Laboratory equipment reservation and access linkage control method and system

Abstract

The invention relates to the technical field of equipment management, and discloses a laboratory equipment reservation and access linkage control method and system, and the method comprises the steps: verifying the legality of user identity information and equipment identification information, and obtaining a reservation verification result; when the reservation verification result is passed, performing dynamic resource allocation on the real-time state data and the reservation time range to obtain a resource allocation strategy; constructing a unique access token, encoding the scheduling instruction into the unique access token, and generating an access control instruction; before the appointment time, an access control instruction is input, and the access permission is activated; performing abnormal mode identification on the operation log data: if an abnormal use behavior is identified, automatically cancelling the access authority, synchronously adjusting a resource allocation strategy, generating a use report, and updating a state database; according to the invention, the efficiency of laboratory equipment reservation and admission linkage control can be improved.

Description

Technical Field

[0001] This invention relates to the field of equipment management technology, and in particular to a method and system for linkage control of laboratory equipment reservation and access. Background Technology

[0002] In existing laboratory equipment reservation and access control schemes, reservation verification and resource allocation lack an efficient linkage mechanism. The process for verifying the legality of user identity information and equipment identification information is cumbersome and lacks accuracy, making it difficult to achieve accurate matching of identity and equipment authorization. At the same time, resource allocation is mostly based on fixed rules and does not fully combine the real-time status data of laboratory equipment with the reservation time range for dynamic adjustment. This easily leads to resource conflicts or idleness, resulting in low equipment utilization efficiency and failing to meet diverse experimental needs.

[0003] In the access control and usage supervision stages, the existing technology's access token generation logic lacks sufficient security and uniqueness guarantees, and the coding method of scheduling instructions is not standardized enough, making it easy for permission misuse or instruction parsing anomalies to occur. In addition, the ability to identify abnormal laboratory equipment operation behavior is weak, and there is a lack of a systematic risk assessment model, making it difficult to quickly and accurately identify abnormal usage behavior. Moreover, after an anomaly occurs, access permissions cannot be revoked in a timely manner and resource allocation strategies cannot be adjusted synchronously. This not only affects the operational safety of the equipment but also leads to a lack of accurate data support for subsequent resource scheduling, further reducing the overall efficiency of laboratory equipment management. Therefore, how to improve the management efficiency of laboratory equipment has become an urgent problem to be solved. Summary of the Invention

[0004] This invention provides a method and system for linking laboratory equipment reservation and access control to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides a laboratory equipment reservation and access control method, comprising:

[0006] S1. Verify the legality of the user's identity information and device identification information in the user's reservation request, and obtain the user's reservation verification result;

[0007] S2. When the reservation verification result is passed, the real-time status data of the laboratory equipment and the reservation time range are dynamically allocated to obtain the resource allocation strategy of the laboratory equipment.

[0008] S3. Use the core scheduling parameters of the resource allocation strategy as the first key and the user identity information as the second key to construct a unique access token for the user, and encode the scheduling instructions in the resource allocation strategy into the unique access token to generate the access control instructions for the laboratory equipment.

[0009] S4. Before the scheduled time for the laboratory equipment, enter the access control command to activate the access rights of the laboratory equipment;

[0010] S5. Perform abnormal pattern recognition on the operation log data of the laboratory equipment: if abnormal usage behavior is detected, automatically revoke the access permission and adjust the resource allocation strategy accordingly.

[0011] S6. Generate a usage report for the laboratory equipment based on the usage status information of the laboratory equipment, and update the status database of the laboratory equipment.

[0012] In a preferred embodiment, verifying the legality of the user identity information and device identification information in the user reservation request to obtain the user's reservation verification result includes:

[0013] The core identity fields in the user's identity information are used as the data blocks to be encrypted, and the data blocks to be encrypted are encrypted to obtain the user's encrypted identifier data.

[0014] The device identification information is hashed to obtain the hash sequence of the laboratory equipment;

[0015] The encrypted identifier data and the hash sequence are mapped to a pre-stored authorization database, and the encrypted identifier data and the hash sequence are compared item by item to obtain the user's preliminary verification result;

[0016] Verify the completeness of the preliminary verification results to obtain the user's appointment verification result.

[0017] In a preferred embodiment, when the reservation verification result is successful, dynamic resource allocation is performed on the real-time status data of the laboratory equipment and the reservation time range to obtain a resource allocation strategy for the laboratory equipment, including:

[0018] The data format of the real-time status data of the laboratory equipment is standardized to obtain the standard status data of the laboratory equipment.

[0019] The reservation time range of the laboratory equipment is segmented to obtain the time window of the reservation time range, and the duration feature of the time window is extracted;

[0020] By detecting the temporal conflict between the standard state data and the duration feature, resource conflict data of the laboratory equipment is obtained.

[0021] Based on the resource conflict data, the allocation scheme of the laboratory equipment is dynamically adjusted to obtain the resource allocation strategy of the laboratory equipment.

[0022] In a preferred embodiment, the step of using the core scheduling parameters of the resource allocation strategy as a first key and the user identity information as a second key to construct a unique access token for the user, and encoding the scheduling instructions in the resource allocation strategy into the unique access token to generate access control instructions for the laboratory equipment, includes:

[0023] The core scheduling parameters of the resource allocation strategy are parsed and encrypted to obtain the user's first key.

[0024] The user's identity information is digested to obtain the user's second key;

[0025] The first key and the second key are bound together as the user's token infrastructure;

[0026] The specific components of the token infrastructure are encoded to obtain the user's unique access token.

[0027] In a preferred embodiment, the step of using the core scheduling parameters of the resource allocation strategy as a first key and the user identity information as a second key to construct a unique access token for the user, and encoding the scheduling instructions in the resource allocation strategy into the unique access token to generate access control instructions for the laboratory equipment, includes:

[0028] Semantic parsing is performed on the scheduling instructions in the resource allocation strategy to obtain the instruction opcode and parameter set of the scheduling instructions;

[0029] A fixed identifier header is assigned to the instruction opcode, and a corresponding type identifier is assigned to the parameters in the parameter set;

[0030] The identifier header and the type identifier are combined in a predetermined order to obtain the encoded sequence of the scheduling instruction;

[0031] The encoded sequence is embedded into a designated data segment of the unique access token, and the designated data segment is encapsulated for data integrity to obtain the access control instruction for the laboratory equipment.

[0032] In a preferred embodiment, the abnormal pattern identification of the operation log data of the laboratory equipment includes: if abnormal usage behavior is identified, automatically revoking the access permission and synchronously adjusting the resource allocation strategy, including:

[0033] By analyzing the deviation between the operational behavior characteristics of the operation log data in the laboratory equipment and the preset benchmark operation model, the potential abnormal behavior characteristics of the laboratory equipment can be obtained.

[0034] Risk assessment is performed on the potential abnormal behavior characteristics to obtain the abnormal behavior determination result of the laboratory equipment;

[0035] When the abnormal behavior is determined to be abnormal, the user's access permissions are revoked.

[0036] Based on the severity level of the abnormal behavior determination result, the scheduling parameters of the resource allocation strategy are updated synchronously.

[0037] In a preferred embodiment, the step of performing a risk assessment on the potential abnormal behavior characteristics to obtain the abnormal behavior determination result of the laboratory equipment includes:

[0038] The potential abnormal behavior features are vectorized and fitted to obtain the risk feature vector of the laboratory equipment.

[0039] The risk feature vector is evaluated at multiple levels to obtain the risk level of abnormal behavior of the laboratory equipment.

[0040] The logical rationality and severity of the risk level of the abnormal behavior are judged to obtain the abnormal behavior judgment result of the laboratory equipment.

[0041] In a preferred embodiment, the step of performing multi-level evaluation on the risk feature vector to obtain the abnormal behavior risk level of the laboratory equipment includes:

[0042] A comprehensive analysis of the risk feature vector yields the comprehensive risk value of the laboratory equipment, wherein the formula for calculating the comprehensive risk value is as follows: ;in, This represents the overall risk value. This represents the dimension of the risk feature vector. Indicates the first The weight coefficients of the aforementioned risk feature vectors, This indicates the preset scaling factor. Indicates the first The aforementioned risk feature vectors, Represents a logarithmic function;

[0043] The comprehensive risk value is mapped to the risk level table of the laboratory equipment to obtain the abnormal behavior risk level of the laboratory equipment.

[0044] In a preferred embodiment, generating a usage report for the laboratory equipment based on its usage status information and updating the laboratory equipment status database includes:

[0045] By comparing the device runtime of the laboratory equipment using the status information with the reservation time range, the usage time analysis data of the laboratory equipment is obtained;

[0046] Based on the usage period analysis data and the function call records and operation instruction sequences in the usage status information, a usage report of the laboratory equipment is generated;

[0047] Based on the key indicators in the usage report, update the equipment status records in the status database of the laboratory equipment, and simultaneously adjust the available status indicators of the laboratory equipment.

[0048] To address the aforementioned problems, the present invention also provides a laboratory equipment reservation and access linkage control system, the system comprising:

[0049] The appointment verification module is used to verify the legality of the user's identity information and device identification information in the user's appointment request, and obtain the user's appointment verification result;

[0050] The resource allocation module is used to dynamically allocate resources to the real-time status data of the laboratory equipment and the reservation time range when the reservation verification result is passed, so as to obtain the resource allocation strategy of the laboratory equipment.

[0051] The access instruction generation module is used to construct a unique access token for the user by using the core scheduling parameters of the resource allocation strategy as the first key and the user identity information as the second key, and to encode the scheduling instructions in the resource allocation strategy into the unique access token to generate the access control instructions for the laboratory equipment.

[0052] The access permission activation module is used to activate the access permission of the laboratory equipment by inputting the access control command before the scheduled time of the laboratory equipment.

[0053] The resource allocation strategy adjustment module is used to identify abnormal patterns in the operation log data of the laboratory equipment: if abnormal usage behavior is identified, the access permission is automatically revoked and the resource allocation strategy is adjusted synchronously.

[0054] The equipment status update module is used to generate a usage report of the laboratory equipment based on the usage status information of the laboratory equipment, and to update the status database of the laboratory equipment.

[0055] Compared with the prior art, the present invention has the following beneficial effects:

[0056] 1. The technical solution of this invention accurately verifies the legality of user identity information and equipment identification information, combines real-time status data of laboratory equipment with reservation time range for dynamic resource allocation, constructs a unique access token for users with dual keys and encodes scheduling instructions to generate access control instructions, thereby realizing efficient linkage between reservation process and access permissions; this design greatly improves the overall efficiency of laboratory equipment reservation and access control, ensures that resource allocation fits the actual status of equipment and user needs, and at the same time makes access permissions exclusive and controllable, ensuring accurate authorization for equipment use.

[0057] 2. This technology can identify abnormal usage behavior and quickly revoke access permissions by performing abnormal pattern recognition on equipment operation log data, and simultaneously adjust resource allocation strategies, effectively ensuring the safety and standardization of equipment use. In addition, it generates usage reports based on equipment usage status information and updates the status database, providing comprehensive and accurate data support for equipment management, improving the precision of laboratory equipment management, and further optimizing the utilization efficiency and lifecycle management effect of equipment resources. Attached Figure Description

[0058] Figure 1 This is a flowchart illustrating a laboratory equipment reservation and access linkage control method according to an embodiment of the present invention.

[0059] Figure 2 A functional block diagram of a laboratory equipment reservation and access linkage control system provided in an embodiment of the present invention;

[0060] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0061] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0062] This application provides a method for linking laboratory equipment reservation and access control. The executing entity of this method includes, but is not limited to, at least one of the following electronic devices that can be configured to execute the method provided in this application: a server, a terminal, etc. In other words, the method can be executed by software or hardware installed on a terminal device or a server device. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster. The server can be an independent server or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms.

[0063] Reference Figure 1 The diagram shown is a flowchart illustrating a laboratory equipment reservation and access linkage control method according to an embodiment of the present invention. In this embodiment, the laboratory equipment reservation and access linkage control method includes:

[0064] S1. Verify the legality of the user's identity information and device identification information in the user's reservation request, and obtain the user's reservation verification result;

[0065] In this embodiment of the invention, verifying the legality of the user identity information and device identification information in the user reservation request to obtain the user's reservation verification result includes:

[0066] The core identity fields in the user's identity information are used as the data blocks to be encrypted, and the data blocks to be encrypted are encrypted to obtain the user's encrypted identifier data.

[0067] The device identification information is hashed to obtain the hash sequence of the laboratory equipment;

[0068] The encrypted identifier data and the hash sequence are mapped to a pre-stored authorization database, and the encrypted identifier data and the hash sequence are compared item by item to obtain the user's preliminary verification result;

[0069] Verify the completeness of the preliminary verification results to obtain the user's appointment verification result.

[0070] The core identity fields are extracted from the user's reservation request. These core identity fields are the unique identification information bound to the user when registering in the laboratory system, such as student ID, employee ID, or unique user ID. These extracted fields are integrated to form a data block to be encrypted. The data block to be encrypted is encrypted using a symmetric encryption method. First, a fixed encryption key is determined. The data block to be encrypted is divided into fixed-length groups according to the standard encryption process. Each group is then subjected to operations such as byte substitution, row shifting, column mixing, and round key addition. After multiple rounds of encryption processing, an irreversible ciphertext data is generated. This ciphertext data is the user's encrypted identification data.

[0071] Collect the unique identification information corresponding to the laboratory equipment, including the unique equipment number set at the factory and the equipment management code assigned within the laboratory. Integrate this information into a string with a unified format. Use a hash algorithm to perform hash transformation on this string. First, convert each character in the string to ASCII code. Then, use the compression function of the hash algorithm to iteratively calculate the converted value to convert the original equipment identification information into a fixed-length binary value. Finally, convert the binary value into a hexadecimal string. This hexadecimal string is the hash sequence of the laboratory equipment.

[0072] The pre-stored authorization database contains encrypted identifiers of all legitimate users who have passed laboratory audits, as well as hash sequences of all laboratory equipment that can be reserved for use. The data in the database is categorized and arranged according to an index structure for quick retrieval. Using the generated user encrypted identifiers and device hash sequences as query conditions, the database's indexing mechanism quickly locates the corresponding storage partition. First, the current user's encrypted identifiers are compared character by character with the encrypted identifiers of all legitimate users stored in the database to ensure that the order and content of each character are completely consistent. Then, the hash sequence of the current device is compared with the hash sequences of authorized devices in the database. If both comparisons find completely matching records, the preliminary verification result is passed. If neither comparison finds a matching record or there are character inconsistencies, the preliminary verification result is failed.

[0073] The completeness of the preliminary verification results is checked. First, it is verified whether the encrypted identifier data and hash sequence remain intact during transmission to the authorization database, without any data truncation, character loss, or transmission errors. Then, it is confirmed whether all relevant legal records in the database have been traversed during the item-by-item comparison process, without any omissions in the comparison. At the same time, it is verified whether the database uses the latest user and device authorization data during the comparison process, and whether expired or tampered stored information is used. If, after verification, the generation process of the preliminary verification results is found to have no data anomalies, no missing data pairs, and the data source is legal, then the final user appointment verification result is consistent with the preliminary verification result. If any issues affecting the accuracy of the verification are found during the verification process, the appointment verification result is determined to be unsuccessful.

[0074] The beneficial effects are as follows: by accurately extracting the user's core identity fields and generating encrypted identification data using specific encryption encoding methods, and combining this with a standardized hash conversion process to obtain the device hash sequence, the security and uniqueness of user identity and device identification are guaranteed from the source. Furthermore, through precise comparison of each item in the authorized database and integrity verification of the preliminary verification results, legitimate reservation requests can be efficiently identified, and reservation applications from illegal users or unauthorized devices can be completely excluded, ensuring the compliance and security of laboratory equipment reservations. At the same time, the entire verification process is clear in steps and specific in operation, effectively improving the accuracy and efficiency of reservation verification, and laying a reliable foundation for subsequent equipment resource allocation and access control.

[0075] S2. When the reservation verification result is passed, the real-time status data of the laboratory equipment and the reservation time range are dynamically allocated to obtain the resource allocation strategy of the laboratory equipment.

[0076] In this embodiment of the invention, when the reservation verification result is passed, dynamic resource allocation is performed on the real-time status data of the laboratory equipment and the reservation time range to obtain the resource allocation strategy for the laboratory equipment, including:

[0077] The data format of the real-time status data of the laboratory equipment is standardized to obtain the standard status data of the laboratory equipment.

[0078] The reservation time range of the laboratory equipment is segmented to obtain the time window of the reservation time range, and the duration feature of the time window is extracted;

[0079] By detecting the temporal conflict between the standard state data and the duration feature, resource conflict data of the laboratory equipment is obtained.

[0080] Based on the resource conflict data, the allocation scheme of the laboratory equipment is dynamically adjusted to obtain the resource allocation strategy of the laboratory equipment.

[0081] Real-time status data is collected from the laboratory equipment's real-time monitoring system. This data includes the equipment's current operating status, the current user's identification information, the time interval occupied by the equipment, and the remaining usable time. The current operating status of the equipment is specifically categorized as running, standby, or faulty. A unified data format standard is preset, which clearly defines the naming rules, data types, and value ranges of each data field. For example, the equipment operating status field is named "Equipment Operating Status," the data type is set to string, and the value is limited to running, standby, or faulty. The remaining usable time field is named "Remaining Usable Time," the data type is set to integer, and the unit is minutes. The collected raw real-time status data is formatted and mapped to each field according to the preset standard. For example, "working" in the equipment status field is converted to "running," and "idle" is converted to "standby." At the same time, the data of each field after conversion is verified to meet the value range requirements. If there are data type mismatches or values ​​that exceed the range, adjustments are made according to preset correction rules. Specifically, the remaining time in non-integer format is converted to integer, and the time exceeding the reasonable range is set to 0. Finally, a standardized and compliant laboratory equipment status data is formed.

[0082] Obtain the user-submitted time range for laboratory equipment reservations, clearly defined by specific dates and times, such as 14:00 to 16:30 on November 20, 2024. Based on the laboratory equipment's usage and management regulations, determine the granularity of the time window division, using the minimum effective usage time of the laboratory equipment as a basis, for example, setting it to a 30-minute time window. Divide the reservation time range equally according to the granularity, dividing it into independent time windows every 30 minutes from the reservation start time. The appointment time range in the example can be divided into five time windows: 14:00-14:30, 14:30-15:00, 15:00-15:30, 15:30-16:00, and 16:00-16:30. For each segmented time window, its duration feature is extracted, specifically recording the start time, end time, and actual duration of each time window. For example, the duration of each window is 30 minutes. This information is then correlated with the time windows one by one to form a complete duration feature record for each time window.

[0083] Extract information related to device time occupancy from standard status data, including the device's currently allocated usage time intervals, such as 13:00-14:20 on November 20, 2024, and the unavailable time intervals due to device maintenance or malfunction, such as 15:00-15:20 on November 20, 2024 (device maintenance). Compare these time intervals with the duration characteristics of each segmented time window, checking whether the start and end times of each time window overlap with the device's occupied or unavailable time intervals. If part or all of a time window falls within the device's occupied or unavailable time interval... If a time window is found to be occupied or unavailable, it is determined that there is a timing conflict between that time window and the current standard status of the equipment. For example, the 14:00-14:30 time window overlaps with the 13:00-14:20 time window where the equipment is occupied, and the 15:00-15:30 time window overlaps with the 15:00-15:20 time window where the equipment is under maintenance. These two time windows are marked as conflict windows, and the specific time range, conflict type (e.g., equipment occupied, equipment under maintenance), and corresponding equipment status information are recorded. These conflict-related data are compiled and summarized to form the resource conflict data of laboratory equipment.

[0084] The conflict windows in the resource conflict data are categorized and statistically analyzed to clarify the conflict type, the number of conflict windows, and the total conflict duration. Conflict types include equipment occupied, equipment maintenance, and equipment failure. Based on the conflict type, corresponding adjustment rules are formulated. If the conflict type is equipment occupied, the standard status data of other similar equipment in the laboratory is queried first to filter out equipment without time-series conflicts within the original reservation time range. The original reservation request is then assigned to this available equipment, forming a new equipment allocation scheme. If all equipment of the same type has conflicts, communication and negotiation are conducted with the user. With the user's consent, the original reservation time range is adjusted to a continuous idle time interval after the conflict window, for example, changing the original 14:00... The 0-16:30 time slot is adjusted to 14:30-17:00, and the time window is re-divided to confirm there are no conflicts. If the conflict type is equipment maintenance or malfunction, the estimated end time of the equipment maintenance or malfunction is queried. If the estimated end time is earlier than the end time of the original scheduled time range, the scheduled time range is adjusted to the time period after the maintenance or malfunction ends. If the estimated end time exceeds the original scheduled time range, other available equipment of the same type is allocated to the user. The adjusted equipment allocation information, the final determined scheduled time range, and the results of the conflict-free time window division are integrated to form clear equipment usage permissions, time arrangements, and status monitoring requirements. This integrated result is the resource allocation strategy for laboratory equipment.

[0085] The beneficial effects are as follows: by unifying the real-time status data format, the consistency and comparability of equipment status data from different sources and in different formats are ensured, providing a standard data foundation for subsequent time-series conflict detection; by segmenting the reservation time range at a fixed granularity and extracting duration features, refined management of reservation time is achieved, facilitating accurate location of conflict periods; by comparing the time-series relationship between standard status data and time windows one by one, resource conflicts can be comprehensively and accurately identified, avoiding omission of conflict situations; and the allocation scheme is dynamically adjusted based on conflict data, which prioritizes meeting users' reservation needs while making full use of laboratory equipment resources, effectively reducing resource waste caused by equipment idleness or conflicts. The final resource allocation strategy is both reasonable and feasible, significantly improving the efficiency and accuracy of laboratory equipment resource allocation.

[0086] S3. Use the core scheduling parameters of the resource allocation strategy as the first key and the user identity information as the second key to construct a unique access token for the user, and encode the scheduling instructions in the resource allocation strategy into the unique access token to generate the access control instructions for the laboratory equipment.

[0087] In this embodiment of the invention, the step of using the core scheduling parameters of the resource allocation strategy as a first key and the user identity information as a second key to construct a unique access token for the user, and encoding the scheduling instructions in the resource allocation strategy into the unique access token to generate access control instructions for the laboratory equipment, includes:

[0088] The core scheduling parameters of the resource allocation strategy are parsed and encrypted to obtain the user's first key.

[0089] The user's identity information is digested to obtain the user's second key;

[0090] The first key and the second key are bound together as the user's token infrastructure;

[0091] The specific components of the token infrastructure are encoded to obtain the user's unique access token.

[0092] The process involves using the core scheduling parameters of the resource allocation strategy as the first key and the user's identity information as the second key to construct a unique access token for the user. The scheduling instructions from the resource allocation strategy are then encoded into the unique access token to generate access control instructions for the laboratory equipment. This process includes:

[0093] Semantic parsing is performed on the scheduling instructions in the resource allocation strategy to obtain the instruction opcode and parameter set of the scheduling instructions;

[0094] A fixed identifier header is assigned to the instruction opcode, and a corresponding type identifier is assigned to the parameters in the parameter set;

[0095] The identifier header and the type identifier are combined in a predetermined order to obtain the encoded sequence of the scheduling instruction;

[0096] The encoded sequence is embedded into a designated data segment of the unique access token, and the designated data segment is encapsulated for data integrity to obtain the access control instruction for the laboratory equipment.

[0097] Core scheduling parameters are extracted from the resource allocation strategy. These parameters include the unique serial number of the laboratory equipment, the user's reserved usage time period, the equipment access permission level, and the equipment operation restrictions. These parameters are key information used to control equipment scheduling in the resource allocation strategy. The extracted core scheduling parameters are encrypted using the DES encryption algorithm. First, the core scheduling parameters are integrated into a continuous character sequence. Then, a fixed encryption initialization vector is determined. Following the DES encryption process, the character sequence is divided into 64-bit blocks. Each block undergoes initial permutation, 16 rounds of iterative encryption, and inverse initial permutation. After the complete encryption process, a ciphertext that cannot be directly deciphered is generated. This ciphertext is the user's first key.

[0098] User identity information is collected, including the user's registered account in the laboratory system, the user's department, and the user's role type, such as teacher, student, or researcher. This information is integrated into a complete identity information string in a fixed order. The SHA-1 hash algorithm is used to perform a digest conversion on this identity information string. First, each character in the identity information string is encoded to obtain the corresponding binary data. Then, the SHA-1 hash function is used to process the binary data, converting the binary data of arbitrary length into a fixed-length 160-bit hash value. Finally, the hash value is converted into a hexadecimal string, which is the user's second key.

[0099] The key binding rules are defined, specifying the association method and structural composition of the first and second keys. The first key is first used as the core data segment of the token infrastructure, and the second key is used as the authentication segment. A fixed separator is added between the two key segments to distinguish them. A data identifier is added at the beginning of the token infrastructure to identify it as the basic data for a unique access token, and a generation timestamp is added at the end to record the execution time of the binding operation. The contents are then integrated in the order of data identifier + first key + separator + second key + timestamp to form a complete structured data set, which constitutes the user's token infrastructure.

[0100] The specific components of the token infrastructure are clearly defined, including a data identifier, a first key, a separator, a second key, and a timestamp. Each component is encoded using Base64 encoding, converting the characters or values ​​of each element into a Base64 encoded string. Following the original order of the components in the token infrastructure, the encoded strings are concatenated to form a continuous encoded string. To ensure the uniqueness of this encoded string, a unique checksum generated based on the user's identity information and core scheduling parameters is added to the end of the concatenated string. The final encoded string containing the checksum is the user's unique access token.

[0101] Semantic parsing is performed on scheduling instructions in resource allocation strategies. These instructions include specific operational commands such as equipment start-up instructions, equipment parameter adjustment instructions, and equipment usage time limit instructions. Semantic parsing tools are used to analyze the linguistic meaning of each instruction, identifying the core operational actions and converting them into corresponding operation codes. For example, operation code 1001 corresponds to equipment start-up, and operation code 1002 corresponds to equipment parameter adjustment. Simultaneously, specific parameters related to the operational actions are extracted from the instructions. These parameters include equipment start-up warm-up time, specific parameter adjustment values, and specific usage time limits in minutes. These parameters are then organized and categorized to form the parameter set of the scheduling instructions.

[0102] Establish rules for assigning identifier headers and type identifiers. These rules specify the fixed identifier headers corresponding to different instruction opcodes. For example, instruction opcode 1001 is assigned the fixed identifier header ST, and instruction opcode 1002 is assigned the fixed identifier header AD. Each instruction opcode's identifier header is unique and cannot be changed within the system. For different types of parameters in the parameter set, assign type identifiers. For example, time-related parameters such as preheating time are assigned the type identifier TIME, numerical parameters such as adjustment values ​​are assigned the type identifier NUM, and status parameters such as device operating modes are assigned the type identifier STAT. This ensures that each parameter can be matched with a unique type identifier.

[0103] The predetermined combination order is determined as identifier header + type identifier + parameter specific value. First, the fixed identifier header corresponding to the scheduling instruction is placed at the beginning. Then, according to the arrangement order of the parameters in the parameter set, the type identifier and parameter specific value of each parameter are sequentially placed after the identifier header. For example, if the scheduling instruction is to start the equipment and the warm-up time is 10 minutes, its instruction opcode corresponds to the identifier header ST, the parameter type is time-related, corresponding to the type identifier TIME, and the parameter specific value is 10. After combining them in the predetermined order, the character sequence ST+TIME+10 is obtained. This character sequence is the encoding sequence of the scheduling instruction.

[0104] A designated data segment is defined within the unique access token's data structure. This segment is a reserved data area in the middle of the token, specifically used to store the encoded sequence of scheduling instructions. The generated encoded sequence of scheduling instructions is completely written into this designated data segment, ensuring that the encoded sequence is stored in a fixed position within the data segment and does not overlap with other data segments of the token. A CRC check algorithm is used to encapsulate the designated data segment for data integrity. First, the CRC check value of the encoded sequence in the designated data segment is calculated, and then the check value is appended to the end of the designated data segment to form a complete data segment containing the encoded sequence and the check value. At this point, the unique access token integrating this complete data segment becomes the access control instruction for the laboratory equipment.

[0105] The beneficial effects are as follows: by generating dual keys through encryption and conversion of core scheduling parameters and digest conversion of user identity information, the security of the keys is greatly improved, and the leakage of critical information is avoided; the dual keys are bound into a token infrastructure and encoded to form a unique access token, which, combined with user identity and scheduling parameters, ensures the uniqueness of the access token and prevents the token from being forged or misused; the scheduling instructions are semantically parsed, identified, and sequenced, and then embedded with the token and encapsulated for integrity, which not only achieves deep integration of scheduling instructions and access tokens, but also ensures the integrity of instruction data through a verification mechanism. The final access control instructions generated have security, uniqueness, and integrity, which effectively improves the reliability of access control for laboratory equipment and prevents equipment use risks caused by illegal operations or data tampering.

[0106] In this embodiment of the invention, S4, before the scheduled time of the laboratory equipment, the access control command is input to activate the access rights of the laboratory equipment;

[0107] Ten to thirty minutes before the scheduled time for laboratory equipment, the current operating status of the equipment is first queried through the laboratory equipment status database to confirm that the equipment is in a standby and fault-free available state, ensuring that the equipment has the basic conditions to receive and process access control commands. At this time, the input process of access control commands is initiated.

[0108] Access control commands can be entered through the local control panel built into the laboratory equipment or the terminal device associated with the laboratory management system. During the operation, the string corresponding to the access control command must be entered completely. The system will provide real-time prompts to ensure the completeness of the character input, so as to avoid the command being unrecognizable due to missing characters or input errors, until all characters are entered completely to complete the command input operation.

[0109] After receiving the input access control command, the device's command processing module automatically parses the unique access token and scheduling command encoding sequence contained in the command. First, it extracts the first key and the second key from the token and compares them one by one with the pre-stored user reservation information and the device's core scheduling parameters. It confirms that the core scheduling parameters corresponding to the first key match the current device and that the user identity information corresponding to the second key matches the reserved user. Then, it checks the CRC check value at the end of the encoding sequence to confirm that the command data has not been tampered with or damaged during transmission and input. Once all the verification items pass, the command verification is completed.

[0110] After the command verification is successful, the device's access control module receives the activation signal sent by the system, automatically unlocks the device's operation function restrictions, enables access permissions for the device's operation interface, function button usage permissions, and data interaction permissions, updates the device's current usage status from "standby" to "ready to use," and records the input time of the access control command, verification result, and access permission activation status in the device operation log, thus completing the activation operation of the laboratory device's access permissions.

[0111] The beneficial effects are as follows: by setting a reasonable time period for pre-booking instruction input, sufficient time is reserved for instruction verification and permission activation, avoiding operational delays close to the time of use, and the pre-confirmation of device status ensures the foundation for instruction processing; complete input prompts and multi-dimensional verification mechanisms can effectively avoid input errors and illegal instructions, ensuring that the activated permissions accurately correspond to the booked user and the target device; after permission activation, the device status and operation logs are updated synchronously, realizing full-process control before device use, which not only ensures the security of device use, but also provides a clear basis for subsequent usage record traceability.

[0112] S5. Perform abnormal pattern recognition on the operation log data of the laboratory equipment: if abnormal usage behavior is detected, automatically revoke the access permission and adjust the resource allocation strategy accordingly.

[0113] In this embodiment of the invention, the abnormal pattern recognition of the operation log data of the laboratory equipment includes: if abnormal usage behavior is detected, automatically revoking the access permission and synchronously adjusting the resource allocation strategy, including:

[0114] By analyzing the deviation between the operational behavior characteristics of the operation log data in the laboratory equipment and the preset benchmark operation model, the potential abnormal behavior characteristics of the laboratory equipment can be obtained.

[0115] Risk assessment is performed on the potential abnormal behavior characteristics to obtain the abnormal behavior determination result of the laboratory equipment;

[0116] When the abnormal behavior is determined to be abnormal, the user's access permissions are revoked.

[0117] Based on the severity level of the abnormal behavior determination result, the scheduling parameters of the resource allocation strategy are updated synchronously.

[0118] The step of conducting a risk assessment on the potential abnormal behavior characteristics to obtain the abnormal behavior determination result of the laboratory equipment includes:

[0119] The potential abnormal behavior features are vectorized and fitted to obtain the risk feature vector of the laboratory equipment.

[0120] The risk feature vector is evaluated at multiple levels to obtain the risk level of abnormal behavior of the laboratory equipment.

[0121] The logical rationality and severity of the risk level of the abnormal behavior are judged to obtain the abnormal behavior judgment result of the laboratory equipment.

[0122] The process of performing multi-level evaluation on the risk feature vector to obtain the abnormal behavior risk level of the laboratory equipment includes:

[0123] A comprehensive analysis of the risk feature vector yields the comprehensive risk value of the laboratory equipment, wherein the formula for calculating the comprehensive risk value is as follows: ;in, This represents the overall risk value. This represents the dimension of the risk feature vector. Indicates the first The weight coefficients of the aforementioned risk feature vectors, This indicates the preset scaling factor. Indicates the first The aforementioned risk feature vectors, Represents a logarithmic function;

[0124] The comprehensive risk value is mapped to the risk level table of the laboratory equipment to obtain the abnormal behavior risk level of the laboratory equipment.

[0125] Complete operation log data for a specified time period is extracted from the laboratory equipment operation log database. The operation log data specifically includes the execution time of each operation, the triggered operation commands (e.g., equipment startup parameter adjustment function switching), the corresponding parameter settings (e.g., temperature, pressure, runtime), the equipment's response status (e.g., normal execution, error message, no response), and the user identifier corresponding to the operation. Based on this log data, operation behavior characteristics are extracted, including the execution order of operation commands (e.g., normal startup should preheat before setting parameters; if parameters are set first and then preheat, a specific command sequence is formed), the range of parameter setting values ​​(e.g., if the normal temperature parameter range for a certain equipment is 20-50℃, record whether the actual setting value falls within this range), and the operation commands. The execution interval, such as the interval between two parameter adjustments in normal operation, is usually no less than 1 minute. The actual interval duration is recorded. The continuity of the equipment response status is also recorded, such as whether the operation is forced even after frequent errors. The pre-stored benchmark operation model is retrieved. This model contains the standard instruction sequence, reasonable parameter range, operation interval threshold, and normal response mode of the laboratory equipment under normal use scenarios. The extracted actual operation behavior features are compared one by one with the corresponding items in the benchmark operation model to calculate the degree of deviation. For example, the magnitude of parameter setting values ​​exceeding the reasonable range, the number of steps of difference between the instruction sequence and the standard sequence, and the number of times the operation interval is lower than the threshold are calculated. These deviation operation behavior features are summarized and organized to obtain the potential abnormal behavior features of the laboratory equipment.

[0126] Based on the acquired potential abnormal behavior characteristics, the system is divided into dimensions according to preset feature dimension classification rules. Common dimensions include parameter operation dimension (e.g., parameters exceeding the range or frequent parameter changes), instruction execution dimension (e.g., incorrect instruction sequence, invalid instructions, or repeated execution), and device response dimension (e.g., ignoring error reports, continuous operation, unresponsive device, yet still forcibly triggering instructions). A corresponding numerical representation is assigned to each dimension's potential abnormal behavior characteristics. For example, in the parameter operation dimension, parameters exceeding the reasonable range by less than 10°C are recorded as 1, exceeding by 10-20°C as 2, and exceeding by more than 20°C as 3. In the instruction execution dimension, one incorrect instruction sequence is recorded as 1, and two or more incorrect sequences as 2. In the device response dimension, ignoring one error report is recorded as 1, and ignoring two or more error reports as 2. Based on the feature values ​​of each dimension, a vector array containing values ​​from all dimensions is constructed. The value at each position in the array corresponds to the degree of potential abnormality in one dimension. This vector array is the risk feature vector of the laboratory equipment.

[0127] First, determine the weight coefficients for each dimension of the risk feature vector. These weight coefficients are set based on the degree of impact of abnormal behavior on the equipment in different dimensions. For example, in the parameter operation dimension, severely out-of-range parameters may damage the equipment, so the weight coefficient is set to 0.4; in the instruction execution dimension, incorrect instruction sequence may affect experimental results, so the weight coefficient is set to 0.3; and in the equipment response dimension, ignoring error reporting may exacerbate equipment failure, so the weight coefficient is set to 0.3. Multiply the value of each dimension in the risk feature vector by its corresponding weight coefficient to obtain the weighted risk value for each dimension. Then, sum the weighted risk values ​​of all dimensions to obtain the comprehensive risk value of the laboratory equipment. For example, a certain wind... The risk feature vector is [3,2,2], and the weight coefficients for each dimension are 0.4, 0.3, and 0.3, respectively. Therefore, the weighted risk values ​​for each dimension are 1.2, 0.6, and 0.6, respectively, and the comprehensive risk value is 1.2 + 0.6 + 0.6 = 2.4. The pre-stored laboratory equipment risk level table is retrieved. This table clearly divides the risk level corresponding to the comprehensive risk value. For example, a comprehensive risk value of 0-1.0 corresponds to low risk, 1.1-2.0 corresponds to medium risk, and 2.1 and above corresponds to high risk. The calculated comprehensive risk value is matched with the interval in the risk level table to determine the corresponding risk level. This level is the risk level of abnormal behavior of the laboratory equipment.

[0128] By combining historical operation records of laboratory equipment with the scenarios in which abnormal behavior occurs, the logical rationality of the risk level of abnormal behavior is determined. For example, if a user's first operation of the equipment results in an incorrect command sequence leading to a medium-risk level, it is necessary to confirm whether the user has received equipment operation training. If not, the risk level is consistent with the actual situation. If the user has received training and there are no abnormalities in historical operations, further verification is needed to determine if there was any misoperation. At the same time, the severity is determined based on the potential hazard level corresponding to the risk level. For example, a low-risk level may only affect experimental efficiency, a medium-risk level may lead to experimental data deviation, and a high-risk level may cause equipment damage or safety accidents. Combining the results of the logical rationality judgment and the severity assessment, if the risk level is confirmed to be reasonable and there is actual hazard, it is determined to be abnormal behavior, and the abnormality type is marked as parameter operation abnormality or command execution abnormality. If it is determined to be misidentification or there is no actual hazard, it is determined to be normal behavior. This determination result is the abnormal behavior determination result of the laboratory equipment.

[0129] When the abnormal behavior is confirmed as abnormal, the access control module of the laboratory equipment immediately receives the abnormal trigger signal and automatically executes the permission revocation operation. Specifically, this includes disabling the device's operation command trigger permissions, such as disabling function buttons to prevent parameter modification, interrupting the currently running device program if the operation may damage the device, and freezing the user's access permissions to the device operation interface. At the same time, the operation log records the time of permission revocation, the corresponding abnormal behavior type, and the execution status of the revocation operation to ensure that the user cannot continue to operate the device and avoid the abnormal behavior from continuing to cause impact.

[0130] Retrieve the risk level of abnormal behavior from the abnormal behavior judgment results, and formulate corresponding resource allocation strategy adjustment rules according to different risk levels. If the risk level is low, simply add the user's operation reminder record to the resource allocation strategy, adjust the pre-approval process for the user's next reservation of the equipment, and add a step to inform the user of operation precautions. If the risk level is medium, suspend the user's reservation qualification for this type of equipment for 1-2 weeks, and adjust the parameter monitoring threshold of the equipment, narrowing the reasonable range of the original parameters by 5% to 10% to enhance the sensitivity of parameter operation. If the risk level is high, prohibit the user from reserving all laboratory equipment for 3 months, update the user reservation permission list in the resource allocation strategy, remove the user's reservation qualification, adjust the equipment reservation review process, add a second verification step for the user's operation qualification, and update the equipment's baseline operation model, adding the high-risk abnormal behavior characteristics discovered this time to the model's abnormal identification library, and simultaneously update the resource allocation strategy scheduling parameters.

[0131] The calculation of the overall risk value involves the dimensions, weighting coefficients, scaling factors, and risk feature vectors of the risk feature vector.

[0132] The dimension of the risk feature vector comes from the number of risk features determined in the actual risk assessment scenario.

[0133] The weight coefficient of each risk feature vector is determined by expert scoring. Experts score each risk feature according to its importance. The initial score is obtained by adding the scores of each expert for a certain risk feature and dividing by the number of experts. The total score is obtained by adding all the initial scores and dividing the total score by the initial score.

[0134] The preset scaling factor comes from historical risk data and risk assessment objectives. It collects historical risk event data, analyzes the probability of risk occurrence and the degree of impact corresponding to risk characteristics, and sets the target for assessment accuracy.

[0135] Each risk feature vector comes from the collection and quantification of relevant data on the assessment object. After the data is collected, it is converted into a numerical value according to a preset quantification standard.

[0136] The calculation first multiplies each risk feature vector by its corresponding scaling factor, adds one to the result, takes the natural logarithm of the added result, and then multiplies it by the corresponding weight coefficient. All the multiplication results are added together to get the numerator; all the weight coefficients are added together to get the denominator; the numerator is divided by the denominator to get the comprehensive risk value. This comprehensively reflects the importance and risk level of each risk feature, accurately reflecting the overall risk level.

[0137] When a certain risk feature vector increases while others remain unchanged, the overall risk value increases.

[0138] If a certain weighting coefficient increases, and the corresponding processed value is greater than the average, the overall risk value increases; conversely, it decreases.

[0139] When a certain scaling factor is increased while other factors remain unchanged, the overall risk value increases.

[0140] The beneficial effects include: by extracting multi-dimensional behavioral features from operation logs and comparing them one by one with the benchmark model, it is possible to accurately capture potential abnormal behaviors with deviations, avoiding misidentification or omissions caused by single feature judgments; by constructing risk feature vectors by quantifying potential abnormal features according to dimensions, and calculating comprehensive risk values ​​and matching risk levels by combining weights, the risk assessment process becomes more objective and quantitative, ensuring accurate risk level classification; by judging the rationality of risk levels based on historical records and scenarios, and assessing the severity by combining the degree of hazard, the reliability of abnormal behavior judgment results is further improved; by immediately revoking access permissions after an anomaly occurs, the continuous impact of abnormal behavior on equipment can be quickly blocked, reducing the risk of equipment damage or safety accidents; and by adjusting resource allocation strategies according to risk level differences, targeted control measures can be taken for abnormal behaviors of different degrees, and subsequent equipment reservation rules and benchmark models can be optimized, continuously improving the safety of laboratory equipment management and the rationality of resource allocation.

[0141] S6. Generate a usage report for the laboratory equipment based on the usage status information of the laboratory equipment, and update the status database of the laboratory equipment.

[0142] In this embodiment of the invention, generating a usage report for the laboratory equipment based on its usage status information and updating the status database of the laboratory equipment includes:

[0143] By comparing the device runtime of the laboratory equipment using the status information with the reservation time range, the usage time analysis data of the laboratory equipment is obtained;

[0144] Based on the usage period analysis data and the function call records and operation instruction sequences in the usage status information, a usage report of the laboratory equipment is generated;

[0145] Based on the key indicators in the usage report, update the equipment status records in the status database of the laboratory equipment, and simultaneously adjust the available status indicators of the laboratory equipment.

[0146] Extract the actual start and end times of the equipment from the usage status information of the laboratory equipment, calculate the difference between the two times to obtain the actual running time of the equipment; simultaneously retrieve the user reservation time range corresponding to the equipment, i.e., the reservation start and end times; compare the difference between the actual running time and the reservation time range, for example, the actual running time is 8 minutes longer or 3 minutes shorter than the reservation time; compare the overlap between the actual running period and the reservation period, for example, whether the actual operation is completely within the reservation period, or whether there are cases of starting 10 minutes early and shutting down 5 minutes late; in addition, it is necessary to count the continuity of operation within the actual running period, such as whether there are any interruptions and the specific duration of the interruptions; organize these data on duration differences, time period overlap, and operational continuity into a structured table, which is the data for analyzing the usage period of the laboratory equipment.

[0147] Extract the function call records from the usage status information. These records include the names of all functions called during this device usage, such as "sample centrifugation function" and "data export function," the number of times each function was called (e.g., "sample centrifugation function called 2 times"), and the duration of each call (e.g., "first sample centrifugation function lasted 20 minutes"). Simultaneously, extract the operation command sequence, which includes all operation commands executed during this usage, such as "power-on command," "parameter setting command," and "power-off command," the order in which the commands were executed, and the result of each command (e.g., "execution successful" or "execution failed"). Integrate the usage periods according to the preset usage report template. The template analyzes data, function call records, and operation instruction sequences. It includes four fixed sections: "Basic Equipment Information," "Usage Time Details," "Function Call Statistics," and "Operation Instruction Details." The "Basic Equipment Information" section is for the equipment number, user, and reservation time range. The "Usage Time Details" section is for the actual runtime, the difference between the actual runtime and the reserved runtime, and any overlap in time periods. The "Function Call Statistics" section is for the function name, the number of calls, and the longest and shortest single call duration. The "Operation Instruction Details" section is for the instruction sequence, execution results, and explanations of any abnormal instructions. After filling in all the data in all sections, a complete written document is generated, which is the laboratory equipment usage report.

[0148] Key metrics are selected from the generated usage report. These metrics include the total actual operating time of the equipment, the normal execution rate of function calls (e.g., a normal execution rate of 100% is achieved if all four function calls are executed normally), the number of abnormal commands in the operation instructions (e.g., one command that failed to execute), and the final status of the equipment at the end of operation, such as "normal shutdown" or "fault shutdown." Based on these key metrics, the laboratory equipment status database is updated: a new usage record is added to the equipment status record, including the user's identity information, the actual start and end times of use, and the total actual operating time; the equipment function status field is updated, and if the function call... If all functions are normal, mark it as "All functions are operating normally". If a function call fails, mark it as "A function needs maintenance". Add abnormal record entries. If there are abnormal commands, record the command content, execution time and reason for failure. Adjust the equipment's availability status indicator synchronously according to key indicators: if the equipment is operating normally, there are no abnormal commands, and the actual use does not exceed the reservation limit, the availability status indicator is set to "Normal and available". If there is a functional failure or a fault shutdown, the indicator is set to "Pending maintenance". If the actual running time exceeds the reservation time and there is no reasonable explanation, the indicator is set to "Manual verification required". Complete the status database update and availability status indicator adjustment.

[0149] The beneficial effects include: by meticulously comparing actual equipment operation times with reserved times, ensuring that the data analysis of usage periods accurately reflects the time compliance of equipment use, and providing an objective basis for subsequent usage evaluation; integrating multi-dimensional information such as time, function, and instructions to generate usage reports, comprehensively presenting the entire process of equipment use, making it easier for managers to quickly grasp the details of equipment operation and potential problems; and updating the status database in real time based on key indicators in the report and adjusting the available status indicators to achieve dynamic synchronization of equipment status, providing accurate equipment status references for subsequent user reservations, and providing clear data support for management work such as equipment maintenance and violation verification, effectively improving the standardization and efficiency of laboratory equipment management.

[0150] like Figure 2 The diagram shown is a functional block diagram of a laboratory equipment reservation and access linkage control system provided in an embodiment of the present invention.

[0151] The laboratory equipment reservation and access control system 100 described in this invention can be installed in an electronic device. Depending on the functions implemented, the laboratory equipment reservation and access control system 100 may include a reservation request verification module 101, a resource allocation module 102, an access instruction generation module 103, an access permission activation module 104, a resource allocation strategy adjustment module 105, and an equipment status update module 106. The module described in this invention can also be referred to as a unit, which refers to a series of computer program segments that can be executed by the processor of an electronic device and can perform a fixed function, and are stored in the memory of the electronic device.

[0152] In this embodiment, the functions of each module / unit are as follows:

[0153] The verification appointment request module 101 is used to verify the legality of the user identity information and device identification information in the user appointment request, and obtain the user's appointment verification result;

[0154] The resource allocation module 102 is used to dynamically allocate resources based on the real-time status data of the laboratory equipment and the reservation time range when the reservation verification result is passed, so as to obtain the resource allocation strategy of the laboratory equipment.

[0155] The access instruction generation module 103 is used to construct a unique access token for the user by using the core scheduling parameters of the resource allocation strategy as the first key and the user identity information as the second key, and to encode the scheduling instructions in the resource allocation strategy into the unique access token to generate the access control instructions for the laboratory equipment.

[0156] The access permission activation module 104 is used to input the access control command before the scheduled time of the laboratory equipment to activate the access permission of the laboratory equipment.

[0157] The resource allocation strategy adjustment module 105 is used to identify abnormal patterns in the operation log data of the laboratory equipment: if abnormal usage behavior is identified, the access permission is automatically revoked and the resource allocation strategy is adjusted synchronously.

[0158] The equipment status update module 106 is used to generate a usage report of the laboratory equipment based on the usage status information of the laboratory equipment, and update the status database of the laboratory equipment.

[0159] In the several embodiments provided by this invention, it should be understood that the disclosed methods and systems can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and other division methods may be used in actual implementation.

[0160] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0161] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.

[0162] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0163] This application embodiment can acquire and process relevant data based on artificial intelligence technology. Artificial intelligence is the theory, method, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0164] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for linking laboratory equipment reservation and access control, characterized in that, The method includes: S1. Verify the legality of the user's identity information and device identification information in the user's reservation request, and obtain the user's reservation verification result; S2. When the reservation verification result is passed, the real-time status data of the laboratory equipment and the reservation time range are dynamically allocated to obtain the resource allocation strategy of the laboratory equipment. S3. Use the core scheduling parameters of the resource allocation strategy as the first key and the user identity information as the second key to construct a unique access token for the user, and encode the scheduling instructions in the resource allocation strategy into the unique access token to generate the access control instructions for the laboratory equipment. S4. Before the scheduled time for the laboratory equipment, enter the access control command to activate the access rights of the laboratory equipment; S5. Perform abnormal pattern recognition on the operation log data of the laboratory equipment: if abnormal usage behavior is detected, automatically revoke the access permission and adjust the resource allocation strategy accordingly. S6. Generate a usage report for the laboratory equipment based on the usage status information of the laboratory equipment, and update the status database of the laboratory equipment.

2. The laboratory equipment reservation and access linkage control method as described in claim 1, characterized in that, The process of verifying the legality of the user's identity information and device identification information in the user's reservation request to obtain the user's reservation verification result includes: The core identity fields in the user's identity information are used as the data blocks to be encrypted, and the data blocks to be encrypted are encrypted to obtain the user's encrypted identifier data. The device identification information is hashed to obtain the hash sequence of the laboratory equipment; The encrypted identifier data and the hash sequence are mapped to a pre-stored authorization database, and the encrypted identifier data and the hash sequence are compared item by item to obtain the user's preliminary verification result; Verify the completeness of the preliminary verification results to obtain the user's appointment verification result.

3. The laboratory equipment reservation and access linkage control method as described in claim 1, characterized in that, When the reservation verification result is successful, dynamic resource allocation is performed on the real-time status data of the laboratory equipment and the reservation time range to obtain the resource allocation strategy for the laboratory equipment, including: The data format of the real-time status data of the laboratory equipment is standardized to obtain the standard status data of the laboratory equipment. The reservation time range of the laboratory equipment is segmented to obtain the time window of the reservation time range, and the duration feature of the time window is extracted; By detecting the temporal conflict between the standard state data and the duration feature, resource conflict data of the laboratory equipment is obtained. Based on the resource conflict data, the allocation scheme of the laboratory equipment is dynamically adjusted to obtain the resource allocation strategy of the laboratory equipment.

4. The laboratory equipment reservation and access linkage control method as described in claim 1, characterized in that, The process involves using the core scheduling parameters of the resource allocation strategy as the first key and the user's identity information as the second key to construct a unique access token for the user. The scheduling instructions from the resource allocation strategy are then encoded into the unique access token to generate access control instructions for the laboratory equipment. This process includes: The core scheduling parameters of the resource allocation strategy are parsed and encrypted to obtain the user's first key. The user's identity information is digested to obtain the user's second key; The first key and the second key are bound together as the user's token infrastructure; The specific components of the token infrastructure are encoded to obtain the user's unique access token.

5. The laboratory equipment reservation and access linkage control method as described in claim 1, characterized in that, The process involves using the core scheduling parameters of the resource allocation strategy as the first key and the user's identity information as the second key to construct a unique access token for the user. The scheduling instructions from the resource allocation strategy are then encoded into the unique access token to generate access control instructions for the laboratory equipment. This process includes: Semantic parsing is performed on the scheduling instructions in the resource allocation strategy to obtain the instruction opcode and parameter set of the scheduling instructions; A fixed identifier header is assigned to the instruction opcode, and a corresponding type identifier is assigned to the parameters in the parameter set; The identifier header and the type identifier are combined in a predetermined order to obtain the encoded sequence of the scheduling instruction; The encoded sequence is embedded into a designated data segment of the unique access token, and the designated data segment is encapsulated for data integrity to obtain the access control instruction for the laboratory equipment.

6. The laboratory equipment reservation and access linkage control method as described in claim 1, characterized in that, The process involves identifying abnormal patterns in the operation log data of the laboratory equipment. If abnormal usage behavior is detected, the access permissions are automatically revoked, and the resource allocation strategy is adjusted accordingly, including: By analyzing the deviation between the operational behavior characteristics of the operation log data in the laboratory equipment and the preset benchmark operation model, the potential abnormal behavior characteristics of the laboratory equipment can be obtained. Risk assessment is performed on the potential abnormal behavior characteristics to obtain the abnormal behavior determination result of the laboratory equipment; When the abnormal behavior is determined to be abnormal, the user's access permissions are revoked. Based on the severity level of the abnormal behavior determination result, the scheduling parameters of the resource allocation strategy are updated synchronously.

7. The laboratory equipment reservation and access linkage control method as described in claim 6, characterized in that, The step of conducting a risk assessment on the potential abnormal behavior characteristics to obtain the abnormal behavior determination result of the laboratory equipment includes: The potential abnormal behavior features are vectorized and fitted to obtain the risk feature vector of the laboratory equipment. The risk feature vector is evaluated at multiple levels to obtain the risk level of abnormal behavior of the laboratory equipment. The logical rationality and severity of the risk level of the abnormal behavior are judged to obtain the abnormal behavior judgment result of the laboratory equipment.

8. The laboratory equipment reservation and access linkage control method as described in claim 7, characterized in that, The process of performing multi-level evaluation on the risk feature vector to obtain the abnormal behavior risk level of the laboratory equipment includes: A comprehensive analysis of the risk feature vector yields the comprehensive risk value of the laboratory equipment, wherein the formula for calculating the comprehensive risk value is as follows: ； in, This represents the overall risk value. This represents the dimension of the risk feature vector. Indicates the first The weight coefficients of the aforementioned risk feature vectors, This indicates the preset scaling factor. Indicates the first The aforementioned risk feature vectors, Represents a logarithmic function; The comprehensive risk value is mapped to the risk level table of the laboratory equipment to obtain the abnormal behavior risk level of the laboratory equipment.

9. The laboratory equipment reservation and access linkage control method as described in claim 1, characterized in that, The step of generating a usage report for the laboratory equipment based on its usage status information and updating the laboratory equipment status database includes: By comparing the device runtime of the laboratory equipment using the status information with the reservation time range, the usage time analysis data of the laboratory equipment is obtained; Based on the usage period analysis data and the function call records and operation instruction sequences in the usage status information, a usage report of the laboratory equipment is generated; Based on the key indicators in the usage report, update the equipment status records in the status database of the laboratory equipment, and simultaneously adjust the available status indicators of the laboratory equipment.

10. A laboratory equipment reservation and access linkage control system, used to implement the laboratory equipment reservation and access linkage control method according to claim 1, the system comprising: The appointment verification module is used to verify the legality of the user's identity information and device identification information in the user's appointment request, and obtain the user's appointment verification result; The resource allocation module is used to dynamically allocate resources to the real-time status data of the laboratory equipment and the reservation time range when the reservation verification result is passed, so as to obtain the resource allocation strategy of the laboratory equipment. The access instruction generation module is used to construct a unique access token for the user by using the core scheduling parameters of the resource allocation strategy as the first key and the user identity information as the second key, and to encode the scheduling instructions in the resource allocation strategy into the unique access token to generate the access control instructions for the laboratory equipment. The access permission activation module is used to activate the access permission of the laboratory equipment by inputting the access control command before the scheduled time of the laboratory equipment. The resource allocation strategy adjustment module is used to identify abnormal patterns in the operation log data of the laboratory equipment: if abnormal usage behavior is identified, the access permission is automatically revoked and the resource allocation strategy is adjusted synchronously. The equipment status update module is used to generate a usage report of the laboratory equipment based on the usage status information of the laboratory equipment, and to update the status database of the laboratory equipment.

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