module: Real-time acquisition of multi-dimensional data. Pressure sensors and infrared sensors are installed at the bottom of each automated parking space to detect whether the space is occupied and the accuracy of vehicle parking, determining whether the vehicle is completely parked within the space area and whether it exceeds the boundary, etc. At the same time, it is associated with the corresponding parking space number and records the time nodes of parking space status changes to generate parking space status data.

[0054] By installing high-definition license plate recognition cameras and panoramic cameras at key locations such as the parking lot entrance, passageways on each floor, around parking spaces, and exit, the high-definition license plate recognition cameras are responsible for collecting basic information such as license plate numbers, vehicle colors, and vehicle models of vehicles entering and leaving the parking lot. The panoramic cameras record the entire video process of a vehicle from entering the parking lot, through equipment handling, to parking in a space, and then retrieving and driving out of the parking lot. The video is segmented and stored according to different storage and retrieval stages to obtain basic vehicle information data and storage and retrieval process video data.

[0055] In response to the interconnected nature of multi-level parking garages, various types of sensing devices are deployed to collect multi-dimensional parking garage data across the entire process, including: Vehicle basic information collection involves using a high-definition license plate recognition camera to capture the license plate number, vehicle color, and vehicle model, and simultaneously generating a timestamp accurate to the millisecond.

[0056] Equipment operation status is collected by deploying vibration sensors, position sensors, and current sensors on the handling equipment in the multi-level parking garage to collect the equipment's operating status, operation commands, and operation time.

[0057] Parking space status data collection involves deploying pressure sensors and infrared sensors at the bottom of each multi-level parking space to collect data on the vacancy / occupancy status of the parking space, whether the vehicle is parked properly, and associating this data with the parking space number.

[0058] The video process is captured by deploying panoramic cameras along the equipment's operating path and around the parking space to record a complete video stream of the vehicle entering, being moved, parked, and retrieved. The video clips are then linked to the corresponding access records as visual evidence.

[0059] All parking lot data is preprocessed through an edge computing gateway to generate a unique raw data hash value.

[0060] Establish a unified standard for data storage in multi-level parking garages, clearly defining the format standards for various types of data. For example, vehicle information, equipment data, and parking space data should be uniformly organized into JSON format. The collected multi-dimensional raw data should be formatted according to this standard to remove duplicate, erroneous, or obviously abnormal data, thus completing the data standardization process and outputting a hash value dataset.

[0061] The raw data acquisition unit is used to collect basic vehicle information, equipment operating status, parking space occupancy, and video of the storage and retrieval process in real time, obtaining multi-dimensional raw data.

[0062] The raw data preprocessing unit performs format standardization conversion according to unified specifications, filters out duplicate and abnormal information, and obtains standardized datasets and corresponding video clips.

[0063] The hash value calculation unit is used to apply hash algorithms to the standardized dataset and each video segment to calculate hash values, generate hash results corresponding to the data, and obtain a hash value dataset.

[0064] The specific steps for calculating the hash value of a standardized dataset are as follows: The hash algorithm has eight 32-bit registers, which are initially set to a fixed initial hash value.

[0065] The hash value dataset byte stream is divided into blocks of fixed length according to the hash algorithm. If the last block of data does not reach the fixed length, a padding operation is performed to make it meet the length requirement. Padding involves adding a 1 bit followed by several 0 bits, and the length information of the original dataset is recorded at the end of the data block, resulting in a hash data block. Specifically, the dataset byte stream is divided into blocks of 512 bits each. If the last block is less than 512 bits, a padding operation is performed to make it 512 bits. The padding rule is to add a 1 bit first, then several 0 bits, until the length requirement is met, and the original data length is recorded in the last 64 bits.

[0066] For each 512-bit data block, 64 rounds of compression function calculations are performed to update the register values. Message expansion calculates intermediate variables based on different conditions. The main compression loop updates the registers through a series of logical operations, including XOR, AND, OR, NOT, cyclic shift, and addition.

[0067] After processing all data blocks, the final register values ​​are concatenated in order to obtain the hash value of the entire standardized dataset, which is then output as a 32-byte hexadecimal string.

[0068] The specific steps for calculating the hash value of video data are as follows: Retrieve video segments stored in sections according to the access stage, and treat them as input data in byte stream form to calculate hash values.

[0069] The initialization and block processing are the same as calculating the hash value for the standardized dataset. First, the hash buffer of the hash algorithm is initialized. Then, the video segment byte stream is divided into blocks of 512 bits each. For the parts that are less than 512 bits, the padding operation is performed, and the original video segment length information is recorded.

[0070] The compression function iterative calculation and hash value output process performs 64 rounds of iterative calculations according to the hash algorithm's compression function calculation rules for each 512-bit video data block, updating the register values ​​accordingly. After processing all video segment data blocks, the final register values ​​are concatenated sequentially to obtain the hash value of the video segment, which is also output as a 32-byte hexadecimal string. This hash value is used to uniquely identify the video segment and verify whether it has been tampered with.

[0071] The equipment adaptation module is used to develop dedicated adaptation interfaces for the communication protocols of different types of automated parking systems, and automatically converts the hash value dataset format to standard hash data.

[0072] The protocol information identification unit is used to collect communication protocol information of different types of automated parking systems, identify the protocol type and data transmission rules of various types of equipment, and output a list of equipment communication protocol types.

[0073] The adapter interface development unit is used to develop corresponding dedicated adapter interfaces for each protocol's syntax and data structure based on the device communication protocol type list, clarify the data interaction logic between the interface and the device, and between the interface and subsequent modules, and output a set of dedicated adapter interfaces.

[0074] The hash value dataset access unit is used to take the hash value dataset as input data for a dedicated adapter interface and output the hash value dataset to be formatted.

[0075] The data format conversion unit is used to perform protocol parsing on the hash value dataset to be converted using a dedicated set of adaptation interfaces, convert it into a standard data format that conforms to the evidence storage system specifications, and output preliminary standard hash data.

[0076] The standard data verification unit is used to verify standard hash data and output standard hash data.

[0077] The blockchain evidence storage module verifies standards and packages them into chain blocks. It uses the Raft algorithm to store the chain blocks to the consortium blockchain node, puts the video data hash value and parking lot access record data on the blockchain, and stores the video in OSS to obtain distributed block data and video-related data.

[0078] This module adopts a consortium blockchain architecture to achieve distributed and tamper-proof data storage. The specific process is as follows: The data verification unit is used to verify the dataset with raw data hash values ​​output by the data acquisition module. It performs strict consistency verification on each data item in the dataset, checks the integrity, accuracy and logical correlation between data, such as verifying whether the vehicle entry and exit time matches the equipment operation record, and whether the video content corresponding to the video hash value matches the vehicle access process, to ensure the reliability of data quality before it enters the storage stage.

[0079] The integrity verification subunit is used to check whether the core fields in the dataset are complete, remove invalid data with missing key information, and output a candidate dataset with complete fields.

[0080] The hash value matching and verification subunit is used to extract the original data hash values ​​from the candidate dataset with complete receiving fields, recalculate the hash values ​​of the candidate dataset content, compare whether the two results are consistent, filter out the valid datasets with hash matching, and output the datasets that pass the hash verification.

[0081] The logical correlation verification subunit is used to combine the logic of the parking and retrieval process of the multi-level parking lot to verify the rationality of the correlation between data, eliminate logically contradictory data, and output the final dataset that has passed the full verification.

[0082] The data block generation unit is used to package vehicle information, device status, parking space information, timestamps, and video clip hash values ​​into a single data block. Each block contains the hash value of the previous block, forming a chain structure. After successful verification, the data is packaged according to predetermined rules and data structures, integrating various vehicle access-related information and video data hash values ​​to generate a chain of blocks.

[0083] The distributed consensus unit utilizes the Raft consensus mechanism to synchronously push generated chained blocks to all nodes of the consortium blockchain. These nodes include parking lot managers, regulatory agencies, and third-party witnessing institutions. Each node stores the received blocks, achieving distributed backup of data across multiple nodes and eliminating single points of failure and data tampering risks. Through a practical Byzantine fault-tolerant consensus mechanism, the consortium blockchain nodes jointly confirm the validity of the blocks. After confirmation, the blocks are synchronously stored in the local ledgers of all nodes, achieving one-time on-chain backup and multiple backups, eliminating the risk of single-point tampering or data loss.

[0084] Special processing and association of video data: Considering the large size of video data, a combination of hash value uploading to the blockchain and distributed storage of video files is adopted. The hash value of the video clip is uploaded to the blockchain along with other data, while the video file is stored on the OSS (Object Storage Service) distributed storage network. The hash value uploaded to the blockchain allows for quick location and verification of the video file's integrity. Given the large volume of video data, a combination of uploading the video hash value to the blockchain and storing the video file on the OSS distributed storage network is used. The hash value of the video data is packaged together with other data into a blockchain block for storage, facilitating rapid verification of the video's integrity and relevance later.

[0085] The video files themselves are stored in the OSS (Object Storage Service) distributed storage network. OSS assigns a unique Content Identifier (CID) to each video file using a content addressing model and stores video file fragments across multiple OSS nodes. This avoids video loss due to the failure of a single storage node and allows for quick location and retrieval of video files using the CID. The hash value uploaded to the blockchain can accurately locate the corresponding video file, thus forming a chain of distributed storage block data and video data association information.

[0086] The business logic automation module, based on chained block data and video correlation information, automatically links the entire process to form records, triggers alarms, calculates costs, and generates complete records, logs, and details. This includes: The data access unit is used to process chained block data and video association information. The chained block data includes core business data such as basic vehicle information, equipment operating status, parking space information, and timestamps, while the video association information is the mapping relationship between video hash values ​​and OSS storage addresses. This unit first performs compatibility adaptation on the formats of the two types of data, such as unifying the encoding format of different fields in the block data to the system's preset standard format. At the same time, it verifies the integrity of the data to ensure that subsequent units can directly call this data. Finally, it outputs a standardized block and video association data package containing complete business data and video association mappings, providing input basis for the end-to-end information association unit.

[0087] After receiving the standardized blocks and video-related data packets output by the data access unit, the end-to-end information association unit extracts key information from the data packets: vehicle information, equipment status, parking space information, timestamp, and video hash value. Subsequently, using the "unique access order number" as the core link, this unit automatically associates the scattered information according to the timeline logic of vehicle access. For example, it associates "10:05 vehicle enters" with "10:06 elevator S1 receives parking instruction" and "10:08 parking space No. 2 on the 3rd floor becomes occupied" as information nodes in the same access process, ultimately forming a preliminary integrated vehicle access record containing information from all stages, which is then passed to the anomaly rule matching unit.

[0088] The anomaly rule matching unit receives the preliminary integrated vehicle access record prototype from the end-to-end information association unit and then calls the system's preset anomaly rule library—which includes equipment anomaly rules and overdue parking rules. It compares the data in the record prototype with the rule library one by one: if it detects that "the operating current of elevator S1 at 10:07 is 15A, exceeding the normal range of 8-12A," the equipment anomaly rule is triggered. If it finds that "a vehicle has been parked from 10:08 to 15:08 and has not left, exceeding the 4-hour free parking period," the overdue parking rule is triggered. Each time an anomaly rule is triggered, this unit automatically generates an anomaly alarm log, which includes the time of the anomaly, the information of the involved equipment / vehicle, the anomaly type, and a detailed description of the anomaly. Simultaneously, it adds an anomaly marker to the corresponding vehicle access record prototype and finally outputs the access record with the anomaly marker and the anomaly alarm log, sending it to the parking fee calculation unit.

[0089] The parking fee calculation unit receives access records with anomaly markers from the anomaly rule matching unit. It first extracts key time information from the records—vehicle entry time (e.g., 10:08) and exit time (e.g., 15:30)—to calculate the actual parking duration (5 hours and 22 minutes). Based on the parking fee standard (e.g., the first hour is free, and each subsequent hour costs 5 yuan, with any fraction of an hour counted as a full hour; peak hours 17:00-20:00 cost 8 yuan per hour), the unit calculates the fee by combining the parking duration with the fee standard: if the parking period does not involve peak hours, 5 hours and 22 minutes is counted as 6 hours, and after deducting the first hour, the fee is 5 hours × 5 yuan = 25 yuan. After calculation, this unit generates a detailed fee breakdown, including parking duration, fee standard basis, fee breakdown for each time period, and total fee amount. It also associates and binds the fee breakdown with the access records with anomaly markers and the anomaly alarm log, finally outputting a complete access record with fee details and the anomaly alarm log, which is then passed to the record integration and output unit.

[0090] Based on the complete access records with detailed fee information and the anomaly alarm logs, these three documents are first integrated according to the system's unified format specifications to ensure consistent field order and accurate information correspondence. Video association information is extracted from the standardized blocks and video association data packets transmitted by the data access unit. The mapping relationship between the video hash value and the IPFS storage address is added to the corresponding access record, allowing the record to be directly associated with video evidence of the access process. The integrated information undergoes final verification. Once confirmed to be correct, the final associated complete access records, anomaly alarm logs, and fee details are output for the traceability query module to use, supporting subsequent user queries and evidence chain generation operations.

[0091] The traceability query module provides users with convenient and accurate traceability query functions, supporting multi-dimensional retrieval and evidence chain export, specifically including: The query condition receiving and processing unit is used to perform format validation and standardization processing on any query condition input by the user, and output standardized query parameters.

[0092] Smart Contract Record Retrieval Unit: Receives standardized query parameters, calls the interface of the smart contract module, and performs precise matching in the associated complete access records, abnormal alarm logs, and fee details stored in the smart contract based on the parameters. It retrieves the target record set corresponding to the query conditions and outputs the successfully retrieved associated smart contract records.

[0093] Distributed Block Data Acquisition and Integration Unit: Receives successfully retrieved smart contract association records, obtains the number of distributed storage chain blocks corresponding to the record from each node of the consortium blockchain, integrates the chain block data with the smart contract association records by field alignment using the unique identifier in the record, and outputs the integrated block contract data.

[0094] Evidence Chain Information Supplement Unit: Receives integrated data from the block contract, extracts video hash values ​​from the data, associates video data association information generated by the data association unit, supplements the acquisition path and verification method of the video file, and outputs a preliminary evidence chain containing video association information.

[0095] Evidence Chain Verification and Output Unit: Receives a preliminary evidence chain containing video-related information, verifies data integrity, checks for missing key timestamps, device log entries, and logical consistency. After verification, it organizes the data according to the access timeline to form a complete evidence chain containing basic information, device logs, cost details, and video paths. It supports exporting to a specified format and outputs the final usable complete evidence chain.

[0096] In summary, this embodiment provides a blockchain-based system for storing and tracing records of access to multi-level parking spaces. It calculates the hash values ​​of parking lot data and video data to record the entire process. The beneficial effects achieved are: This invention comprehensively collects information related to multi-level parking spaces using multiple types of sensing devices, covering various dimensions such as basic vehicle information, equipment operating status, parking space status, and video recordings of the access process. Coupled with millisecond-accurate timestamp recordings, every detail of the access process is precisely captured, providing extremely detailed and reliable data support for subsequent evidence preservation and traceability. Simultaneously, the invention utilizes hash algorithms to calculate the hash value of the data and standardizes the original data, ensuring data integrity, uniqueness, and format standardization. This effectively prevents data tampering and facilitates rapid and accurate subsequent verification and retrieval of data.

[0097] In terms of system compatibility, it has a dedicated equipment adaptation module that can develop adaptable interfaces for various equipment communication protocols in different multi-level parking lots, converting data into standard formats, overcoming compatibility problems caused by equipment differences, ensuring that the system can operate stably in diverse parking lot environments, and is widely applicable to various practical scenarios.

[0098] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods of various embodiments or some parts of embodiments.

[0099] 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 it. 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. These modifications or substitutions do not cause the essence of the corresponding technical solutions to depart from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A blockchain-based system for storing, recording, and tracing access to multi-level parking spaces, characterized in that: include: The data acquisition module is used to collect multi-dimensional parking lot data in real time, preprocess the collected data, and obtain a hash value dataset. The equipment adaptation module is used to develop dedicated adaptation interfaces for the equipment communication protocols of different types of automated parking systems, and automatically converts the hash value dataset format to standard hash data. The blockchain evidence storage module verifies the standard hash data and packages it into chain blocks. It uses the Raft algorithm to store the chain blocks to the consortium blockchain node, puts the video data hash value and parking lot access record data on the blockchain, and stores the video in OSS to obtain distributed block data and video-related data. The business logic automation module, based on chained block data and video association information, automatically associates the entire process to form records, triggers alarms, calculates costs, and generates complete records; The traceability query module supports querying based on any condition, retrieving complete records, and combining them with distributed block data to form a complete chain of evidence.

2. The blockchain-based multi-level parking space access record storage and traceability system according to claim 1, characterized in that, The data acquisition module includes: The raw data acquisition unit is used to collect basic vehicle information, equipment operating status, parking space occupancy and storage and retrieval process videos in real time to obtain multi-dimensional raw data. The raw data preprocessing unit performs format standardization conversion according to unified specifications, filters out duplicate and abnormal information, and obtains standardized datasets and corresponding video clips. The hash value calculation unit is used to apply a hash algorithm to the standardized dataset and each video segment to calculate the hash value, generate the hash result corresponding to the data, and obtain the hash value dataset.

3. The blockchain-based multi-level parking space access record storage and traceability system according to claim 2, characterized in that, The specific steps for calculating the hash value of a standardized dataset are as follows: The register is initialized by assigning a value to it according to the fixed initial hash value preset by the hash algorithm. The hash value dataset byte stream is divided into blocks of fixed length according to the hash algorithm to obtain hash data blocks; The hash data block is subjected to multiple rounds of compression function calculations to update the value of the initialized register. During the calculation process, intermediate variables are first generated based on different conditions through message expansion, and then the register state is continuously updated through the main compression loop with the help of logical operations to obtain the updated register. After processing all data blocks, the updated register values ​​are concatenated in order to obtain the first set of standardized hash values.

4. The blockchain-based multi-level parking space access record storage and traceability system according to claim 1, characterized in that, The specific steps for calculating the hash value of a video clip are as follows: Convert the segmented video clips into hash values ​​to be calculated in byte stream format; Initialize the hash buffer of the hash algorithm, divide the video segment byte stream into blocks of fixed length, pad the parts that are not long enough, record the length information of the original video segment, and obtain the processed video data block; The input video data blocks are processed, and multiple rounds of iterative calculations are performed according to the compression function calculation rules of the hash algorithm. The values ​​of the registers are continuously updated. After all video data blocks have been processed, the register values ​​are concatenated in order to obtain the hash value dataset two.

5. The blockchain-based three-dimensional parking space access record storage and traceability system according to claim 1, characterized in that, The equipment adaptation module includes: The protocol information identification unit is used to collect equipment communication protocol information of different types of automated parking systems, identify the protocol type and data transmission rules of various types of equipment, and output a list of equipment communication protocol types. The adapter interface development unit is used to develop corresponding dedicated adapter interfaces for the syntax and data structure of each protocol according to the list of device communication protocol types, clarify the data interaction logic between the interface and the device and the interface and subsequent modules, and output a set of dedicated adapter interfaces. The hash value dataset access unit is used to take the hash value dataset as input data for a dedicated adapter interface and output the hash value dataset to be formatted. The data format conversion unit is used to perform protocol parsing on the hash value dataset to be converted using a dedicated set of adaptation interfaces, converting it into a standard data format that conforms to the evidence storage system specifications, and outputting preliminary standard hash data. The standard data verification unit is used to verify the standard hash data and output the standard hash data.

6. The blockchain-based multi-level parking space access record storage and traceability system according to claim 1, characterized in that, The blockchain evidence storage module includes: The data verification unit is used to verify the data integrity, hash value matching degree, and logical correlation of the dataset containing the original data hash values; The data block generation unit is used to package the verified dataset according to the block structure to form a chain of blocks that can be uploaded to the blockchain. Distributed consensus units are used to synchronize and store blocks to all nodes of the consortium blockchain using the Raft algorithm; The data association unit is used to process excessively large video files by using video data hash values ​​to be uploaded to the blockchain and video files to be stored in a distributed manner.

7. The blockchain-based three-dimensional parking space access record storage and traceability system according to claim 6, characterized in that, The data block generation unit includes: The block structure definition sub-unit presets the standard structure of blockchain blocks and outputs a standardized block structure template. The data integration and packaging subunit is used to classify the dataset according to the verification dataset and the block structure template, fill it into the block body, write the timestamp and the hash value of the previous block in the block header, and output the initial block. The blockchain-style associated sub-unit is used to calculate the hash value of the current block based on the initial block, write it into the block header of the next block, form a chain association, and output a chain block that can be uploaded to the chain.

8. The blockchain-based three-dimensional parking space access record storage and traceability system according to claim 6, characterized in that, The distributed consensus unit includes: In the leader election sub-unit, consortium chain nodes periodically initiate elections, using a heartbeat mechanism and voting logic to determine the leader node responsible for block synchronization, and output the identifier of the elected leader node. The log replication subunit, based on the leader node identifier and the chained blocks, has the leader node send the blocks sequentially to all follower nodes in the consortium chain. After the follower nodes confirm receipt, they return a response to the leader and output a confirmation message that the block replication is complete. The security assurance subunit is used to verify whether the block content stored by all nodes is consistent based on the confirmation information of the block replication completion. When more than half of the nodes confirm that it is consistent, the block is marked as committed and the block data of the distributed storage is completed is output.

9. The blockchain-based multi-level parking space access record storage and traceability system according to claim 1, characterized in that, The business logic automation module includes: The data access unit is used to adapt the data format according to the chained block data and video association information to obtain standard block and video association data packets; The full-process information association unit is used to extract vehicle information, equipment status, parking space data, timestamps and video hash values ​​from standard blocks and video-associated data packets, automatically associate information across all stages according to the access timeline, and output preliminary vehicle access records. The abnormal rule matching unit is used to compare the device data in the preliminary vehicle access record with the parking time to determine whether it is greater than the preset time. If it is, an abnormal alarm log is generated and the abnormal marked access record and abnormal alarm log are output. The parking fee calculation unit is used to extract the vehicle entry time and exit time from the abnormal marked access records, automatically calculate the parking fee according to the charging standard, generate fee details, and output complete access records with fee details and abnormal alarm logs.

10. The blockchain-based multi-level parking space access record storage and traceability system according to claim 1, characterized in that, The traceability query module includes: The query condition receiving and processing unit is used to perform format validation and standardization processing on any query condition input by the user, and output standard query parameters. The smart contract record retrieval unit is used to accurately match the associated complete access records, abnormal alarm logs, and fee details stored in the smart contract according to standard query parameters, retrieve the target record set corresponding to the query conditions, and output the associated records. The distributed block data acquisition and integration unit is used to acquire the distributed storage chain block data corresponding to the associated records from each node of the consortium blockchain, and to integrate the chain block data with the associated records by aligning the fields through the unique identifier in the records, and output the integrated block contract data. The evidence chain information supplement unit is used to extract the video hash value from the integrated data of the block contract, associate the video data association information, supplement the acquisition path and verification method of the video file, and output a preliminary evidence chain. The evidence chain verification and output unit is used to verify the completeness and logical consistency of the preliminary evidence chain. After the verification is passed, the data is sorted out according to the access timeline and the complete evidence chain is output.

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