An Internet of Things-based intelligent laboratory management system and access control method

Abstract

The present application provides an Internet of Things-based intelligent laboratory management system and an access control method, which can perform area error node positioning on the access verification information of error positioning objects in the area according to different access verification information, and obtain sensing error positioning nodes corresponding to different access verification information positioning areas respectively; perform associated depth verification to obtain the associated depth and characteristic distance corresponding to each access verification object and the sensing error positioning node of the area respectively; perform access control according to the characteristic distance and associated depth between the access verification information corresponding to each access verification object and the sensing error positioning node of the area, so that error node positioning can be performed according to the access verification information of the error positioning object, and access control can be performed according to the sensing error positioning node, reducing the access misjudgment rate caused by sensor errors.

Description

Technical Field

[0001] This application relates to the technical field of laboratory access control, and more specifically, to an intelligent laboratory management system and an access control method based on the Internet of Things, such as terminal devices, chips, computer storage media, etc. Background Art

[0002] The application of access control alarm monitoring networking technology in modern laboratories marks the further upgrading and intelligentization of security prevention. With the booming development of the research industry and the increasing personnel flow, laboratory security management has become more critical. The security requirements of laboratories are highly complex, and the security measures achieved by increasing personnel cannot meet the current needs of laboratories. Therefore, the networking integration of access control, alarm, and monitoring systems has become an important strategy to improve the overall security of laboratories.

[0003] In the existing laboratory access control management system, the facial information or other types of biometric features of external personnel are mainly collected through Internet of Things sensors, and the personnel identity is identified by comparing with the personnel information stored in the database, and different access control permissions are assigned. This method is often interfered by the device errors of Internet of Things sensors, resulting in misjudgment of access control, increasing the passing time required for access control personnel. Therefore, how to improve the accuracy rate of the access control process has become an urgent problem to be solved. Summary of the Invention

[0004] This application provides an intelligent laboratory management system and an access control method based on the Internet of Things, which can locate the error nodes according to the access control verification information of the error positioning object, and perform access control according to the sensing error positioning nodes, reducing the misjudgment rate of access control caused by sensor errors.

[0005] In the first aspect, this application provides an access control method, which can be executed by a network device, or can also be executed by a chip configured in the network device. This application does not make any limitations in this regard.

[0006] Specifically, the method includes:

[0007] Obtain a set of access control verification information, perform information repositioning on the access control verification information corresponding to each access control verification object in the set of access control verification information to obtain multiple access control verification information positioning regions, obtain the access control information comparison result, and extract the error positioning object and the access control verification object in different access control verification information positioning regions based on the access control information comparison result;

[0008] Perform regional error node positioning according to the access control verification information of the error positioning object in different access control verification information positioning regions to obtain the sensing error positioning nodes corresponding to different access control verification information positioning regions respectively;

[0009] For any access control verification information positioning area, perform association depth verification on the access control verification information corresponding to each access control verification object in this access control verification information positioning area respectively with the sensing error positioning nodes in this area, to obtain the association depths corresponding to each access control verification object and the sensing error positioning nodes in this area respectively;

[0010] Determine the characteristic distances between the access control verification information corresponding to each access control verification object and the sensing error positioning nodes in this area respectively; perform access control according to the characteristic distances and the association depths between the access control verification information corresponding to each access control verification object and the sensing error positioning nodes in this area respectively.

[0011] Combined with the first aspect, in some implementation manners of the first aspect, obtaining the access control verification information set specifically includes: collecting access control information for each access control verification object through an Internet of Things terminal device to obtain the access control verification information set.

[0012] Combined with the first aspect, in some implementation manners of the first aspect, obtaining the access control information comparison result specifically includes: obtaining the user storage information in the Internet of Things terminal device, and performing access control information comparison on the access control verification information set according to the user storage information to obtain the access control information comparison result.

[0013] Combined with the first aspect, in some implementation manners of the first aspect, performing information repositioning on the access control verification information corresponding to each access control verification object in the access control verification information set respectively to obtain multiple access control verification information positioning areas specifically includes: determining an access control adjustment index based on the minimum cosine similarity between the access control verification information corresponding to each access control verification object in the access control verification information set and the standard access control verification information corresponding to each access control user respectively; performing information repositioning on the access control verification information corresponding to each access control user in the access control verification information set respectively based on the access control adjustment index to obtain multiple access control verification information positioning areas.

[0014] Combined with the first aspect, in some implementation manners of the first aspect, performing information repositioning on the access control verification information corresponding to each access control user in the access control verification information set respectively based on the access control adjustment index to obtain multiple access control verification information positioning areas specifically includes:

[0015] Obtain the access control verification information corresponding to each access control verification object in the access control verification information set respectively, and form an access control verification information multi-dimensional space;

[0016] Obtain the access control adjustment index, and perform information clustering on the access control verification information multi-dimensional space based on the access control adjustment index to obtain multiple access control verification information positioning areas.

[0017] In combination with the first aspect, in certain implementations of the first aspect, an information storage unit is installed in the Internet of Things terminal device, and the information storage unit is used to store real-time access control verification information and pre-stored user storage information.

[0018] In combination with the first aspect, in certain implementations of the first aspect, for the access control verification information of the error positioning objects in the positioning area according to different access control verification information, area error node positioning is performed to obtain the sensing error positioning nodes respectively corresponding to different access control verification information positioning areas, which specifically includes:

[0019] For any access control verification information positioning area, obtain the deviation characteristics between the access control verification information of each error positioning object in the access control verification information positioning area and the corresponding access control verification information in the user storage information, and determine the dynamic error positioning node according to the deviation characteristics;

[0020] Determine the static error positioning node according to the mean characteristics of the access control verification information of each error positioning object; perform node positioning according to the dynamic error positioning node and the static error positioning node to obtain the sensing error positioning node corresponding to this access control verification information positioning area.

[0021] In the second aspect, the present application provides an Internet of Things-based intelligent laboratory management system, which includes an access control unit, and the access control unit includes:

[0022] An information processing module, configured to obtain an access control verification information set, perform information repositioning on the access control verification information corresponding to each access control verification object in the access control verification information set to obtain multiple access control verification information positioning areas, obtain an access control information comparison result, and extract error positioning objects and access control verification objects in different access control verification information positioning areas based on the access control information comparison result;

[0023] An access control module, configured to perform area error node positioning according to the access control verification information of the error positioning objects in different access control verification information positioning areas to obtain the sensing error positioning nodes respectively corresponding to different access control verification information positioning areas;

[0024] The access control module is further configured to obtain the access control verification information corresponding to each access control verification object in the access control verification information of the access control verification object; perform association depth verification between the access control verification information corresponding to each access control verification object and the sensing error positioning node of this area respectively to obtain the association depth respectively corresponding to each access control verification object and the sensing error positioning node of this area;

[0025] The access control module is further configured to determine the characteristic distances between the access verification information corresponding to each access verification object and the sensing error positioning nodes in this area; and perform access control according to the characteristic distances and the association depths between the access verification information corresponding to each access verification object and the sensing error positioning nodes in this area.

[0026] In a third aspect, the present application provides a computer terminal device, which includes a memory and a processor. The memory stores code, and the processor is configured to obtain the code and execute the above-mentioned access control method.

[0027] In a fourth aspect, the present application provides a computer-readable storage medium, which stores at least one computer program. The computer program is loaded and executed by a processor to implement the operations performed by the above-mentioned access control method.

[0028] The technical solutions provided by the disclosed embodiments of the present application have the following beneficial effects:

[0029] In the intelligent laboratory management system and access control method based on the Internet of Things provided by the present application, first, information repositioning is performed on the access verification information corresponding to each access verification object in the access verification information set to obtain multiple access verification information positioning areas, and the access information comparison result is obtained. Based on the access information comparison result, the error positioning objects and access verification objects in different access verification information positioning areas are extracted; regional error node positioning is performed according to the access verification information of the error positioning objects in different access verification information positioning areas to obtain the sensing error positioning nodes corresponding to different access verification information positioning areas respectively; for any one access verification information positioning area, association depth verification is performed between the access verification information corresponding to each access verification object in this access verification information positioning area and the sensing error positioning node in this area to obtain the association depths corresponding to each access verification object and the sensing error positioning node in this area respectively; the characteristic distances between the access verification information corresponding to each access verification object and the sensing error positioning node in this area are determined; and access control is performed according to the characteristic distances and the association depths between the access verification information corresponding to each access verification object and the sensing error positioning node in this area.

[0030] Therefore, it can be seen that in this application, through information relocation, the access control verification information is divided into multiple positioning areas, and the sensing error positioning nodes are determined according to the access control verification information of the error positioning objects in each area. The access control verification information of the access control object only needs to be compared with a few sensing error positioning nodes, rather than all the historical stored information. The access control verification information of the access control object only needs to be matched with the closest sensing error positioning node, avoiding misidentification caused by the complexity of data distribution. And the access control adjustment index is determined according to the real-time passing situation, so as to dynamically adjust the comparison range and update the sensing error positioning nodes, avoiding the decline of recognition accuracy caused by long-term non-update. Moreover, in this application, the sensing error positioning nodes are determined according to the access control verification information of the error positioning objects in the area, so that the sensor error in the access control process can also be detected by the sensing error positioning nodes, reducing the access control misjudgment caused by sensor error and greatly improving the accuracy and recognition efficiency of the access control process.

[0031] In summary, this application can locate the error nodes according to the access control verification information of the error positioning objects, and perform access control according to the sensing error positioning nodes, reducing the access control misjudgment rate caused by sensor error. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 is an exemplary flowchart of an access control method according to some embodiments of this application;

[0033] Figure 2 is an exemplary flowchart for implementing access control information comparison in some embodiments of this application;

[0034] Figure 3 is a schematic structural diagram of an access control unit according to some embodiments of this application;

[0035] Figure 4 is a schematic structural diagram of a computer terminal device for implementing the access control method according to some embodiments of this application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0036] In this application, information repositioning is performed on the access control verification information corresponding to each access control verification object in the access control verification information set to obtain multiple access control verification information positioning regions. Region error node positioning is performed based on the access control verification information of the error positioning objects in different access control verification information positioning regions to obtain sensing error positioning nodes corresponding to different access control verification information positioning regions respectively. For any access control verification information positioning region, association depth verification is performed between the access control verification information corresponding to each access control verification object in this access control verification information positioning region and the sensing error positioning node of this region to obtain the association depths corresponding to each access control verification object and the sensing error positioning node of this region respectively. The characteristic distances between the access control verification information corresponding to each access control verification object and the sensing error positioning node of this region are determined. Access control is performed based on the characteristic distances and association depths between the access control verification information corresponding to each access control verification object and the sensing error positioning node of this region, so that error node positioning can be performed based on the access control verification information of the error positioning objects, and access control can be performed based on the sensing error positioning nodes, reducing the false judgment rate of access control caused by sensor errors.

[0037] To better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings of the specification and specific embodiments. Refer to Figure 1 , which is an exemplary flowchart of an access control method shown according to some embodiments of the present application. The access control method 100 mainly includes the following steps:

[0038] In step S101, an access control verification information set is obtained, information repositioning is performed on the access control verification information corresponding to each access user in the access control verification information set to obtain multiple access control verification information positioning regions, an access information comparison result is obtained, and error positioning objects and access control verification objects in different access control verification information positioning regions are extracted based on the access information comparison result.

[0039] Optionally, in some embodiments, obtaining the access control verification information set specifically includes: collecting access control information for each access user through an Internet of Things terminal device to obtain an access control verification information set.

[0040] Optionally, in some embodiments, obtaining the access information comparison result specifically includes: obtaining user storage information in the Internet of Things terminal device, and performing access information comparison on the access control verification information set according to the user storage information to obtain an access information comparison result.

[0041] Optionally, in some embodiments, the IoT terminal device includes IoT sensors. Specifically, the IoT terminal device includes a camera (IoT sensor), an RFID reader, a biometric sensor, a Bluetooth module, etc., which are not elaborated in this application.

[0042] It should be noted that the access control users are the target users who need to pass through the laboratory access control. By collecting access control information for each access control user, the identity of each access control user can be identified and the corresponding access control permissions can be granted, thereby improving the security of laboratory access control management.

[0043] Optionally, in some embodiments, the access control verification information set contains the access control verification information corresponding to each access control user. Specifically, the access control verification information can be a feature vector, which is used to store the information features collected by the IoT terminal device. For example, when the IoT terminal device collects the facial image of an access control user, the FaceNet deep learning model carried by the storage chip in the IoT terminal device can be used to extract the feature vector of the facial image of the access control user, and this feature vector is used as the access control verification information of the access control user. In some other embodiments, other types of biometrically recognizable features can also be collected by the IoT terminal device for feature comparison, and the feature vector extraction method commonly used in other existing technologies can be used to extract the feature vector and use it as the access control verification information of the access control user. This application does not make any limitations in this regard.

[0044] Optionally, in some embodiments, an information storage unit is installed in the IoT terminal device. The information storage unit is used to store real-time access control verification information and pre-stored user storage information. Among them, the user storage information is the user identity information pre-stored in the IoT terminal device, which is used to compare with the real-time collected access control verification information to determine the user identity and grant the corresponding access control permissions, thereby improving the security of laboratory access control management. Specifically, to improve the information comparison rate, the storage form of the user storage information can be a feature vector with the same dimension as the access control verification information.

[0045] Optionally, in some embodiments, refer to Figure 2 As shown, this figure is an exemplary flowchart for implementing access control information comparison in some embodiments of this application. The access control information comparison of the access control verification information set according to the user storage information to obtain the access control information comparison result can be implemented by the following steps:

[0046] In step S1011, obtain the standard access control verification information corresponding to each access control user in the user storage information;

[0047] In step S1012, obtain the access control verification information corresponding to each access control user in the access control verification information set;

[0048] In step S1013, for any access control user, calculate the cosine similarity between the access control verification information corresponding to this access control user and the standard access control verification information corresponding to each access control user. When there is a cosine similarity lower than the preset threshold, it is determined that this access control user passes the comparison successfully.

[0049] Preferably, in some embodiments, information repositioning is performed on the access control verification information corresponding to each access control verification object in the access control verification information set to obtain multiple access control verification information positioning regions, which specifically includes: determining an access control adjustment index based on the minimum cosine similarity between the access control verification information of each access control verification object in the access control verification information set and the standard access control verification information corresponding to each access control user; performing information repositioning on the access control verification information corresponding to each access control user in the access control verification information set based on the access control adjustment index to obtain multiple access control verification information positioning regions.

[0050] It should be noted that the access control adjustment index is an adjustment coefficient determined according to the verification success rate and feature similarity degree in the access control verification information set. The access control adjustment index is used to adjust the number of nodes of the sensing error positioning node. When the access control user verification success rate in the access control verification information set is lower and the feature similarity degree in the access control verification information set is smaller, the corresponding access control adjustment index is larger, so that the sensing error positioning node can be dynamically updated according to the real-time access control situation, avoiding the decline of recognition accuracy caused by long-term non-update, and increasing the security of laboratory access control.

[0051] Specifically, the access control adjustment index is the average value of the minimum cosine similarity between each access control user and the standard access control verification information corresponding to each access control user / a preset standard access control adjustment index, and the standard access control adjustment index is calibrated as a constant.

[0052] Optionally, in some embodiments, determining the corresponding access control adjustment index according to the access control information comparison result can also be implemented in the following manner: determining the comparison success rate of the access control user according to the access control information comparison result, obtaining a preset mapping table, and mapping the comparison success rate to the corresponding access control adjustment index according to the mapping table. Specifically, the higher the comparison success rate, the smaller the mapped access control adjustment index.

[0053] Optionally, in some embodiments, when the access control adjustment index is higher than the preset threshold, information repositioning is performed on the access control verification information corresponding to each access control user in the access control verification information set to obtain multiple access control verification information positioning regions.

[0054] It should be noted that when the access control adjustment index is higher than the preset threshold, it indicates that due to factors such as environmental interference or sensor detection accuracy deviation, the success rate of access control user verification is low, and the similarity degree of features in the access control verification information set is small. At this time, it is necessary to perform information repositioning on the access control verification information corresponding to each access control user in the access control verification information set to obtain multiple access control verification information positioning regions, and extract positioning nodes based on the access control verification information positioning regions for identity verification, so as to reduce the interference of factors such as environmental interference or sensor detection accuracy deviation, improve the recognition accuracy and recognition efficiency of laboratory access control, and improve the security of access control identity recognition.

[0055] Optionally, in some embodiments, when the access control adjustment index is lower than the preset threshold, the access control is controlled to be opened or not based on the access control information comparison result, that is, when the comparison result of the access control information of the access control user is qualified, the access control is opened.

[0056] Optionally, in some embodiments, the information repositioning of the access control verification information corresponding to each access control user in the access control verification information set to obtain multiple access control verification information positioning regions can be implemented by the following steps:

[0057] Obtain the access control verification information corresponding to each access control object in the access control verification information set and form a multi-dimensional space of access control verification information;

[0058] Obtain the access control adjustment index, and perform information clustering on the multi-dimensional space of access control verification information based on the access control adjustment index to obtain multiple access control verification information positioning regions.

[0059] It should be noted that the multi-dimensional space of the access control verification information is a vector space containing multiple feature vectors, and the dimensionality of the vector space is consistent with the vector dimensionality of the feature vectors. In some embodiments, for the convenience of information clustering, the feature vectors can be stored in the multi-dimensional space of the access control verification information in the form of data points. Specifically, the multi-dimensional space of the access control verification information contains the feature vectors in the access control verification information corresponding to each access control verification object respectively. Preferably, in some embodiments, according to the threshold interval where the access control adjustment index is located, the access control adjustment index can be mapped to the corresponding number of regions. For example, when the data interval of the access control adjustment index is from 0 to 1, a linear mapping method can be used to map the access control adjustment index to an integer from 1 to 20 as the number of regions, and according to the corresponding number of regions, K-means clustering is used to cluster the access control verification information in the multi-dimensional space of the access control verification information to obtain multiple access control verification information positioning regions. It should be noted that the access control verification information positioning region is a sub-region of the multi-dimensional space of the access control verification information, and each access control verification information positioning region contains the access control verification information corresponding to multiple access control verification objects respectively.

[0060] It should be noted that the error positioning object is part of the access control users who collect information for positioning the sensor error. Specifically, in implementation, the part of the access control users who pass the comparison in the process of comparing the access control information can be extracted as the error positioning object. The access control verification object is part of the access control users who need to perform access control according to the sensor error positioning node for the collected information. Specifically, in implementation, the part of the access control users who fail the comparison in the process of comparing the access control information can be used as the access control verification object. There is a certain proportion of access control misjudgments in the access control verification information of the access control verification object due to sensor interference. In this application, the sensor error positioning node is determined through the information characteristics of the access control verification information of the adjacent error positioning objects, so as to realize the identity recognition of the access control verification object. In the case of the same sensor acquisition environment, the interference characteristics of part of the environment and sensor error can be located through the sensor error positioning node. For example, when there is a detection error in a certain direction of the sensor, the sensor error positioning node determined through the information characteristics of the access control verification information of the adjacent error positioning objects can store this part of the detection error. Identifying the identity of the access control verification object according to the sensor error positioning node can dynamically adjust the positioning node according to the sensor error, thereby reducing the access control misjudgment of the access control verification information of the access control verification object caused by equipment error and improving the robustness of the access control recognition process in the laboratory.

[0061] In step S102, the regional error nodes are located according to the access control verification information of the error positioning objects in different access control verification information positioning regions, and the sensor error positioning nodes corresponding to different access control verification information positioning regions are obtained.

[0062] It should be noted that the sensing error positioning node is an information node containing error characteristics obtained after extracting sensor error information based on the acquisition information of the error positioning object. Optionally, in some embodiments, the regional error node positioning is performed according to the access control verification information of the error positioning object in different access control verification information positioning regions, and the sensing error positioning nodes corresponding to different access control verification information positioning regions can be implemented by the following steps:

[0063] For any access control verification information positioning region, obtain the deviation characteristics between the access control verification information of each error positioning object in the access control verification information positioning region and the corresponding access control verification information in the user storage information, and determine the dynamic error positioning node according to the deviation characteristics. Specifically, when implementing, extract the mean characteristic of each deviation characteristic as the dynamic error positioning node;

[0064] Determine the static error positioning node according to the mean characteristics of the access control verification information of each error positioning object. Specifically, when implementing, the mean characteristic of the access control verification information of each error positioning object can be extracted as the static error positioning node;

[0065] Perform node positioning according to the dynamic error positioning node and the static error positioning node to obtain the sensing error positioning node corresponding to this access control verification information positioning region. Specifically, when implementing, the sum of the mean characteristics of the dynamic error positioning node and the mean characteristics of the static error positioning node can be used as the sensing error positioning node of this region.

[0066] In step S103, for any access control verification information positioning region, perform an association depth verification between the access control verification information corresponding to each access control verification object in this access control verification information positioning region and the sensing error positioning node of this region to obtain the association depth corresponding to each access control verification object and the sensing error positioning node of this region respectively.

[0067] It should be noted that the associated depth is the degree of similarity between the access control verification information and the sensing error positioning node in this area. When the environment and Internet of Things sensor interference are greater, the greater the amount of common interference information between the access control verification information and the sensing error positioning node in this area. According to the associated depth, the present application adjusts the recognition accuracy of the identity recognition process, and can increase the recognition efficiency of some access control verification objects during access control when interfered by Internet of Things sensors. Optionally, in some embodiments, the associated depth verification of the access control verification information corresponding to each access control verification object and the sensing error positioning node in this area is performed respectively, and the associated depth corresponding to each access control verification object can be obtained by the following steps: For any access control verification object, the characteristic elements of the access control verification information corresponding to this access control verification object and the characteristic elements of the sensing error positioning node in this area are respectively obtained, and the characteristic sequences are respectively formed in sequence according to the dimensions. Based on the Pearson correlation coefficient between the characteristic sequences, the associated depth corresponding to this access control verification object is determined.

[0068] In step S104, the characteristic distances between the access control verification information corresponding to each access control verification object and the sensing error positioning node in this area are determined; access control is performed according to the characteristic distances and the associated depth between the access control verification information corresponding to each access control verification object and the sensing error positioning node in this area.

[0069] Optionally, in some embodiments, the determination of the characteristic distances between the access control verification information corresponding to each access control verification object and the sensing error positioning node in this area can be implemented by the following steps: Locate the Euclidean distances between the access control verification information corresponding to each access control verification object and the sensing error positioning node in the access control verification information positioning area, and use them as the characteristic distances between the access control verification information corresponding to each access control verification object and the sensing error positioning node in this area.

[0070] Optionally, in some embodiments, access control based on the characteristic distances and association depths between the access verification information corresponding to each access verification object and the sensing error positioning nodes in this area can be implemented by the following steps: Determine the recognition thresholds corresponding to each access verification object according to the association depths between each access verification object and the sensing error positioning nodes in this area. Based on the characteristic distances and recognition thresholds between each access verification object and the sensing error positioning nodes in this area, perform identity recognition on each access verification object in this area to obtain the identity recognition results of each access verification object in this area. Perform access control according to the identity recognition results. Specifically, when implementing, the product of the association depth and a preset standard threshold can be used as the recognition threshold. When the characteristic distance between this access verification object and the sensing error positioning node in this area is lower than the recognition threshold compared with the characteristic distance between the access verification object and the average characteristic of the access verification information of the users in this area in the user storage information, it is determined that the identity recognition of this access verification object passes, and an access opening operation is performed.

[0071] In addition, on the other hand of the present application, in some embodiments, the present application provides an intelligent laboratory management system based on the Internet of Things. The device includes an access control unit. Refer to Figure 3 , this figure is a schematic structural diagram of the access control unit according to some embodiments of the present application. The access control unit 200 includes: an information processing module 201 and an access control module 202, which are described as follows:

[0072] The information processing module 201 is used to obtain an access verification information set, perform information repositioning on the access verification information corresponding to each access verification object in the access verification information set to obtain multiple access verification information positioning areas, obtain an access information comparison result, and extract error positioning objects and access verification objects in different access verification information positioning areas based on the access information comparison result;

[0073] The access control module 202 is used to perform regional error node positioning according to the access verification information of the error positioning objects in different access verification information positioning areas to obtain the sensing error positioning nodes corresponding to different access verification information positioning areas respectively;

[0074] The access control module 202 is further used to obtain the access verification information corresponding to each access verification object in the access verification information of the access verification object; perform association depth verification between the access verification information corresponding to each access verification object and the sensing error positioning nodes in this area respectively to obtain the association depths corresponding to each access verification object and the sensing error positioning nodes in this area respectively;

[0075] The access control module 202 is further configured to determine the characteristic distances between the access verification information corresponding to each access verification object and the sensing error positioning nodes in this area; and perform access control according to the characteristic distances between the access verification information corresponding to each access verification object and the sensing error positioning nodes in this area and the association depth.

[0076] The above has introduced in detail an example of an Internet of Things-based intelligent laboratory management system and an access control method provided by the embodiments of the present application. It can be understood that, in order to implement the above functions, the corresponding device includes the corresponding hardware structure and / or software module for executing each function.

[0077] Those skilled in the art should easily realize that, combining the units and algorithm steps of each example described in the embodiments disclosed in this article, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a certain function in the application is executed in the way of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Therefore, professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0078] In addition, the present application further provides a computer terminal device, where the computer terminal device includes a memory and a processor. The memory stores code, and the processor is configured to obtain the code and execute the above-mentioned access control method.

[0079] In some embodiments, refer to Figure 4 , this figure is a schematic structural diagram of a computer terminal device for implementing an access control method according to some embodiments of the present application. The access control method in the above embodiments can be implemented by Figure 4 the computer terminal device shown. The computer terminal device 300 includes at least one communication bus 301, a communication interface 302, a processor 303, and a memory 304.

[0080] The processor 303 can be a general-purpose central processing unit (CPU), or an application-specific integrated circuit (ASIC), or one or more for controlling the execution of an access control method in the present application.

[0081] The communication bus 301 may include a path for transmitting information between the above components.

[0082] The memory 304 can be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (RAM) or other types of dynamic storage devices that can store information and instructions, or can also be an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM), or other optical disc storage, optical disc storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), a magnetic disk, or other magnetic storage devices, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory 304 can exist independently and be connected to the processor 303 through the communication bus 301. The memory 304 can also be integrated with the processor 303.

[0083] Among them, the memory 304 is used to store the program code for executing the solution of this application and is controlled by the processor 303 for execution. The processor 303 is used to execute the program code stored in the memory 304. The program code can include one or more software modules. In the above embodiment, the determination of the access control adjustment index can be implemented by one or more software modules in the program code of the processor 303 and the memory 304.

[0084] The communication interface 302 uses any device such as a transceiver to communicate with other devices or communication networks, such as Ethernet, a radio access network (RAN), a wireless local area network (WLAN), etc.

[0085] Optionally, the above computer terminal device 300 can further include a power supply 305 for supplying power to various components or circuits in the real-time computer terminal device.

[0086] In a specific implementation, as an embodiment, the computer terminal device can include multiple processors, and each of these processors can be a single-core (single-CPU) processor or a multi-core (multi-CPU) processor. Here, the processor can refer to one or more devices, circuits, and / or processing cores for processing data (such as computer program instructions).

[0087] The above computer terminal device can be a general computer terminal device or a dedicated computer terminal device. In specific implementations, the computer terminal device can be a desktop computer, a laptop computer, a network server, a personal digital assistant (PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device, or an embedded device. The embodiments of the present application do not limit the type of the computer terminal device.

[0088] In addition, in other aspects of the present application, there is provided a computer-readable storage medium storing at least one computer program, and the computer program is loaded and executed by a processor to implement the operations performed by the above-described access control method.

[0089] In summary, in an intelligent laboratory management system and an access control method based on the Internet of Things disclosed in the embodiments of the present application, by performing information repositioning on the access verification information corresponding to each access verification object in the access verification information set, a plurality of access verification information positioning regions are obtained, and region error node positioning is performed according to the access verification information of the error positioning objects in different access verification information positioning regions to obtain sensing error positioning nodes corresponding to different access verification information positioning regions respectively; for any one access verification information positioning region, association depth verification is performed on the access verification information corresponding to each access verification object in this access verification information positioning region and the sensing error positioning node of this region to obtain the association depth corresponding to each access verification object and the sensing error positioning node of this region respectively; the characteristic distance between the access verification information corresponding to each access verification object and the sensing error positioning node of this region is determined; access control is performed according to the characteristic distance and the association depth between the access verification information corresponding to each access verification object and the sensing error positioning node of this region, so that error node positioning can be performed according to the access verification information of the error positioning object, and access control can be performed according to the sensing error positioning node, reducing the access misjudgment rate caused by sensor errors.

[0090] The above are only the embodiments of the present application, and specific technical solutions or common knowledge such as well-known features are not described in detail herein. It should be noted that for those skilled in the art, without departing from the technical solutions of the present application, several deformations and improvements can still be made, and these should also be regarded as the protection scope of the present application, and these will not affect the implementation effect of the present application and the practicality of the patent.

[0091] The protection scope claimed in this application shall be subject to the content of its claims. The specific implementation manners and other records in the specification can be used to interpret the content of the claims. Obviously, those skilled in the art can make various changes and modifications to this application without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalent technologies, this application also intends to include these changes and modifications.

Claims

1. A door access control method, characterized in that: include: Obtaining a set of access control verification information, relocating the access control verification information corresponding to each access control verification object in the access control verification information set, obtaining multiple access control verification information positioning areas, obtaining access control information comparison results, and extracting error positioning objects and access control verification objects in different access control verification information positioning areas based on the access control information comparison results; Perform regional error node positioning according to the access control verification information of the error positioning object in different access control verification information positioning areas, and obtain the sensor error positioning nodes corresponding to the different access control verification information positioning areas; For any access control verification information positioning area, the access control verification information corresponding to each access control verification object in the access control verification information positioning area is respectively associated with the sensor error positioning node of the area to obtain the association depth corresponding to each access control verification object and the sensor error positioning node of the area; Determine the characteristic distances between the access control verification information corresponding to each access control verification object and the sensor error positioning node of the area; perform access control according to the characteristic distances and correlation depths between the access control verification information corresponding to each access control verification object and the sensor error positioning node of the area; Among them, regional error node positioning is performed according to the access control verification information of the error positioning object in different access control verification information positioning areas, and the sensor error positioning nodes corresponding to different access control verification information positioning areas are obtained, which specifically include: For any access control verification information positioning area, obtain the deviation characteristics between the access control verification information of each error positioning object in the access control verification information positioning area and the corresponding access control verification information in the user storage information, and determine the dynamic error positioning node according to the deviation characteristics; Determine a static error location node according to the mean characteristics of the access control verification information of each error location object; perform node location according to the dynamic error location node and the static error location node to obtain a sensor error location node corresponding to the location area of ​​the access control verification information; Among them, the mean feature of each deviation feature is extracted as the dynamic error location node, the mean feature of the access control verification information of each error location object is extracted as the static error location node, and the mean feature of the dynamic error location node and the mean feature of the static error location node are summed as the sensor error location node of the area; Among them, relocating the access control verification information corresponding to each access control verification object in the access control verification information set to obtain multiple access control verification information positioning areas specifically includes: determining the access control adjustment index based on the minimum cosine similarity between the access control verification information of each access control verification object in the access control verification information set and the standard access control verification information corresponding to each access control user; relocating the access control verification information corresponding to each access control user in the access control verification information set based on the access control adjustment index to obtain multiple access control verification information positioning areas; Wherein, based on the access control adjustment index, the access control verification information corresponding to each access control user in the access control verification information set is relocated, and the multiple access control verification information location areas are obtained, specifically including: Obtaining access control verification information corresponding to each access control verification object in the access control verification information set, and forming a multi-dimensional space of access control verification information; The access control adjustment index is obtained, and information clustering is performed on the access control verification information multi-dimensional space based on the access control adjustment index to obtain multiple access control verification information positioning areas.

2. The method according to claim 1, characterized in that Acquiring the access control verification information set specifically includes: collecting access control information of each access control verification object through an Internet of Things terminal device to obtain the access control verification information set.

3. The method according to claim 1, characterized in that Obtaining the access control information comparison result specifically includes: obtaining user storage information in the Internet of Things terminal device, performing access control information comparison on the access control verification information set according to the user storage information, and obtaining the access control information comparison result.

4. The method according to claim 2, characterized in that The Internet of Things terminal device is equipped with an information storage unit, which is used to store real-time access control verification information and pre-stored user storage information.

5. An intelligent laboratory management system based on the Internet of Things, comprising an access control unit, wherein the access control unit is used to execute the access control method according to any one of claims 1 to 4, characterized in that: The access control unit comprises: An information processing module is used to obtain a set of access control verification information, relocate the access control verification information corresponding to each access control verification object in the access control verification information set, obtain multiple access control verification information positioning areas, obtain access control information comparison results, and extract error positioning objects and access control verification objects in different access control verification information positioning areas based on the access control information comparison results; The access control module is used to perform regional error node positioning according to the access verification information of the error positioning object in different access verification information positioning areas, and obtain the sensor error positioning nodes corresponding to the different access verification information positioning areas; The access control module is further used to obtain access verification information corresponding to each access verification object in the access verification information of the access verification object; perform association depth verification with the sensor error positioning node of the area according to the access verification information corresponding to each access verification object, and obtain the association depth corresponding to each access verification object and the sensor error positioning node of the area; The access control module is also used to determine the characteristic distances between the access verification information corresponding to each access verification object and the sensor error positioning node in the area; and perform access control based on the characteristic distances and association depths between the access verification information corresponding to each access verification object and the sensor error positioning node in the area.

6. A computer terminal device, characterized in that: The computer terminal device includes a memory and a processor, the memory stores codes, and the processor is configured to obtain the codes and execute a door access control method as claimed in any one of claims 1 to 4.

7. A computer-readable storage medium storing at least one computer program, characterized in that: The computer program is loaded and executed by a processor to implement the operations performed by the access control method according to any one of claims 1 to 4.

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