CN117495227A - Intelligent laboratory security management strategy determination method and device based on Internet of things - Google Patents
Intelligent laboratory security management strategy determination method and device based on Internet of things Download PDFInfo
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Abstract
The embodiment of the application provides an intelligent laboratory security management strategy determining method and device based on the Internet of things, and relates to the field of the Internet of things, wherein the method comprises the following steps: receiving a hazardous chemical substance reagent sensing signal sent by an electronic tag reader arranged at a laboratory set position, wherein the hazardous chemical substance reagent is bound with a unique coded electronic tag, and the hazardous chemical substance reagent sensing signal is generated when the electronic tag reader senses the unique coded electronic tag; determining a corresponding hazardous chemical substance reagent management strategy according to the hazardous chemical substance reagent position information in the hazardous chemical substance reagent sensing signals and a set inventory management model; the method and the device can accurately and automatically manage laboratory hazardous chemicals.
Description
Technical Field
The application relates to the field of Internet of things, in particular to an intelligent laboratory security management strategy determining method and device based on the Internet of things.
Background
In reagent inventory management systems commonly used in the prior art, management of dangerous chemicals, particularly management and control of dangerous chemicals, is not automated enough and intelligent. Scientists need to manually input dangerous chemicals in a management system in the field, such as picking up, warehouse transferring, warehouse returning and scrapping, or else the situation that the data in the system is inconsistent with the actual situation occurs. The manual operation not only wastes a lot of time for scientists, but also often causes that the system stock data is inconsistent with the actual stock due to the error of manual operation, and the data of the management system deviates more and more from the actual situation over time, so that the original purpose of managing dangerous chemicals and reducing the use risk of the dangerous chemicals is not guaranteed.
Disclosure of Invention
Aiming at the problems in the prior art, the application provides an intelligent laboratory security management strategy determining method and device based on the Internet of things, which can accurately and automatically manage laboratory hazardous chemicals.
In order to solve at least one of the above problems, the present application provides the following technical solutions:
in a first aspect, the present application provides a method for determining an intelligent laboratory security management policy based on the internet of things, including:
receiving a hazardous chemical substance reagent sensing signal sent by an electronic tag reader arranged at a laboratory set position, wherein the hazardous chemical substance reagent is bound with a unique coded electronic tag, and the hazardous chemical substance reagent sensing signal is generated when the electronic tag reader senses the unique coded electronic tag;
and determining a corresponding hazardous chemical substance reagent management strategy according to the hazardous chemical substance reagent position information in the hazardous chemical substance reagent sensing signals and a set inventory management model.
Further, before determining the corresponding hazardous chemical reagent management strategy according to the hazardous chemical reagent position information in the hazardous chemical reagent sensing signal and the set inventory management model, the method comprises the following steps:
setting historical use data and corresponding position information of the hazardous chemical substance reagent as a model training set so as to perform model training on a preset artificial intelligent model;
And carrying out iterative optimization on the artificial intelligent model trained by the model according to the use mode of the dangerous chemical reagent to obtain an inventory management model, wherein the use mode of the dangerous chemical reagent comprises the storage position of the dangerous chemical reagent when the dangerous chemical reagent changes with seasons.
Further, the determining a corresponding hazardous chemical reagent management strategy according to the hazardous chemical reagent position information in the hazardous chemical reagent sensing signal and the set inventory management model includes:
determining seasonal change of the storage validity period of the corresponding hazardous chemical substance according to the hazardous chemical substance reagent position information in the hazardous chemical substance reagent sensing signals;
determining the corresponding dangerous chemical reagent prediction validity period according to seasonal change of the dangerous chemical storage validity period and setting an inventory management model, and generating a corresponding expiration reminding signal according to the dangerous chemical reagent prediction validity period and the current system time.
Further, the determining the corresponding hazardous chemical reagent management strategy according to the hazardous chemical reagent position information in the hazardous chemical reagent sensing signal and the set inventory management model further includes:
receiving a hazardous chemical substance reagent weight signal sent by a weight sensor arranged at a laboratory set position, and determining corresponding reagent loss according to the hazardous chemical substance reagent weight signal; wherein the hazardous chemical reagent weight signal is generated when the weight sensor monitors the hazardous chemical reagent weight;
And determining the predicted depletion time of the hazardous chemical reagent according to the reagent loss, the hazardous chemical reagent position information and the set inventory management model, and generating a corresponding hazardous chemical reagent ordering reminding signal according to the comparison relation between the predicted depletion time and the numerical value of the preset time threshold.
Further, the setting the historical usage data and the corresponding position information of the hazardous chemical substance reagent as a model training set to perform model training on a preset artificial intelligent model, and further includes:
carrying out data cleaning and missing value processing on the historical use data and the corresponding position information of the hazardous chemical substance reagent according to a preset data preprocessing rule;
and setting historical use data and corresponding position information of the hazardous chemical substance reagent subjected to the data cleaning and missing value processing as a model training set.
Further, the iterative optimization is performed on the model trained by the model according to the usage mode of the hazardous chemical substance reagent to obtain an inventory management model, which comprises the following steps:
determining corresponding position weights according to storage positions of the hazardous chemical substances when the hazardous chemical substances are seasonally changed;
and carrying out iterative optimization on the artificial intelligent model trained by the model according to the position weight to obtain an inventory management model.
In a second aspect, the present application provides an intelligent laboratory security management policy determining device based on the internet of things, including:
the sensing signal receiving module is used for receiving a hazardous chemical substance reagent sensing signal sent by an electronic tag reader arranged at a laboratory set position, wherein the hazardous chemical substance reagent is bound with a unique coded electronic tag, and the hazardous chemical substance reagent sensing signal is generated when the electronic tag reader senses the unique coded electronic tag;
and the management strategy prediction module is used for determining a corresponding hazardous chemical substance reagent management strategy according to the hazardous chemical substance reagent position information in the hazardous chemical substance reagent sensing signals and the set inventory management model.
In a third aspect, the present application provides an intelligent laboratory security management policy determining system based on the internet of things, including: the inventory management module and the electronic tag module comprise unique coded electronic tags bound on dangerous chemicals;
the inventory management module comprises an intelligent laboratory security management policy determining device based on the Internet of things, which is provided according to the second aspect of the application.
In a fourth aspect, the present application provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the steps of the intelligent laboratory security management policy determining method based on the internet of things are implemented when the processor executes the program.
In a fifth aspect, the present application provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the intelligent laboratory security management policy determination method based on the internet of things.
In a sixth aspect, the present application provides a computer program product comprising computer programs/instructions which, when executed by a processor, implement the steps of the intelligent laboratory security management policy determination method based on the internet of things.
According to the technical scheme, the application provides an intelligent laboratory security management strategy determining method, device and system based on the Internet of things, and the method, device and system are used for receiving a hazardous chemical substance reagent sensing signal sent by an electronic tag reader arranged at a laboratory set position, wherein the hazardous chemical substance reagent is bound with a unique coded electronic tag, and the hazardous chemical substance reagent sensing signal is generated when the unique coded electronic tag is sensed by the electronic tag reader; and determining a corresponding hazardous chemical reagent management strategy according to the hazardous chemical reagent position information in the hazardous chemical reagent sensing signals and the set inventory management model, so that laboratory hazardous chemical management can be accurately and automatically performed.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, and it is obvious that the drawings in the following description are some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is one of flow diagrams of an intelligent laboratory security management policy determining method based on the internet of things in an embodiment of the present application;
fig. 2 is a second flowchart of an intelligent laboratory security management policy determining method based on the internet of things in the embodiment of the present application;
fig. 3 is a third flow chart of a method for determining an intelligent laboratory security management policy based on the internet of things in the embodiment of the present application;
FIG. 4 is a fourth flow chart of a method for determining security management policies of an intelligent laboratory based on the Internet of things in an embodiment of the present application;
FIG. 5 is a fifth flow chart of a method for determining security management policies of an intelligent laboratory based on the Internet of things in an embodiment of the present application;
FIG. 6 is a flowchart of a method for determining security management policies of an intelligent laboratory based on the Internet of things in an embodiment of the present application;
Fig. 7 is a block diagram of an intelligent laboratory security management policy determining device based on the internet of things in an embodiment of the present application;
fig. 8 is a block diagram of an intelligent laboratory security management policy determining system based on the internet of things in an embodiment of the present application;
fig. 9 is a schematic structural diagram of an electronic device in an embodiment of the present application.
Detailed Description
For the purposes of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.
The data acquisition, storage, use, processing and the like in the technical scheme meet the relevant regulations of national laws and regulations.
In view of the fact that the management of hazardous chemicals, particularly the management of hazardous chemicals, is not fully automated and intelligent in reagent inventory management systems commonly used in the prior art. Scientists need to manually input in a management system in site operations such as picking up, warehouse transferring, warehouse returning and scrapping, otherwise, the situation that data in the system is inconsistent with the actual situation can occur, and the application provides an intelligent laboratory safety management strategy determining method, device and system based on the Internet of things, wherein a unique coded electronic tag is bound to a dangerous chemical reagent sensing signal sent by an electronic tag reader arranged at a laboratory set position, and the dangerous chemical reagent sensing signal is generated when the unique coded electronic tag is sensed by the electronic tag reader; and determining a corresponding hazardous chemical reagent management strategy according to the hazardous chemical reagent position information in the hazardous chemical reagent sensing signals and the set inventory management model, so that laboratory hazardous chemical management can be accurately and automatically performed.
In order to accurately and automatically manage laboratory hazardous chemicals, the application provides an embodiment of an intelligent laboratory security management policy determining method based on the internet of things, referring to fig. 1, the intelligent laboratory security management policy determining method based on the internet of things specifically includes the following contents:
step S101: receiving a hazardous chemical substance reagent sensing signal sent by an electronic tag reader arranged at a laboratory set position, wherein the hazardous chemical substance reagent is bound with a unique coded electronic tag, and the hazardous chemical substance reagent sensing signal is generated when the electronic tag reader senses the unique coded electronic tag;
alternatively, in this embodiment, a unique code may be generated in the system for each hazardous chemical reagent to be entered into the laboratory, and a label is printed by using a label printer, and is correspondingly attached to the body of each reagent bottle, where an IC card chip (i.e., an electronic label) is included in the label, and the number of the IC card chip is associated with the unique code of the reagent bottle.
Optionally, the laboratory setting locations include, but are not limited to: door edge of each laboratory, reagent cabinet and laboratory bench.
It can be understood that when a certain electronic tag approaches or moves out of the sensor for a certain distance, the sensor can sense the change, and collect and send the serial number of the IC card, the change information and the serial number of the sensor corresponding to the tag.
For example, when a reagent is placed in a reagent cabinet, the system automatically records that the bottle of reagent has been put in storage and automatically marks the storage location; when the reagent is taken out of the reagent cabinet, the system automatically records the state of the reagent as in use, and the storage position is moved out of the reagent cabinet; when a reagent is placed on the experiment table, the system automatically records the current position of the reagent on the experiment table; when a reagent moves out of a laboratory room, the system automatically records that the reagent has moved out of the room; when the reagent moves to the discard area, the system automatically records that the reagent has been used up and discarded.
Step S102: and determining a corresponding hazardous chemical substance reagent management strategy according to the hazardous chemical substance reagent position information in the hazardous chemical substance reagent sensing signals and a set inventory management model.
Alternatively, the present embodiment may take into account the effect of storage locations on the reagent, some of which may result in a faster expiration of the reagent, as environmental conditions may affect the stability of the reagent, using storage locations as an additional feature to more accurately predict the expiration date of the reagent. The present application can thus use historical data to train preset artificial intelligence models (e.g., linear regression models, decision trees, and random forest models, and time series models) and adjust according to the performance of the models. And (3) adjusting the super parameters of the model to ensure that the seasonal and position-related changes of the reagent validity period can be captured better, and finally outputting the corresponding dangerous chemical reagent prediction validity period by the model.
It follows that this embodiment can more effectively predict, monitor and optimize hazardous chemicals and reagent inventory in the laboratory and determine corresponding hazardous chemical reagent management strategies through the application of artificial intelligence models.
As can be seen from the above description, according to the intelligent laboratory security management policy determining method based on the internet of things provided by the embodiment of the application, a hazardous chemical reagent sensing signal sent by an electronic tag reader arranged at a laboratory set position can be received, wherein the hazardous chemical reagent is bound with a unique coded electronic tag, and the hazardous chemical reagent sensing signal is generated when the electronic tag reader senses the unique coded electronic tag; and determining a corresponding hazardous chemical reagent management strategy according to the hazardous chemical reagent position information in the hazardous chemical reagent sensing signals and the set inventory management model, so that laboratory hazardous chemical management can be accurately and automatically performed.
In order to accurately determine the hazardous chemical substance reagent management policy, in an embodiment of the method for determining the security management policy of the intelligent laboratory based on the internet of things, referring to fig. 2, the method may further specifically include the following:
Step S201: setting historical use data and corresponding position information of the hazardous chemical substance reagent as a model training set so as to perform model training on a preset artificial intelligent model;
step S202: and carrying out iterative optimization on the artificial intelligent model trained by the model according to the use mode of the dangerous chemical reagent to obtain an inventory management model, wherein the use mode of the dangerous chemical reagent comprises the storage position of the dangerous chemical reagent when the dangerous chemical reagent changes with seasons.
Alternatively, in this embodiment, historical usage data for laboratory hazardous chemicals and reagents may be collected, including historical usage data and corresponding location information, as well as frequency of use, depletion time, order records, and the like. These data will be used to train the inventory management model.
Alternatively, in this embodiment, the selected inventory management model may be trained using historical data. This may include predicting usage patterns of the reagent, depletion time, seasonal changes, etc. Model parameters are adjusted to improve their performance.
In view of the fact that the mode of use of the hazardous chemical reagent may include seasonal changes and storage locations, the mode of use of the hazardous chemical reagent may include storage locations where the hazardous chemical reagent is seasonally changed.
In order to accurately predict the expiration date of the hazardous chemical reagent according to the artificial intelligence, in an embodiment of the method for determining the security management policy of the intelligent laboratory based on the internet of things of the present application, referring to fig. 3, the method may further specifically include the following:
step S301: determining seasonal change of the storage validity period of the corresponding hazardous chemical substance according to the hazardous chemical substance reagent position information in the hazardous chemical substance reagent sensing signals;
step S302: determining the corresponding dangerous chemical reagent prediction validity period according to seasonal change of the dangerous chemical storage validity period and setting an inventory management model, and generating a corresponding expiration reminding signal according to the dangerous chemical reagent prediction validity period and the current system time.
Alternatively, in this embodiment, a time series of seasonal analysis may be introduced into the model to capture periodic changes each year, month, or week, taking into account that seasonal changes may affect the pattern of use of the agent. This may be achieved by adding time-dependent features or using time-series models, such as seasonal decomposition or periodic exponential smoothing.
Meanwhile, considering the influence of the reagent storage location on the usage pattern, the storage location may affect the ease of use, visibility, and accessibility of the reagent. The storage location information may be used in this embodiment as an additional feature of the model to more accurately predict reagent usage and inventory requirements. Spatial data analysis methods may be used or the storage locations may be converted into features that are understandable to the model.
In particular, the present embodiment may use a time series analysis method to capture seasonal variations in reagent usage patterns. This may include techniques such as seasonal decomposition, periodic exponential smoothing, etc. to identify and extract seasonal trends. Meanwhile, the present embodiment may consider the influence of the storage position on the reagent. Certain storage locations may result in a faster expiration of the reagent because environmental conditions may affect the stability of the reagent. The storage location is used as an additional feature to more accurately predict the expiration date of the reagent. Whereby the model is trained using the historical data and adjusted according to the performance of the model. And (3) adjusting the super parameters of the model to ensure that the seasonal and position-related changes of the reagent validity period can be captured better, and finally outputting the corresponding dangerous chemical reagent prediction validity period by the model.
In order to accurately predict the exhaustion time of the hazardous chemical reagent, in an embodiment of the method for determining the intelligent laboratory security management policy based on the internet of things of the present application, referring to fig. 4, the method may further specifically include the following:
step S401: receiving a hazardous chemical substance reagent weight signal sent by a weight sensor arranged at a laboratory set position, and determining corresponding reagent loss according to the hazardous chemical substance reagent weight signal; wherein the hazardous chemical reagent weight signal is generated when the weight sensor monitors the hazardous chemical reagent weight;
Step S402: and determining the predicted depletion time of the hazardous chemical reagent according to the reagent loss, the hazardous chemical reagent position information and the set inventory management model, and generating a corresponding hazardous chemical reagent ordering reminding signal according to the comparison relation between the predicted depletion time and the numerical value of the preset time threshold.
Alternatively, in this embodiment, the effect of the weight change of the reagent on the reagent usage and depletion time is considered. If the weight change of the reagent is related to its amount used, the reagent weight can be added to the model as a key feature. Wherein the hazardous chemical reagent weight signal is generated when a weight sensor provided at a laboratory setting location monitors the hazardous chemical reagent weight.
Thus, seasonal variation, storage location information, and reagent weight variation can be simultaneously considered in the present embodiment to more accurately predict the depletion time of the hazardous chemical reagent, thereby more effectively performing inventory management.
In order to obtain an accurate prediction model, in an embodiment of the method for determining the intelligent laboratory security management policy based on the internet of things in the present application, referring to fig. 5, the method may further specifically include the following:
Step S501: carrying out data cleaning and missing value processing on the historical use data and the corresponding position information of the hazardous chemical substance reagent according to a preset data preprocessing rule;
step S502: and setting historical use data and corresponding position information of the hazardous chemical substance reagent subjected to the data cleaning and missing value processing as a model training set.
Optionally, in this embodiment, the data cleaning includes:
1. outlier processing: abnormal values in the data are checked by statistical analysis and visualization means. For variables relating to numerical values such as the amount of reagent used and the amount of stock, abnormal values may be identified using a tool such as a box chart, and whether to delete, correct or replace these abnormal values may be determined according to the business context.
2. And (5) de-duplication: the reagent data is checked to ensure the uniqueness of each reagent. If there are duplicate records of the same reagent, it is possible to ensure that there is only one record per reagent by deleting duplicate records or combining records.
3. Processing redundant variables: it is checked whether there are a plurality of variables in the data that provide the same information. For example, if the reagent name and reagent number both provide the same information, one may be selected to be retained and the other deleted to reduce redundancy.
4. Handling error data types: ensuring that the data type is consistent with expectations. For example, whether the date field is correctly interpreted as a date type, whether the number field is a numeric type, and the like.
Optionally, in this embodiment, the missing value processing includes:
1. identifying a missing value: using descriptive statistics or visualization tools, missing values in the data are identified. Knowing the distribution and pattern of missing values helps to take the appropriate filling strategy.
2. Filling the missing value: for a limited number of missing values, it is contemplated to use a mean, median or mode for filling. For category type variables, a mode may be used. For time series data, padding using values of adjacent time points may be considered.
3. Deletion of missing values: if the missing values are few and the impact on the overall model is limited, the samples containing the missing values may be selected for deletion.
In order to obtain an accurate prediction model, in an embodiment of the method for determining the intelligent laboratory security management policy based on the internet of things in the present application, referring to fig. 6, the method may further specifically include the following:
step S601: determining corresponding position weights according to storage positions of the hazardous chemical substances when the hazardous chemical substances are seasonally changed;
Step S602: and carrying out iterative optimization on the artificial intelligent model trained by the model according to the position weight to obtain an inventory management model.
Alternatively, in this embodiment, correlation analysis may be used to quantify the relationship between the storage locations and the reagent usage patterns to determine the corresponding location weights. A correlation coefficient between the storage location and the amount of reagent used is calculated to identify whether a significant correlation exists. Positive correlation indicates that the storage location may affect the pattern of use of the reagent, while negative correlation indicates that the opposite may be true.
Seasonal trend analysis may also be performed on reagent usage patterns at different storage locations. For example using a time series decomposition method such as STL (Seasonal and Trend decomposition using Loess) or periodic exponential smoothing to identify seasonal variations at each storage location, thereby determining the corresponding location weights.
In order to accurately and automatically perform laboratory hazardous chemical management, the application provides an embodiment of an intelligent laboratory security management policy determining device based on the internet of things, which is used for implementing all or part of the content of the intelligent laboratory security management policy determining method based on the internet of things, referring to fig. 7, the intelligent laboratory security management policy determining device based on the internet of things specifically includes the following contents:
The sensing signal receiving module 10 is configured to receive a hazardous chemical substance reagent sensing signal sent by an electronic tag reader disposed at a laboratory set position, where the hazardous chemical substance reagent is bound with a unique coded electronic tag, and the hazardous chemical substance reagent sensing signal is generated when the electronic tag reader senses the unique coded electronic tag;
the management policy prediction module 20 is configured to determine a corresponding hazardous chemical substance reagent management policy according to the hazardous chemical substance reagent location information in the hazardous chemical substance reagent sensing signal and the set inventory management model.
As can be seen from the above description, the intelligent laboratory security management policy determining device based on the internet of things provided by the embodiments of the present application is capable of receiving a hazardous chemical reagent sensing signal sent by an electronic tag reader disposed at a laboratory set position, where the hazardous chemical reagent is bound with a unique coded electronic tag, and the hazardous chemical reagent sensing signal is generated when the electronic tag reader senses the unique coded electronic tag; and determining a corresponding hazardous chemical reagent management strategy according to the hazardous chemical reagent position information in the hazardous chemical reagent sensing signals and the set inventory management model, so that laboratory hazardous chemical management can be accurately and automatically performed.
In order to further explain the scheme, the application further provides a specific application example of the intelligent laboratory security management policy determining device based on the internet of things for implementing the intelligent laboratory security management policy determining system based on the internet of things, referring to fig. 8, specifically including: the inventory management module and the electronic tag module comprise unique coded electronic tags bound on dangerous chemicals;
the inventory management module includes:
the sensing signal receiving module is used for receiving a hazardous chemical substance reagent sensing signal sent by an electronic tag reader arranged at a laboratory set position, wherein the hazardous chemical substance reagent sensing signal is generated when the electronic tag reader senses the unique coded electronic tag;
and the management strategy prediction module is used for determining a corresponding hazardous chemical substance reagent management strategy according to the hazardous chemical substance reagent position information in the hazardous chemical substance reagent sensing signals and the set inventory management model.
As can be seen from the above description, the intelligent laboratory security management policy determining system based on the internet of things provided by the embodiments of the present application is capable of receiving a hazardous chemical reagent sensing signal sent by an electronic tag reader disposed at a laboratory set position, where the hazardous chemical reagent is bound with a unique coded electronic tag, and the hazardous chemical reagent sensing signal is generated when the electronic tag reader senses the unique coded electronic tag; and determining a corresponding hazardous chemical reagent management strategy according to the hazardous chemical reagent position information in the hazardous chemical reagent sensing signals and the set inventory management model, so that laboratory hazardous chemical management can be accurately and automatically performed.
In order to accurately and automatically perform laboratory hazardous chemical substance management from a hardware level, the application provides an embodiment of an electronic device for implementing all or part of contents in the intelligent laboratory security management policy determination method based on the internet of things, wherein the electronic device specifically comprises the following contents:
a processor (processor), a memory (memory), a communication interface (Communications Interface), and a bus; the processor, the memory and the communication interface complete communication with each other through the bus; the communication interface is used for realizing information transmission between the intelligent laboratory security management policy determining device based on the Internet of things and related equipment such as a core service system, a user terminal and a related database; the logic controller may be a desktop computer, a tablet computer, a mobile terminal, etc., and the embodiment is not limited thereto. In this embodiment, the logic controller may refer to an embodiment of the method for determining an intelligent laboratory security management policy based on the internet of things and an embodiment of the device for determining an intelligent laboratory security management policy based on the internet of things, and the contents thereof are incorporated herein and are not repeated here.
It is understood that the user terminal may include a smart phone, a tablet electronic device, a network set top box, a portable computer, a desktop computer, a Personal Digital Assistant (PDA), a vehicle-mounted device, a smart wearable device, etc. Wherein, intelligent wearing equipment can include intelligent glasses, intelligent wrist-watch, intelligent bracelet etc..
In practical application, part of the intelligent laboratory security management policy determining method based on the internet of things can be executed on the electronic equipment side as described above, or all operations can be completed in the client equipment. Specifically, the selection may be made according to the processing capability of the client device, and restrictions of the use scenario of the user. The present application is not limited in this regard. If all operations are performed in the client device, the client device may further include a processor.
The client device may have a communication module (i.e. a communication unit) and may be connected to a remote server in a communication manner, so as to implement data transmission with the server. The server may include a server on the side of the task scheduling center, and in other implementations may include a server of an intermediate platform, such as a server of a third party server platform having a communication link with the task scheduling center server. The server may include a single computer device, a server cluster formed by a plurality of servers, or a server structure of a distributed device.
Fig. 9 is a schematic block diagram of a system configuration of an electronic device 9600 of an embodiment of the present application. As shown in fig. 9, the electronic device 9600 may include a central processor 9100 and a memory 9140; the memory 9140 is coupled to the central processor 9100. Notably, this fig. 9 is exemplary; other types of structures may also be used in addition to or in place of the structures to implement telecommunications functions or other functions.
In an embodiment, the intelligent laboratory security management policy determination method functions based on the internet of things may be integrated into the central processor 9100. The central processor 9100 may be configured to perform the following control:
step S101: receiving a hazardous chemical substance reagent sensing signal sent by an electronic tag reader arranged at a laboratory set position, wherein the hazardous chemical substance reagent is bound with a unique coded electronic tag, and the hazardous chemical substance reagent sensing signal is generated when the electronic tag reader senses the unique coded electronic tag;
step S102: and determining a corresponding hazardous chemical substance reagent management strategy according to the hazardous chemical substance reagent position information in the hazardous chemical substance reagent sensing signals and a set inventory management model.
As can be seen from the above description, the electronic device provided by the embodiment of the present application receives a hazardous chemical substance reagent sensing signal sent by an electronic tag reader disposed at a laboratory setting position, where the hazardous chemical substance reagent is bound with a unique coded electronic tag, and the hazardous chemical substance reagent sensing signal is generated when the electronic tag reader senses the unique coded electronic tag; and determining a corresponding hazardous chemical reagent management strategy according to the hazardous chemical reagent position information in the hazardous chemical reagent sensing signals and the set inventory management model, so that laboratory hazardous chemical management can be accurately and automatically performed.
In another embodiment, the intelligent laboratory security management policy determining device based on the internet of things may be configured separately from the central processor 9100, for example, the intelligent laboratory security management policy determining device based on the internet of things may be configured as a chip connected to the central processor 9100, and the intelligent laboratory security management policy determining method function based on the internet of things is implemented by control of the central processor.
As shown in fig. 9, the electronic device 9600 may further include: a communication module 9110, an input unit 9120, an audio processor 9130, a display 9160, and a power supply 9170. It is noted that the electronic device 9600 need not include all of the components shown in fig. 9; in addition, the electronic device 9600 may further include components not shown in fig. 9, and reference may be made to the related art.
As shown in fig. 9, the central processor 9100, sometimes referred to as a controller or operational control, may include a microprocessor or other processor device and/or logic device, which central processor 9100 receives inputs and controls the operation of the various components of the electronic device 9600.
The memory 9140 may be, for example, one or more of a buffer, a flash memory, a hard drive, a removable media, a volatile memory, a non-volatile memory, or other suitable device. The information about failure may be stored, and a program for executing the information may be stored. And the central processor 9100 can execute the program stored in the memory 9140 to realize information storage or processing, and the like.
The input unit 9120 provides input to the central processor 9100. The input unit 9120 is, for example, a key or a touch input device. The power supply 9170 is used to provide power to the electronic device 9600. The display 9160 is used for displaying display objects such as images and characters. The display may be, for example, but not limited to, an LCD display.
The memory 9140 may be a solid state memory such as Read Only Memory (ROM), random Access Memory (RAM), SIM card, etc. But also a memory which holds information even when powered down, can be selectively erased and provided with further data, an example of which is sometimes referred to as EPROM or the like. The memory 9140 may also be some other type of device. The memory 9140 includes a buffer memory 9141 (sometimes referred to as a buffer). The memory 9140 may include an application/function storage portion 9142, the application/function storage portion 9142 storing application programs and function programs or a flow for executing operations of the electronic device 9600 by the central processor 9100.
The memory 9140 may also include a data store 9143, the data store 9143 for storing data, such as contacts, digital data, pictures, sounds, and/or any other data used by an electronic device. The driver storage portion 9144 of the memory 9140 may include various drivers of the electronic device for communication functions and/or for performing other functions of the electronic device (e.g., messaging applications, address book applications, etc.).
The communication module 9110 is a transmitter/receiver 9110 that transmits and receives signals via an antenna 9111. A communication module (transmitter/receiver) 9110 is coupled to the central processor 9100 to provide input signals and receive output signals, as in the case of conventional mobile communication terminals.
Based on different communication technologies, a plurality of communication modules 9110, such as a cellular network module, a bluetooth module, and/or a wireless local area network module, etc., may be provided in the same electronic device. The communication module (transmitter/receiver) 9110 is also coupled to a speaker 9131 and a microphone 9132 via an audio processor 9130 to provide audio output via the speaker 9131 and to receive audio input from the microphone 9132 to implement usual telecommunications functions. The audio processor 9130 can include any suitable buffers, decoders, amplifiers and so forth. In addition, the audio processor 9130 is also coupled to the central processor 9100 so that sound can be recorded locally through the microphone 9132 and sound stored locally can be played through the speaker 9131.
The embodiments of the present application further provide a computer readable storage medium capable of implementing all the steps in the intelligent laboratory security management policy determination method based on the internet of things in which the execution subject in the above embodiments is a server or a client, and the computer readable storage medium stores a computer program thereon, where the computer program when executed by a processor implements all the steps in the intelligent laboratory security management policy determination method based on the internet of things in which the execution subject in the above embodiments is a server or a client, for example, the processor implements the following steps when executing the computer program:
Step S101: receiving a hazardous chemical substance reagent sensing signal sent by an electronic tag reader arranged at a laboratory set position, wherein the hazardous chemical substance reagent is bound with a unique coded electronic tag, and the hazardous chemical substance reagent sensing signal is generated when the electronic tag reader senses the unique coded electronic tag;
step S102: and determining a corresponding hazardous chemical substance reagent management strategy according to the hazardous chemical substance reagent position information in the hazardous chemical substance reagent sensing signals and a set inventory management model.
As can be seen from the above description, the computer readable storage medium provided in the embodiments of the present application receives a hazardous chemical substance reagent sensing signal sent by an electronic tag reader disposed at a laboratory setting location, where the hazardous chemical substance reagent is bound with a unique coded electronic tag, and the hazardous chemical substance reagent sensing signal is generated when the electronic tag reader senses the unique coded electronic tag; and determining a corresponding hazardous chemical reagent management strategy according to the hazardous chemical reagent position information in the hazardous chemical reagent sensing signals and the set inventory management model, so that laboratory hazardous chemical management can be accurately and automatically performed.
The embodiment of the present application further provides a computer program product capable of implementing all the steps in the intelligent laboratory security management policy determination method based on the internet of things in the embodiment of the present application, where the execution subject is a server or a client, and the computer program/instructions implement the steps of the intelligent laboratory security management policy determination method based on the internet of things when executed by a processor, for example, the computer program/instructions implement the steps of:
step S101: receiving a hazardous chemical substance reagent sensing signal sent by an electronic tag reader arranged at a laboratory set position, wherein the hazardous chemical substance reagent is bound with a unique coded electronic tag, and the hazardous chemical substance reagent sensing signal is generated when the electronic tag reader senses the unique coded electronic tag;
step S102: and determining a corresponding hazardous chemical substance reagent management strategy according to the hazardous chemical substance reagent position information in the hazardous chemical substance reagent sensing signals and a set inventory management model.
As can be seen from the above description, the computer program product provided in the embodiments of the present application receives a hazardous chemical reagent sensing signal sent by an electronic tag reader disposed at a laboratory setting location, where the hazardous chemical reagent is bound to a unique coded electronic tag, and the hazardous chemical reagent sensing signal is generated when the electronic tag reader senses the unique coded electronic tag; and determining a corresponding hazardous chemical reagent management strategy according to the hazardous chemical reagent position information in the hazardous chemical reagent sensing signals and the set inventory management model, so that laboratory hazardous chemical management can be accurately and automatically performed.
It will be apparent to those skilled in the art that embodiments of the present invention may be provided as a method, apparatus, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (devices), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The principles and embodiments of the present invention have been described in detail with reference to specific examples, which are provided to facilitate understanding of the method and core ideas of the present invention; meanwhile, as those skilled in the art will have variations in the specific embodiments and application scope in accordance with the ideas of the present invention, the present description should not be construed as limiting the present invention in view of the above.
Claims (10)
1. An intelligent laboratory security management policy determining method based on the internet of things is characterized by comprising the following steps:
receiving a hazardous chemical substance reagent sensing signal sent by an electronic tag reader arranged at a laboratory set position, wherein the hazardous chemical substance reagent is bound with a unique coded electronic tag, and the hazardous chemical substance reagent sensing signal is generated when the electronic tag reader senses the unique coded electronic tag;
and determining a corresponding hazardous chemical substance reagent management strategy according to the hazardous chemical substance reagent position information in the hazardous chemical substance reagent sensing signals and a set inventory management model.
2. The method for determining the security management policy of the intelligent laboratory based on the internet of things according to claim 1, wherein before determining the corresponding security management policy of the security reagent according to the location information of the security reagent in the security reagent sensing signal and the set inventory management model, the method comprises:
setting historical use data and corresponding position information of the hazardous chemical substance reagent as a model training set so as to perform model training on a preset artificial intelligent model;
and carrying out iterative optimization on the artificial intelligent model trained by the model according to the use mode of the dangerous chemical reagent to obtain an inventory management model, wherein the use mode of the dangerous chemical reagent comprises the storage position of the dangerous chemical reagent when the dangerous chemical reagent changes with seasons.
3. The method for determining the security management policy of the intelligent laboratory based on the internet of things according to claim 1, wherein determining the corresponding security management policy of the security reagent according to the location information of the security reagent in the security reagent sensing signal and the set inventory management model comprises:
determining seasonal change of the storage validity period of the corresponding hazardous chemical substance according to the hazardous chemical substance reagent position information in the hazardous chemical substance reagent sensing signals;
determining the corresponding dangerous chemical reagent prediction validity period according to seasonal change of the dangerous chemical storage validity period and setting an inventory management model, and generating a corresponding expiration reminding signal according to the dangerous chemical reagent prediction validity period and the current system time.
4. The method for determining the security management policy of the intelligent laboratory based on the internet of things according to claim 1, wherein determining the corresponding security management policy of the security reagent according to the location information of the security reagent in the security reagent sensing signal and the set inventory management model further comprises:
receiving a hazardous chemical substance reagent weight signal sent by a weight sensor arranged at a laboratory set position, and determining corresponding reagent loss according to the hazardous chemical substance reagent weight signal; wherein the hazardous chemical reagent weight signal is generated when the weight sensor monitors the hazardous chemical reagent weight;
And determining the predicted depletion time of the hazardous chemical reagent according to the reagent loss, the hazardous chemical reagent position information and the set inventory management model, and generating a corresponding hazardous chemical reagent ordering reminding signal according to the comparison relation between the predicted depletion time and the numerical value of the preset time threshold.
5. The method for determining the security management policy of the intelligent laboratory based on the internet of things according to claim 2, wherein the setting the historical usage data of the hazardous chemical substance reagent and the corresponding position information as a model training set to perform model training on a preset artificial intelligent model, further comprises:
carrying out data cleaning and missing value processing on the historical use data and the corresponding position information of the hazardous chemical substance reagent according to a preset data preprocessing rule;
and setting historical use data and corresponding position information of the hazardous chemical substance reagent subjected to the data cleaning and missing value processing as a model training set.
6. The method for determining the security management policy of the intelligent laboratory based on the internet of things according to claim 2, wherein the iterative optimization of the artificial intelligent model trained by the model according to the usage pattern of the hazardous chemical substance reagent, to obtain an inventory management model, comprises:
Determining corresponding position weights according to storage positions of the hazardous chemical substances when the hazardous chemical substances change with seasons;
and carrying out iterative optimization on the artificial intelligent model trained by the model according to the position weight to obtain an inventory management model.
7. An intelligent laboratory security management policy determining device based on thing networking, characterized by comprising:
the sensing signal receiving module is used for receiving a hazardous chemical substance reagent sensing signal sent by an electronic tag reader arranged at a laboratory set position, wherein the hazardous chemical substance reagent is bound with a unique coded electronic tag, and the hazardous chemical substance reagent sensing signal is generated when the electronic tag reader senses the unique coded electronic tag;
and the management strategy prediction module is used for determining a corresponding hazardous chemical substance reagent management strategy according to the hazardous chemical substance reagent position information in the hazardous chemical substance reagent sensing signals and the set inventory management model.
8. An intelligent laboratory security management policy determining system based on the internet of things, the system comprising: the system comprises an inventory management module and an electronic tag module, wherein the electronic tag module comprises a unique coded electronic tag bound on a hazardous chemical reagent, and the inventory management module comprises the intelligent laboratory security management policy determining device based on the Internet of things according to claim 7.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the intelligent laboratory security management policy determination method based on the internet of things of any one of claims 1 to 6 when executing the program.
10. A computer readable storage medium having stored thereon a computer program, characterized in that the computer program when executed by a processor implements the steps of the intelligent laboratory security management policy determination method based on the internet of things of any one of claims 1 to 6.
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