Intelligent laboratory management system based on Internet of Things and access control method

Abstract

The invention provides an intelligent laboratory management system based on Internet of Things and an access control method, which can perform area error node positioning according to access control verification information of error positioning objects in different access control verification information positioning areas to obtain sensing error positioning nodes respectively corresponding to the different access control verification information positioning areas; performing association depth verification to obtain association depth and feature distance corresponding to each access control verification object and the sensing error positioning node of the area; according to the access control verification information corresponding to each access control verification object and the feature distance and association depth between the sensing error positioning node of the area, access control is carried out, so that error node positioning can be carried out according to the access control verification information of the error positioning object, and access control is carried out according to the sensing error positioning node. And the entrance guard misjudgment rate caused by sensor errors is reduced.

Description

Technical Field

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

[0002] The application of access control, alarm and monitoring networking technology in modern laboratories marks a further upgrade and intelligence of security precautions. With the vigorous development of the research industry and the increase in personnel flow, laboratory safety management has become more critical. The safety needs of laboratories are highly complex. 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 safety of laboratories.

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

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

[0005] In a first aspect, the present application provides a door access control method, which may be executed by a network device, or may be executed by a chip configured in the network device, and the present application does not limit this.

[0006] Specifically, the method includes: 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.

[0007] In combination with the first aspect, in certain implementations of the first aspect, obtaining 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.

[0008] In combination with the first aspect, in certain implementation methods of the first aspect, 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 based on the user storage information, and obtaining the access control information comparison result.

[0009] In combination with the first aspect, in certain implementation methods of the first aspect, information relocation 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 location areas, specifically including: 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; based on the access control adjustment index, information relocation 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 location areas.

[0010] In combination with the first aspect, in certain implementations of the first aspect, the access control verification information corresponding to each access control user in the access control verification information set is relocated based on the access control adjustment index, 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.

[0011] In combination with the first aspect, in certain implementations of the first aspect, the Internet of Things terminal device is equipped with an information storage unit, and the information storage unit is used to store real-time access control verification information and pre-stored user storage information.

[0012] In combination with the first aspect, in some implementations of the first aspect, performing regional error node positioning according to access control verification information of error positioning objects in different access control verification information positioning areas, and obtaining sensor error positioning nodes corresponding to different access control verification information positioning areas 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; A static error positioning node is determined according to the mean characteristics of the access control verification information of each error positioning object; node positioning is performed according to the dynamic error positioning node and the static error positioning node to obtain a sensor error positioning node corresponding to the access control verification information positioning area.

[0013] In a second aspect, the present application provides an intelligent laboratory management system based on the Internet of Things, which includes an access control unit, and the access control unit includes: 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.

[0014] In a third aspect, the present application provides a computer terminal device, which includes a memory and a processor, wherein the memory stores a code, and the processor is configured to obtain the code and execute the above-mentioned access control method.

[0015] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores at least one computer program, and the computer program is loaded and executed by a processor to implement the operations performed by the above-mentioned access control method.

[0016] The technical solution provided by the embodiments disclosed in this application has the following beneficial effects: In an intelligent laboratory management system and access control method based on the Internet of Things provided by the present application, first, the access control verification information corresponding to each access control verification object in the access control verification information set is relocated to obtain multiple access control verification information positioning areas, and the access control information comparison result is obtained. The error positioning objects and access control verification objects in different access control verification information positioning areas are extracted based on the access control information comparison result; the regional error node positioning is performed according to the access control verification information of the error positioning objects in different access control verification information positioning areas to 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; the characteristic distance between the access control verification information corresponding to each access control verification object and the sensor error positioning node of the area is determined; and access control is performed according to the characteristic distance and association depth between the access control verification information corresponding to each access control verification object and the sensor error positioning node of the area.

[0017] Therefore, it can be seen that the present application divides the access control verification information into multiple positioning areas through information relocation, and determines the sensor error positioning node according to the access control verification information of the error positioning object in each area. The access control verification information of the access control verification object only needs to be compared with a few sensor error positioning nodes, rather than with all historical storage information. The access control verification information of the access control verification object only needs to be matched with the closest sensor error positioning node to avoid misidentification caused by the complexity of data distribution, and the access control adjustment index is determined according to the real-time traffic conditions, so as to dynamically adjust the comparison range and update the sensor error positioning node to avoid the reduction in recognition accuracy caused by long-term non-update, and the present application determines the sensor error positioning node according to the access control verification information of the error positioning object in the area, so that the sensor error in the access control process can also be detected by the sensor error positioning node, reducing the access control misjudgment caused by sensor error, and greatly improving the accuracy and recognition efficiency of the access control process.

[0018] In summary, the present application can locate error nodes according to access control verification information of the error positioning object, and perform access control according to the sensor error positioning node, thereby reducing the access control misjudgment rate caused by sensor errors. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 is an exemplary flow chart of a door access control method according to some embodiments of the present application; Figure 2 is an exemplary flow chart for implementing access control information comparison in some embodiments of the present application; Figure 3 is a schematic diagram of the structure of an access control unit according to some embodiments of the present application; Figure 4 It is a structural diagram of a computer terminal device for implementing a door access control method according to some embodiments of the present application. DETAILED DESCRIPTION

[0020] The present application obtains multiple access control information positioning areas by relocating the access control information corresponding to each access control verification object in the access control verification information set, and performs regional error node positioning according to the access control information of the error positioning object in different access control information positioning areas to obtain the sensor error positioning nodes corresponding to the different access control information positioning areas; for any access control information positioning area, the access control information corresponding to each access control verification object in the access control information positioning area is respectively associated with the sensor error positioning node of the area for depth verification to obtain the associated depths corresponding to each access control verification object and the sensor error positioning node of the area; the characteristic distances between the access control information corresponding to each access control verification object and the sensor error positioning node of the area are determined; access control is performed according to the characteristic distances and association depths between the access control information corresponding to each access control verification object and the sensor error positioning node of the area, so that the error node can be located according to the access control information of the error positioning object, and access control is performed according to the sensor error positioning node, thereby reducing the access control misjudgment rate caused by sensor errors.

[0021] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods. Figure 1 , which is an exemplary flow chart of a door access control method according to some embodiments of the present application. The door access control method 100 mainly includes the following steps: In step S101, a set of access control verification information is obtained, and the access control verification information corresponding to each access control user in the access control verification information set is relocated to obtain multiple access control verification information positioning areas, and access control information comparison results are obtained. Based on the access control information comparison results, error positioning objects and access control verification objects in different access control verification information positioning areas are extracted.

[0022] Optionally, in some embodiments, obtaining the access control verification information set specifically includes: collecting access control information of each access control user through an Internet of Things terminal device to obtain the access control verification information set.

[0023] Optionally, in some embodiments, 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.

[0024] Optionally, in some embodiments, the IoT terminal device includes an IoT sensor. In specific implementation, the IoT terminal device includes a camera (IoT sensor), a radio frequency (RFID) card reader, a biometric sensor, a Bluetooth module, etc. This application does not go into details.

[0025] It should be noted that the access control users are the target users who need to pass the laboratory access control. By collecting access control information of each access control user, the identity of each access control user can be identified and the corresponding access control authority can be granted, thereby improving the security of laboratory access control management.

[0026] Optionally, in some embodiments, the access control verification information set includes access control verification information corresponding to each access control user. In specific implementation, the access control verification information may be a feature vector, and the feature vector is used to store information features collected by the Internet of Things terminal device. For example, when the Internet of Things terminal device collects the facial image of the access control user, the FaceNet deep learning model carried by the storage chip in the Internet of Things terminal device can be used to extract the feature vector of the facial image of the access control user, and the feature vector is used as the access control verification information of the access control user. In some other embodiments, other types of biometric identifiable features can also be collected by the Internet of Things terminal device for feature comparison, and feature vector extraction methods commonly used in other prior arts are used to extract feature vectors, and use them as the access control verification information of the access control user. This application does not limit this.

[0027] Optionally, in some embodiments, the Internet of Things terminal device is equipped with an information storage unit, and the information storage unit is used to store real-time access control verification information and pre-stored user storage information, wherein the user storage information is user identity information pre-stored in the Internet of Things terminal device, which is used to compare with the access control verification information collected in real time to determine the user identity and grant corresponding access control permissions, thereby improving the security of laboratory access control management. In specific implementation, in order to increase 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.

[0028] Optionally, in some embodiments, reference Figure 2 As shown, this figure is an exemplary flow chart for implementing access control information comparison in some embodiments of the present application. The access control information is compared with the access control verification information set according to the user storage information, and the access control information comparison result can be obtained by the following steps: In step S1011, the standard access control verification information corresponding to each access control user in the user storage information is obtained; In step S1012, access control verification information corresponding to each access control user in the access control verification information set is obtained; In step S1013, for any access control user, the cosine similarity between the access control verification information corresponding to the access control user and the standard access control verification information corresponding to each access control user is calculated. When the cosine similarity is lower than a preset threshold, it is determined that the access control user is successfully matched.

[0029] Preferably, in some embodiments, information relocation 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 location areas, specifically including: 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; information relocation is performed 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 location areas.

[0030] It should be noted that the access control adjustment index is an adjustment coefficient determined based on the verification success rate and feature similarity in the access control verification information set. The access control adjustment index is used to adjust the number of sensor error positioning nodes. The lower the access control user verification success rate in the access control verification information set and the smaller the feature similarity in the access control verification information set, the larger the corresponding access control adjustment index. This enables the sensor error positioning node to be dynamically updated based on real-time access control traffic conditions, thereby avoiding a decrease in recognition accuracy due to long-term non-updates, and increasing the security of laboratory access control.

[0031] In specific implementation, 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 / preset standard access control adjustment index, and the standard access control adjustment index is calibrated as a constant.

[0032] Optionally, in some embodiments, determining the corresponding access control adjustment index based on the access control information comparison result can also be achieved in the following way: determining the comparison success rate of the access control user based on 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. In specific implementation, the higher the comparison success rate, the smaller the mapped access control adjustment index.

[0033] Optionally, in some embodiments, when the access control adjustment index is higher than a preset threshold, the access control verification information corresponding to each access control user in the access control verification information set is relocated based on the access control adjustment index to obtain multiple access control verification information location areas.

[0034] It should be noted that when the access control adjustment index is higher than the preset threshold, it indicates that the access control user verification success rate is low and the feature similarity in the access control verification information set is small due to factors such as environmental interference or sensor detection accuracy deviation. At this time, it is necessary to relocate 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, and obtain multiple access control verification information positioning areas. Based on the access control verification information positioning areas, positioning nodes are extracted for identity authentication, thereby reducing the interference of factors such as environmental interference or sensor detection accuracy deviation, improving the recognition accuracy and efficiency of laboratory access control identification, and improving the security of access control identity identification.

[0035] Optionally, in some embodiments, when the access control adjustment index is lower than a preset threshold, whether the access control is opened is controlled based on the access control information comparison result, that is, the access control is opened when the access control information comparison result of the access control user is qualified.

[0036] Optionally, in some embodiments, the access control verification information corresponding to each access control user in the access control verification information set is relocated based on the access control adjustment index to obtain multiple access control verification information location areas, which can be achieved by using the following steps: 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.

[0037] It should be noted that the access control verification information multidimensional space is a vector space containing multiple feature vectors, and the spatial dimension of the vector space is consistent with the vector dimension of the feature vector. In some embodiments, to facilitate information clustering, the feature vector can be stored in the access control verification information multidimensional space in the form of data points. In specific implementation, the access control verification information multidimensional space contains feature vectors in the access control verification information corresponding to each access control verification object. Preferably, in some embodiments, the access control adjustment index can be mapped to the corresponding number of areas according to the threshold interval where the access control adjustment index is located. For example, when the data interval of the access control adjustment index is 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 areas, and according to the corresponding number of areas, K-means clustering is used to cluster the access control verification information in the access control verification information multidimensional space to obtain multiple access control verification information positioning areas. It should be noted that the access control verification information positioning area is a sub-area of ​​the access control verification information multidimensional space, and each access control verification information positioning area contains access control verification information corresponding to multiple access control verification objects.

[0038] It should be noted that the error positioning object is some access control users whose information is collected for locating sensor errors. In specific implementation, some access control users who have passed the comparison in the access control information comparison process can be extracted as error positioning objects. The access control verification object is some access control users whose information needs to be collected for access control according to the sensor error positioning node. In specific implementation, some access control users who have failed the comparison in the access control information comparison process can be used as access control verification objects. Due to sensor interference, there is a certain proportion of access control misjudgments in the access control verification information of the access control verification objects. The present application determines the sensor error by the information features of the access control verification information of the adjacent error positioning objects. Positioning nodes are used to identify the access control verification object. Under the condition that the sensor collection environment is the same, the interference characteristics of some environments and sensor errors can be located through the sensor error positioning node. For example, when the sensor has a detection error in a certain direction, the information characteristics of the access control verification information of the adjacent error positioning object are used to determine that the sensor error positioning node can store the part of the detection error. The identity of the access control verification object is identified according to the sensor error positioning node. The positioning node can be dynamically adjusted 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 errors, and improving the robustness of the laboratory access control identification process.

[0039] In step S102, 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 to obtain sensor error positioning nodes corresponding to different access control verification information positioning areas.

[0040] It should be noted that the sensor error positioning node is an information node containing error characteristics obtained after extracting sensor error information based on the collected information of the error positioning object. Optionally, in some embodiments, 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. The following steps can be used to implement it: 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. In specific implementation, extract the mean characteristics of each deviation characteristic as the dynamic error positioning node; The static error location node is determined according to the mean feature of the access control verification information of each error location object. In specific implementation, the mean feature of the access control verification information of each error location object can be extracted as the static error location node; Node positioning is performed according to the dynamic error positioning node and the static error positioning node to obtain the sensor error positioning node corresponding to the access control verification information positioning area. In specific implementation, the mean feature of the dynamic error positioning node and the mean feature of the static error positioning node can be used as the sensor error positioning node of the area.

[0041] In step S103, 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.

[0042] It should be noted that the association depth is the degree of similarity between the access control verification information and the sensor error positioning nodes in the area. When the interference between the environment and the Internet of Things sensors is greater, the amount of common interference information between the access control verification information and the sensor error positioning nodes in the area is greater. The present application adjusts the recognition accuracy of the identity recognition process according to the association depth, and can increase the recognition efficiency of some access control verification objects in access control recognition when interfered by the Internet of Things sensors. Optionally, in some embodiments, the access control verification information corresponding to each access control verification object is respectively verified with the sensor error positioning nodes in the area, and the association 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 the access control verification object and the characteristic elements of the sensor error positioning nodes in the area are respectively obtained, and feature sequences are respectively formed in order according to the dimensions, and the association depth corresponding to the access control verification object is determined based on the Pearson correlation coefficient between the feature sequences.

[0043] In step S104, 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 are determined; access control is performed 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.

[0044] Optionally, in some embodiments, determining 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 can be achieved by using the following steps: locating the Euclidean distances between the access control verification information corresponding to each access control verification object and the sensor error positioning node of the area in the access control verification information positioning area, and using them as 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.

[0045] Optionally, in some embodiments, access control based on the characteristic distances and association depths between access control verification information corresponding to each access control verification object and the sensor error positioning node of the area can be implemented by the following steps: determining the identification thresholds corresponding to each access control verification object according to the association depths between each access control verification object and the sensor error positioning node of the area, performing identity recognition of each access control verification object in the area based on the characteristic distances and identification thresholds between each access control verification object and the sensor error positioning node of the area, obtaining identity recognition results of each access control verification object in the area, and performing access control based on the identity recognition results. In specific implementation, the product of the association depth and a preset standard threshold can be used as the recognition threshold. When the characteristic distance between the access control verification object and the sensor error positioning node of the area and the characteristic distance between the access control verification object and the mean feature of the access control verification information of users in the area in the user storage information are lower than the identification threshold, it is determined that the identity recognition of the access control verification object has passed, and the access control opening operation is performed.

[0046] In addition, in another aspect 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, reference Figure 3 , which is a schematic diagram of the structure of an 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: The information processing module 201 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 location areas, obtain access control information comparison results, and extract error location objects and access control verification objects in different access control verification information location areas based on the access control information comparison results; The access control module 202 is used to 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; The access control module 202 is further used to obtain 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 with the sensor error positioning node of the area according to the access control verification information corresponding to each access control verification object, and obtain the association depth corresponding to each access control verification object and the sensor error positioning node of the area; The access control module 202 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 correlation depths between the access verification information corresponding to each access verification object and the sensor error positioning node in the area.

[0047] The above describes in detail an example of an IoT-based intelligent laboratory management system and access control method provided in an embodiment of the present application. It can be understood that in order to realize the above functions, the corresponding device includes a hardware structure and / or software module corresponding to executing each function.

[0048] Those skilled in the art should easily realize that, in combination with the units and algorithm steps of each example described in the embodiments disclosed in this document, 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 hardware or in a computer software-driven hardware manner depends on the specific application and design constraints of the technical solution. Therefore, professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0049] In addition, the present application also provides a computer terminal device, which includes a memory and a processor, the memory stores a code, and the processor is configured to obtain the code and execute the above-mentioned access control method.

[0050] In some embodiments, reference Figure 4 , which is a schematic diagram of the structure of a computer terminal device for implementing a door access control method according to some embodiments of the present application. The door access control method in the above embodiment can be Figure 4 The computer terminal device 300 shown in the figure is implemented, and the computer terminal device 300 includes at least one communication bus 301, a communication interface 302, a processor 303 and a memory 304.

[0051] The processor 303 may be a general-purpose central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more processors for controlling the execution of a door access control method in the present application.

[0052] The communication bus 301 may include a path for transmitting information between the above-mentioned components.

[0053] The memory 304 may 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 an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, an optical disc storage (including a compressed optical disc, a laser disc, an optical disc, a digital versatile disc, a Blu-ray disc, etc.), a magnetic disk or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of an instruction or data structure and can be accessed by a computer, but is not limited thereto. The memory 304 may exist independently and be connected to the processor 303 via the communication bus 301. The memory 304 may also be integrated with the processor 303.

[0054] The memory 304 is used to store the program code for executing the solution of the present application, and the execution is controlled by the processor 303. The processor 303 is used to execute the program code stored in the memory 304. The program code may include one or more software modules. The determination of the access control adjustment index in the above embodiment can be implemented by the processor 303 and one or more software modules in the program code in the memory 304.

[0055] The communication interface 302 uses any transceiver or other device for communicating with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area networks (WLAN), etc.

[0056] Optionally, the computer terminal device 300 may further include a power supply 305 for providing power to various devices or circuits in the real-time computer terminal device.

[0057] In a specific implementation, as an embodiment, a computer terminal device may include multiple processors, each of which may be a single-CPU processor or a multi-CPU processor. The processor here may refer to one or more devices, circuits, and / or processing cores for processing data (such as computer program instructions).

[0058] The above-mentioned computer terminal device may be a general-purpose computer terminal device or a dedicated computer terminal device. In a specific implementation, the computer terminal device may be a desktop computer, a portable 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 embodiment of the present application does not limit the type of computer terminal device.

[0059] In addition, in other aspects of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores at least one computer program, and the computer program is loaded and executed by a processor to implement the operations performed by the above-mentioned access control method.

[0060] In summary, in an intelligent laboratory management system and access control method based on the Internet of Things disclosed in an embodiment of the present application, by relocating the access control information corresponding to each access control verification object in the access control verification information set, a plurality of access control verification information positioning areas are obtained, and 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 areas, and the sensor error positioning nodes corresponding to the different access control verification information positioning areas are obtained; 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 located with the sensor error positioning nodes. The sensor error positioning nodes in the area are verified by correlation depth verification to obtain the correlation depths corresponding to each access control verification object and the sensor error positioning nodes in the area; the characteristic distances between the access control verification information corresponding to each access control verification object and the sensor error positioning nodes in the area are determined; access control is performed 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 nodes in the area, so that the error node can be located according to the access control verification information of the error positioning object, and access control is performed according to the sensor error positioning node, thereby reducing the access control misjudgment rate caused by sensor errors.

[0061] The above is only an embodiment of the present application, and the common knowledge such as the specific technical scheme or characteristics in the scheme is not described in detail here. It should be pointed out that for those skilled in the art, without departing from the technical scheme of the present application, several modifications and improvements can be made, which should also be regarded as the scope of protection of the present application, and these will not affect the effect of the implementation of the present application and the practicality of the patent.

[0062] The scope of protection claimed by this application shall be based on the content of its claims. The specific implementation methods 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 equivalents, this application is also intended to include these modifications and variations.

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.

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 1, characterized in that The access control verification information corresponding to each access control verification object in the access control verification information set is relocated to obtain multiple access control verification information location areas, 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; and 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 location areas.

5. The method according to claim 4, characterized in that 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.

6. 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.

7. The method according to claim 1, characterized in that 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 areas, and the sensor error positioning nodes corresponding to the 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; A static error positioning node is determined according to the mean characteristics of the access control verification information of each error positioning object; node positioning is performed according to the dynamic error positioning node and the static error positioning node to obtain a sensor error positioning node corresponding to the access control verification information positioning area.

8. An intelligent laboratory management system based on the Internet of Things, including an access control unit, 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.

9. 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 described in any one of claims 1 to 7.

10. 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 7.

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