CN112116515A - Community big health information processing method and system after epidemic situation - Google Patents
Community big health information processing method and system after epidemic situation Download PDFInfo
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Abstract
The invention discloses a community big health information processing method after epidemic situation, which comprises the following steps: obtaining source information of a first food; obtaining category information of the first food; inputting the source information and the category information of the first food into a training model, wherein the training model is obtained by training a plurality of sets of training data, and each set of training data in the plurality of sets comprises: source information and the category information of the first food and identification information for identifying a safety level of the first food; obtaining output information of the training model, wherein the output information comprises safety level information of the first food; according to the safety level information of the first food, acquiring corresponding early warning level information; and processing the first food according to the corresponding early warning level information. The technical effects of accurately and effectively supervising foreign food and further ensuring food safety are achieved.
Description
Technical Field
The invention relates to the technical field of community health, in particular to a community health information processing method and system after epidemic situation.
Background
The new crown epidemic situation is one of the most serious health challenges in the new century, and the epidemic situation not only has great impact on the global public health system, but also examines the degree of the construction and the perfection of the functions of the basic-level medical health institution in the public health epidemic prevention system of various governments and the strain capacity of the division and the cooperation of medical staff of the basic-level medical health institution.
However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the inventors of the present application find that the above-mentioned technology has at least the following technical problems:
when dealing with new crown epidemic situations, the community still has some defects in the monitoring method and the monitoring force of foreign foods, and the safety of the foods cannot be effectively guaranteed.
Disclosure of Invention
The embodiment of the application provides a community big health information processing method and system after epidemic situation, solves the technical problems that monitoring methods and force for foreign food are still lacked and the safety of food cannot be effectively guaranteed in the prior art, and achieves the technical effects of accurately and effectively supervising the foreign food and further guaranteeing the safety of the food.
In view of the foregoing problems, embodiments of the present application provide a method and a system for processing post-epidemic community big health information.
In a first aspect, an embodiment of the present application provides a method for processing community big health information after epidemic situations, where the method includes: obtaining source information of a first food, wherein the source information is source information of the first food entering a first community; obtaining category information of the first food, wherein the category information is category information of the first food entering the first community; inputting the source information and the category information of the first food into a training model, wherein the training model is obtained by training a plurality of sets of training data, and each set of training data in the plurality of sets comprises: source information and the category information of the first food and identification information for identifying a safety level of the first food; obtaining output information of the training model, wherein the output information comprises safety level information of the first food; according to the safety level information of the first food, acquiring corresponding early warning level information; and processing the first food according to the corresponding early warning level information.
On the other hand, this application still provides a big health information processing system of community after epidemic situation, wherein, the system includes: the first obtaining unit is used for obtaining source information of first food, and the source information is source information of the first food entering a first community; a second obtaining unit, configured to obtain category information of the first food, where the category information is category information of the first food entering the first community; a first input unit, configured to input the source information and the category information of the first food into a training model, where the training model is obtained by training multiple sets of training data, and each set of training data in the multiple sets includes: source information and the category information of the first food and identification information for identifying a safety level of the first food; a third obtaining unit, configured to obtain output information of the training model, where the output information includes safety level information of the first food; a fourth obtaining unit, configured to obtain corresponding early warning level information according to the safety level information of the first food; and the first processing unit is used for processing the first food according to the corresponding early warning level information.
In a third aspect, the present invention provides a post-epidemic community health information processing system, comprising a memory, a processor and a computer program stored on the memory and operable on the processor, wherein the processor implements the steps of the method according to any one of claims 1 to 7 when executing the program.
One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:
the method comprises the steps of inputting source information and type information of first food into a training model, judging the more accurate effect of the input information after training a plurality of groups of training data based on the training model, obtaining more accurate safety grade information of the first food, further obtaining corresponding early warning grade information, processing the first food according to the corresponding early warning grade information, and achieving the technical effects of accurately and effectively supervising the incoming food and further ensuring the food safety and community people safety.
The foregoing description is only an overview of the technical solutions of the present application, and the present application can be implemented according to the content of the description in order to make the technical means of the present application more clearly understood, and the following detailed description of the present application is given in order to make the above and other objects, features, and advantages of the present application more clearly understandable.
Drawings
Fig. 1 is a schematic flow chart of a post-epidemic community health information processing method according to an embodiment of the present application;
FIG. 2 is a schematic flow chart illustrating the method for processing community health information after epidemic situation to ensure the accuracy of a training model in the embodiment of the present application;
fig. 3 is a schematic flow chart illustrating the process of obtaining corresponding early warning level information in the post-epidemic community health information processing method in the embodiment of the present application;
fig. 4 is a schematic flowchart illustrating a process of determining whether the safety level information of the first food is within the predetermined level threshold in the post-epidemic community health information processing method according to the embodiment of the present application;
fig. 5 is a schematic flowchart illustrating a process of ensuring the security of the pass instruction in the post-epidemic community health information processing method according to the embodiment of the present application;
fig. 6 is a schematic flowchart illustrating a process of further encrypting a pass instruction in the post-epidemic community health information processing method according to the embodiment of the present application;
fig. 7 is a schematic flow chart illustrating accurate processing of the first food in the post-epidemic community health information processing method according to the embodiment of the present application;
FIG. 8 is a schematic structural diagram of a post-epidemic community big health information processing system according to an embodiment of the present application;
fig. 9 is a schematic structural diagram of an exemplary electronic device according to an embodiment of the present application.
Description of reference numerals: a first obtaining unit 11, a second obtaining unit 12, a first input unit 13, a third obtaining unit 14, a fourth obtaining unit 15, a first processing unit 16, a bus 300, a receiver 301, a processor 302, a transmitter 303, a memory 304, a bus interface 306.
Detailed Description
The embodiment of the application provides a community big health information processing method and system after epidemic situation, solves the technical problems that monitoring methods and force for foreign food are still lacked and the safety of food cannot be effectively guaranteed in the prior art, and achieves the technical effects of accurately and effectively supervising the foreign food and further guaranteeing the safety of the food. Hereinafter, example embodiments according to the present application will be described in detail with reference to the accompanying drawings. It should be apparent that the described embodiments are merely some embodiments of the present application and not all embodiments of the present application, and it should be understood that the present application is not limited to the example embodiments described herein.
Summary of the application
The new crown epidemic situation is one of the most serious health challenges in the new century, the epidemic situation not only has great impact on the global public health system, but also tests the function construction and perfection degree of the basic-level medical health institution in the public health epidemic prevention system of various governments and the labor division and cooperation strain capacity of medical staff of the basic-level medical health institution, and when the new crown epidemic situation is responded, the monitoring method and the strength of the community on foreign food are still deficient, and the safety of the food cannot be effectively ensured.
In view of the above technical problems, the technical solution provided by the present application has the following general idea:
the embodiment of the application provides a community big health information processing method after epidemic situation, which comprises the following steps: obtaining source information of a first food, wherein the source information is source information of the first food entering a first community; obtaining category information of the first food, wherein the category information is category information of the first food entering the first community; inputting the source information and the category information of the first food into a training model, wherein the training model is obtained by training a plurality of sets of training data, and each set of training data in the plurality of sets comprises: source information and the category information of the first food and identification information for identifying a safety level of the first food; obtaining output information of the training model, wherein the output information comprises safety level information of the first food; according to the safety level information of the first food, acquiring corresponding early warning level information; and processing the first food according to the corresponding early warning level information.
Having thus described the general principles of the present application, various non-limiting embodiments thereof will now be described in detail with reference to the accompanying drawings.
Example one
As shown in fig. 1, an embodiment of the present application provides a post-epidemic community big health information processing method, where the method includes:
step S100: obtaining source information of a first food, wherein the source information is source information of the first food entering a first community;
specifically, the first food is a food required by the first community, the source information of the food is the origin and route of the food, the food source information is automatically obtained, and the effect of ensuring the safety of the food is achieved by limiting the food source information.
Step S200: obtaining category information of the first food, wherein the category information is category information of the first food entering the first community;
specifically, the category refers to categories classified according to the nature or characteristics of the object itself, and the category information of the first food is specifically the category information of the first food, for example, in an emergency, if the seafood product may carry related viruses, and the food category is identified as the seafood product, the first food is prohibited from entering the cell. The effect of ensuring the safety of the food is achieved by limiting the food classification information.
Step S300: inputting the source information and the category information of the first food into a training model, wherein the training model is obtained by training a plurality of sets of training data, and each set of training data in the plurality of sets comprises: source information and the category information of the first food and identification information for identifying a safety level of the first food;
specifically, the training model is a Neural network model, i.e., a Neural network model in machine learning, and a Neural Network (NN) is a complex Neural network system formed by widely connecting a large number of simple processing units (called neurons), which reflects many basic features of human brain functions, and is a highly complex nonlinear dynamical learning system. Neural network models are described based on mathematical models of neurons. Artificial Neural Networks (Artificial Neural Networks) are a description of the first-order properties of the human brain system. Briefly, it is a mathematical model. Based on the training of a large amount of training data, the neural network model is continuously corrected by itself, and then the input data is processed more accurately.
Further, the process of training the training data is essentially a process of supervised learning, and each set of supervised data includes: the source information and the category information of the first food and identification information used for identifying a first food safety level are input into a neural network model, the neural network model outputs first food safety level information, whether the output information is consistent with the identification information used for identifying the first food safety level or not is judged, and if yes, supervised learning of the next group of data is carried out; if the output information is inconsistent with the identification information for identifying the first food safety level, the neural network model performs self-correction and adjustment until the obtained output information is consistent with the identification information for identifying the first food safety level, the group of data supervised learning is ended, and the next group of data supervised learning is performed; and when the output information of the neural network model reaches the preset accuracy rate/reaches the convergence state, finishing the supervised learning process. Through the supervised learning of the neural network model, the neural network model can process the input data more accurately, the output first food safety level is more accurate, the first food safety level is accurately judged, and the effect of ensuring the safety of food is achieved.
Step S400: obtaining output information of the training model, wherein the output information comprises safety level information of the first food;
specifically, the training model is established based on a logistic regression model, a coordinate system is established by taking the source information of the first food as an abscissa and the category information of the first food as an ordinate, a logistic regression line is obtained according to the coordinate system, one side of the logistic regression line represents a first result, and the first result is a result with a high food safety level; the other side of the logistic regression line represents a second result, which is a result that the food safety level is low. According to the difference of the food safety grade, different processing modes are adopted for the food, and the effect of ensuring the safety of the food is further realized.
Step S500: according to the safety level information of the first food, acquiring corresponding early warning level information;
specifically, after the food is subjected to primary classification of high safety level and low safety level, the safety levels are classified according to the real-time state of epidemic situations, a preset level threshold value is obtained, whether the safety level information of the first food is within the preset level threshold value is judged, early warning level information is obtained according to the relation between the safety level information and the preset threshold value, and early warning processing is carried out on the food.
Step S600: processing the first food according to the corresponding early warning level information;
specifically, different processing modes are adopted for the first food according to different early warning levels. For example: if the safety level information of the first food is below the preset level threshold value, obtaining first early warning level information, wherein the first early warning level information is used for forbidding the first food from entering the first community; if the safety level information of the first food is within the preset level threshold, second early warning level information is obtained, and the second early warning information is used for judging whether epidemic prevention information of all food residents reaches a safety index or not; if the safety level information of the first food is above the predetermined level threshold, obtaining a third communication instruction, wherein the third communication instruction is used for enabling the first food to enter the first community. Different processing modes are carried out on the food through different early warning levels, and then the effect of guaranteeing the safety of the food is achieved.
As shown in fig. 2, in order to ensure the accuracy of the training model, an embodiment S300 of the present application further includes:
step S310: judging whether the first food belongs to seafood or not according to the type information of the first food;
step S320: generating a first correction parameter when the first food is seafood;
step S330: the first correction parameter is used for correcting the output information of the training model.
Specifically, the method comprises the following steps: recent research finds that there is a high risk of a virus existing in seafood, and thus, when the first food belongs to seafood, a first correction parameter for correcting output information of the training model, correcting the output information so that safety level information of the first food is below the predetermined level threshold, and obtaining first warning level information for prohibiting the first food from entering the first community is obtained.
As shown in fig. 3, obtaining corresponding early warning level information according to the safety level information of the first food, in an embodiment S500 of the present application, further includes:
step S510: obtaining a predetermined grade threshold;
step S520: determining whether the safety level information of the first food is within the predetermined level threshold;
step S530: if the safety level information of the first food is below the preset level threshold value, obtaining first early warning level information, wherein the first early warning level information is used for forbidding the first food from entering the first community;
specifically, the predetermined grade threshold is a grade threshold obtained in real time according to real-time epidemic situation dynamics, and the grade threshold is used for ensuring the safety of the food. When the safety level information of the first food is below the preset level threshold, it is indicated that the safety level of the food is not enough, and a risk of carrying viruses may exist, and at this time, first early warning level information is obtained, and the first early warning level information is used for prohibiting the first food from entering the first community. By means of the mode that the food safety level is lower than the preset level threshold value, the food which possibly contains the hidden virus is isolated outside the community, and the technical effect of guaranteeing the food safety of the community is achieved.
As shown in fig. 4, determining whether the safety level information of the first food is within the predetermined level threshold, step S520 of the embodiment of the present application further includes:
step S521: if the safety level information of the first food is within the preset level threshold, obtaining second early warning level information, wherein the second early warning level information is used for obtaining identity information of a first resident, and the first resident is an owner of the first food;
step S522: obtaining body temperature information of the first resident;
step S523: acquiring epidemic prevention information of the first resident according to the identity information and the body temperature information of the first resident;
step S524: judging whether the epidemic prevention information of the first resident reaches a safety index;
step S525: if the epidemic prevention information of the first resident reaches the safety index, obtaining a first passing instruction, wherein the first passing instruction is used for enabling the first food to enter the first community;
step S526: and if the epidemic prevention information of the first resident does not reach the safety index, obtaining a second communication instruction, wherein the second communication instruction is used for forbidding the first food from entering the first community.
Specifically, when the safety grade information of the first food just meets the preset grade threshold, second early warning information is obtained, the second early warning information is used for obtaining the identity information of residents of all people of the first food, the first residents carry out real-time temperature measurement, the travel information of the first residents is obtained, whether the residents have the history of coming in and going out in an urban high-risk city in an epidemic situation or not, whether the residents closely contact with virus carriers or not is judged, epidemic prevention information of the first residents is generated according to the identity information of the first residents and the body temperature information, and after the epidemic prevention information of the first residents is judged to reach a safety index, a first passing instruction is obtained and used for enabling the first food to enter the first community. The safety of the first food and the first food owner is further ensured by detecting the first food owner just meeting the preset grade threshold, generating epidemic prevention information, judging whether the epidemic prevention information meets the safety index and then processing the first food.
Further, if the safety level information of the first food is above the predetermined level threshold, a third communication instruction for causing the first food to enter the first community is obtained.
Specifically, when the safety level information of the first food is above the predetermined level threshold, it indicates that both the food and the food owner are safe, and at this time, a third communication instruction for causing the first food to enter the first community is obtained.
As shown in fig. 5, in order to ensure the safety of the pass command, step S526 in this embodiment of the present application further includes:
step S5261: generating a first verification code according to the first pass instruction, wherein the first verification code corresponds to the first pass instruction one to one;
step S5262: generating a second verification code according to the second passing instruction and the first verification code;
step S5263: taking the first pass instruction and the first verification code as a first storage unit;
step S5264: taking the second pass instruction and the second verification code as a second storage unit;
step S5265: and respectively copying and storing the first storage unit and the second storage unit on two devices.
Specifically, hash calculation is performed on the first pass instruction 1 to obtain a first verification code, where the first verification code corresponds to the first pass instruction one to one; performing hash calculation according to the second passing instruction 1 and the first verification code to obtain a second verification code; the hash calculation is carried out according to the first pass instruction 2 and the second verification code to obtain a third verification code, the encryption processing based on block chain logic is carried out on all the pass instructions, and a block chain technology, also called as a distributed account book technology, is a new technology which is formed by jointly participating in accounting by a plurality of computing devices and jointly maintaining a complete distributed database. The blockchain technology has been widely used in many fields due to its characteristics of decentralization, transparency, participation of each computing device in database records, and rapid data synchronization between computing devices. The method comprises the steps that a first pass instruction 1 and a first verification code are used as a first storage unit, a second pass instruction 1 and a second verification code are used as a second storage unit, a first pass instruction 2 and a third verification code are used as a third storage unit, the first storage unit, the second storage unit and an Nth storage unit are respectively copied and stored on M devices, when the pass instruction needs to be called, after each subsequent node receives data stored by a previous node, the data are verified through a common identification mechanism and stored, and each storage unit is connected in series through a Hash function, so that the pass instruction is not easy to lose and damage, the safety of the pass instruction is guaranteed, and the effect of guaranteeing the safety of food is achieved.
As shown in fig. 6, in order to further encrypt the pass command, step S5265 in this embodiment of the present application further includes:
step S52651: obtaining the recording time of the first storage unit, wherein the recording time of the first storage unit represents the time required to be recorded by the first storage unit;
step S52652: according to the recording time of the first storage unit, the first equipment with the fastest transport capacity in the two pieces of equipment is obtained;
step S52653: sending the recording right of a first storage unit to the first device;
specifically, a predetermined recording time required for the first storage unit is obtained, a device which cannot complete recording of the first storage unit within a predetermined time is excluded, a device which records the first storage unit with the fastest transport capacity among the N devices is obtained, and the recording right of the first storage unit is given to the device. Furthermore, the second storage unit, the third storage unit, · · nth storage unit all adopt a recording method like the first storage unit, so as to ensure safe, effective and stable operation of the decentralized block chain system, and can ensure that the storage units can be rapidly and accurately recorded in the device, so as to ensure the safety of the traffic instructions, and further achieve the effect of ensuring the safety of food.
As shown in fig. 7, in order to accurately process the first food, the step S600 further includes:
step S610: acquiring a global epidemic situation information network according to the big data;
step S620: judging whether the first food is in the node of the global epidemic situation information network or not;
step S630: if the first food is in the node of the global epidemic situation information network, a fourth traffic instruction is obtained, and the fourth traffic instruction is used for forbidding the first food from entering the first community;
specifically, the global epidemic information network specifically refers to a real-time updated global epidemic information sharing network, the nodes are nodes for epidemic outbreak in a global scope, and when the real-time updated epidemic outbreak nodes contain cities with food sources, a fourth traffic instruction is obtained and is used for prohibiting the first food from entering the first community. Through global epidemic situation information obtained in real time, food possibly carrying viruses is prohibited from entering the community, the safety of the first food entering the community is guaranteed, and the effect of guaranteeing the safety of community residents is achieved.
To sum up, the method and the system for processing the community big health information after epidemic situation provided by the embodiment of the application have the following technical effects:
1. the method comprises the steps of inputting source information and type information of first food into a training model, judging the more accurate effect of the input information after training a plurality of groups of training data based on the training model, obtaining more accurate safety grade information of the first food, further obtaining corresponding early warning grade information, processing the first food according to the corresponding early warning grade information, and achieving the technical effects of accurately and effectively supervising the incoming food and further ensuring the food safety and community people safety.
2. The method adopts the mode of refining the first food safety level and generating different passing instructions to determine whether the first food can enter the community, so that the food possibly hiding viruses is isolated outside the community, and the technical effect of ensuring the safety of the community food is further achieved.
3. Due to the fact that the passing instruction is encrypted based on the block chain logic, the passing instruction is not easy to tamper, the safety of the passing instruction is guaranteed, and the effect of guaranteeing the safety of food is achieved.
Example two
Based on the same inventive concept as the method for processing the big health information of the community after the epidemic situation in the previous embodiment, the invention also provides a system for processing the big health information of the community after the epidemic situation, as shown in fig. 8, the system comprises:
a first obtaining unit 11, where the first obtaining unit 11 is configured to obtain source information of a first food, where the source information is source information of the first food entering a first community;
a second obtaining unit 12, where the second obtaining unit 12 is configured to obtain category information of the first food, where the category information is category information of the first food entering the first community;
a first input unit 13, where the first input unit 13 is configured to input the source information and the category information of the first food into a training model, where the training model is obtained by training multiple sets of training data, and each set of training data in the multiple sets includes: source information and the category information of the first food and identification information for identifying a safety level of the first food;
a third obtaining unit 14, wherein the third obtaining unit 14 is configured to obtain output information of the training model, and the output information includes safety level information of the first food;
a fourth obtaining unit 15, where the fourth obtaining unit 15 is configured to obtain corresponding early warning level information according to the safety level information of the first food;
a first processing unit 16, wherein the first processing unit 16 is configured to process the first food according to the corresponding early warning level information.
Further, the system further comprises:
a fifth obtaining unit configured to obtain a predetermined level threshold;
a first judging unit for judging whether the safety level information of the first food is within the predetermined level threshold;
a sixth obtaining unit, configured to obtain first warning level information if the safety level information of the first food is below the predetermined level threshold, where the first warning level information is used to prohibit the first food from entering the first community.
Further, the system further comprises:
a seventh obtaining unit, configured to obtain second warning level information if the safety level information of the first food is within the predetermined level threshold, the second warning level information being used to obtain identity information of the first resident, the first resident being an owner of the first food;
an eighth obtaining unit configured to obtain body temperature information of the first resident;
a ninth obtaining unit, configured to obtain epidemic prevention information of the first resident according to the identity information and the body temperature information of the first resident.
The second judgment unit is used for judging whether the epidemic prevention information of the first resident reaches a safety index or not;
a tenth obtaining unit, configured to obtain a first passing instruction if epidemic prevention information of the first resident reaches the safety index, where the first passing instruction is used to enable the first food to enter the first community;
an eleventh obtaining unit, configured to obtain a second permission instruction if the epidemic prevention information of the first resident does not reach the safety index, where the second permission instruction is used to prohibit the first food from entering the first community.
Further, the system further comprises:
a twelfth obtaining unit, configured to obtain a third routing instruction if the safety level information of the first food is above the predetermined level threshold, the third routing instruction being configured to cause the first food to enter the first community.
Further, the system further comprises:
a thirteenth obtaining unit, configured to generate a first verification code according to the first pass instruction, where the first verification code corresponds to the first pass instruction one to one;
a fourteenth obtaining unit, configured to generate a second verification code according to the second pass instruction and the first verification code.
A fifteenth obtaining unit, configured to use the first pass instruction and the first verification code as a first storage unit;
a sixteenth obtaining unit configured to use the second pass instruction and the second verification code as a second storage unit;
a first storage unit configured to copy and store the first storage unit and the second storage unit in two devices, respectively.
Further, the system further comprises:
a seventeenth obtaining unit, configured to obtain a recording time of the first storage unit, where the recording time of the first storage unit indicates a time that the first storage unit needs to be recorded;
an eighteenth obtaining unit, configured to obtain, according to the recording time of the first storage unit, a first device with the fastest transport capacity of the two devices;
a nineteenth obtaining unit configured to send the recording right of the first storage unit to the first device.
Further, the system further comprises:
a twentieth obtaining unit, configured to obtain a global epidemic situation information network according to the big data;
a third judging unit, configured to judge whether the first food is in a node of the global epidemic situation information network;
a twenty-first obtaining unit, configured to obtain a fourth passing instruction if the first food is in a node of the global epidemic information network, where the fourth passing instruction is used to prohibit the first food from entering the first community.
Various changes and specific examples of the method for processing big health information of a post-epidemic community in the first embodiment of fig. 1 are also applicable to the system for processing big health information of a post-epidemic community of the present embodiment, and through the detailed description of the method for processing big health information of a post-epidemic community, those skilled in the art can clearly know the method for implementing the system for processing big health information of a post-epidemic community in the present embodiment, so for the brevity of the description, detailed description is not repeated here.
Exemplary electronic device
The electronic apparatus of the embodiment of the present application is described below with reference to fig. 9.
Fig. 9 illustrates a schematic structural diagram of an electronic device according to an embodiment of the present application.
Based on the inventive concept of the post-epidemic community big health information processing method in the foregoing embodiment, the present invention further provides a post-epidemic community big health information processing system, on which a computer program is stored, and when the computer program is executed by a processor, the steps of any one of the foregoing post-epidemic community big health information processing methods are implemented.
Where in fig. 9 a bus architecture (represented by bus 300), bus 300 may include any number of interconnected buses and bridges, bus 300 linking together various circuits including one or more processors, represented by processor 302, and memory, represented by memory 304. The bus 300 may also link together various other circuits such as peripherals, voltage regulators, power management circuits, and the like, which are well known in the art, and therefore, will not be described any further herein. A bus interface 306 provides an interface between the bus 300 and the receiver 301 and transmitter 303. The receiver 301 and the transmitter 303 may be the same element, i.e., a transceiver, providing a means for communicating with various other systems over a transmission medium.
The processor 302 is responsible for managing the bus 300 and general processing, and the memory 304 may be used for storing data used by the processor 302 in performing operations.
The embodiment of the invention provides a community big health information processing method after epidemic situation, which comprises the following steps: obtaining source information of a first food, wherein the source information is source information of the first food entering a first community; obtaining category information of the first food, wherein the category information is category information of the first food entering the first community; inputting the source information and the category information of the first food into a training model, wherein the training model is obtained by training a plurality of sets of training data, and each set of training data in the plurality of sets comprises: source information and the category information of the first food and identification information for identifying a safety level of the first food; obtaining output information of the training model, wherein the output information comprises safety level information of the first food; according to the safety level information of the first food, acquiring corresponding early warning level information; and processing the first food according to the corresponding early warning level information. The technical problems that monitoring methods and force for external food are still insufficient and the safety of the food cannot be effectively guaranteed in the prior art are solved, and the technical effects of accurately and effectively supervising the external food and further guaranteeing the safety of the food are achieved.
As will be appreciated by one skilled in the art, 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 flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams 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 a system 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. While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (9)
1. A community big health information processing method after epidemic situation, wherein the method comprises the following steps:
obtaining source information of a first food, wherein the source information is source information of the first food entering a first community;
obtaining category information of the first food, wherein the category information is category information of the first food entering the first community;
inputting the source information and the category information of the first food into a training model, wherein the training model is obtained by training a plurality of sets of training data, and each set of training data in the plurality of sets comprises: source information and the category information of the first food and identification information for identifying a safety level of the first food;
obtaining output information of the training model, wherein the output information comprises safety level information of the first food;
according to the safety level information of the first food, acquiring corresponding early warning level information;
and processing the first food according to the corresponding early warning level information.
2. The method of claim 1, wherein the obtaining corresponding pre-warning level information according to the safety level information of the first food comprises:
obtaining a predetermined grade threshold;
determining whether the safety level information of the first food is within the predetermined level threshold;
and if the safety level information of the first food is below the preset level threshold value, obtaining first early warning level information, wherein the first early warning level information is used for forbidding the first food from entering the first community.
3. The method of claim 2, wherein the method comprises:
if the safety level information of the first food is within the preset level threshold, obtaining second early warning level information, wherein the second early warning level information is used for obtaining identity information of a first resident, and the first resident is an owner of the first food;
obtaining body temperature information of the first resident;
acquiring epidemic prevention information of the first resident according to the identity information and the body temperature information of the first resident;
judging whether the epidemic prevention information of the first resident reaches a safety index;
if the epidemic prevention information of the first resident reaches the safety index, obtaining a first passing instruction, wherein the first passing instruction is used for enabling the first food to enter the first community;
and if the epidemic prevention information of the first resident does not reach the safety index, obtaining a second communication instruction, wherein the second communication instruction is used for forbidding the first food from entering the first community.
4. The method of claim 3, wherein the method comprises:
if the safety level information of the first food is above the predetermined level threshold, obtaining a third communication instruction, wherein the third communication instruction is used for enabling the first food to enter the first community.
5. The method of claim 4, wherein the method comprises:
generating a first verification code according to the first pass instruction, wherein the first verification code corresponds to the first pass instruction one to one;
generating a second verification code according to the second passing instruction and the first verification code;
taking the first pass instruction and the first verification code as a first storage unit;
taking the second pass instruction and the second verification code as a second storage unit;
and respectively copying and storing the first storage unit and the second storage unit on two devices.
6. The method of claim 5, wherein the method comprises:
obtaining the recording time of the first storage unit, wherein the recording time of the first storage unit represents the time required to be recorded by the first storage unit;
according to the recording time of the first storage unit, the first equipment with the fastest transport capacity in the two pieces of equipment is obtained;
and sending the recording right of the first storage unit to the first device.
7. The method of claim 1, wherein the method comprises:
acquiring a global epidemic situation information network according to the big data;
judging whether the first food is in the node of the global epidemic situation information network or not;
if the first food is in the nodes of the global epidemic situation information network, a fourth passing instruction is obtained and used for forbidding the first food to enter the first community.
8. A post-epidemic community big health information processing system, wherein the system comprises:
the first obtaining unit is used for obtaining source information of first food, and the source information is source information of the first food entering a first community;
a second obtaining unit, configured to obtain category information of the first food, where the category information is category information of the first food entering the first community;
a first input unit, configured to input the source information and the category information of the first food into a training model, where the training model is obtained by training multiple sets of training data, and each set of training data in the multiple sets includes: source information and the category information of the first food and identification information for identifying a safety level of the first food;
a third obtaining unit, configured to obtain output information of the training model, where the output information includes safety level information of the first food;
a fourth obtaining unit, configured to obtain corresponding early warning level information according to the safety level information of the first food;
and the first processing unit is used for processing the first food according to the corresponding early warning level information.
9. A post-epidemic community health information processing system, comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor executes the program to implement the steps of the method according to any one of claims 1 to 7.
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Application publication date: 20201222 |