Food safety risk assessment method and system based on intelligent agricultural batch supervision

Abstract

The invention discloses a food safety risk assessment method and system based on intelligent agricultural batch supervision, relates to the technical field of risk assessment, formulates an agricultural batch food safety assessment project, and constructs a food safety traceability chain based on the agricultural batch food safety assessment project, the food safety tracing chain comprises safety detection parameter types corresponding to a food production link and a food forming link; setting a cloud database corresponding to the food safety traceability chain, and setting safe eggs corresponding to the cloud database; safety detection parameters of food are collected based on the food safety traceability chain, and the safety detection parameters are stored in the cloud database; and evaluating the safety risk of the food based on the safety detection parameters of the food to obtain an evaluation result. According to the method, subsequent storage of the food safety detection data can be guaranteed, malicious behaviors are prevented from accessing and modifying the food safety detection data, the accuracy of food safety assessment is guaranteed, and a good food safety management effect is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of risk assessment, and in particular to a food safety risk assessment method and system based on smart agricultural wholesale supervision. Background Art

[0002] With the improvement of living standards and the change of consumption concepts, consumers have higher and higher requirements for food safety. They not only require food to taste good and be nutritious, but also require food to be reliable and safe. Therefore, the food safety risk assessment method of smart agricultural wholesale supervision also needs to be continuously improved and perfected to meet consumers' high requirements for food safety. Since food safety is an issue that the food processing industry attaches great importance to, it is currently difficult to test and store the food safety parameters collected by professional testing institutions in the corresponding food processing links. There are security issues in data storage, which can easily lead to inaccuracies in subsequent food safety assessments. Summary of the invention

[0003] The purpose of the present invention is to provide a food safety risk assessment method and system based on smart agricultural wholesale supervision to address the deficiencies in the background technology.

[0004] In order to achieve the above object, the present invention provides the following technical solution: a food safety risk assessment method based on smart agricultural wholesale supervision, comprising the following steps: Formulate a safety assessment project for agricultural wholesale food, and build a food safety traceability chain based on the safety assessment project for agricultural wholesale food, where the food safety traceability chain includes the types of safety testing parameters corresponding to the food production link and the food formation link; A cloud database is set up corresponding to the food safety traceability chain, and a safety egg is set up corresponding to the cloud database, wherein the safety egg includes multiple obfuscation ports and information areas; Collect food safety testing parameters based on the food safety traceability chain and store the safety testing parameters in the cloud database; The food safety risk is assessed based on the food safety testing parameters to obtain the assessment results.

[0005] In a preferred embodiment, the step of formulating the safety assessment items for the agricultural batch food and building a food safety traceability chain based on the safety assessment items for the agricultural batch food includes: Determine the safety assessment items for agricultural and wholesale food; Determine the food production links of agricultural food and match the corresponding safety assessment items; Determine the corresponding safety detection parameter type according to the safety assessment project, sort the food production links, and bind the corresponding safety detection parameter types of the food production links to obtain the food safety traceability chain.

[0006] In a preferred embodiment, the step of setting up a cloud database corresponding to the food safety traceability chain and setting up a safe egg corresponding to the cloud database includes: Configure a cloud database corresponding to the food safety traceability chain, divide the cloud database into multiple processing links in the food production process in equal quantities, and obtain multiple sub-data spaces; One-to-one correspondence is made between the multiple sub-data spaces and the multiple processing links in the food production link, and the multiple sub-data spaces are sorted according to the corresponding processing links and the corresponding food production links; A data port is set on the cloud database, multiple obfuscation ports are set corresponding to the cloud database, and an information area is set as a safety egg.

[0007] In a preferred embodiment, the steps of setting a data port on the cloud database, setting a plurality of decoy ports corresponding to the cloud database, and setting an information area as a safe egg include: An information area is set outside the cloud database, and obfuscated data is stored in the information area; Combining multiple obfuscation ports in the cloud database in pairs without duplication to obtain multiple obfuscation port groups, establishing communication channels between two obfuscation ports in the multiple obfuscation port groups, setting access analysis points in the communication channels, and connecting the obfuscation ports to the information area; A connection group and a main data port are set in the data port, and the main data port is connected to the cloud database. The connection group is composed of multiple transfer ports, and the number of transfer ports is the same as the number of obfuscation port groups. The transfer ports are matched one-to-one with the obfuscation port groups, and the transfer ports are connected to any obfuscation port in the corresponding obfuscation port group.

[0008] In a preferred embodiment, the steps of establishing a communication channel between two decoy ports of a plurality of decoy port groups, setting an access analysis point in the communication channel, and connecting the decoy port to the information area include: Establishing a communication channel between two obfuscation ports of the plurality of obfuscation port groups, wherein the communication channel passes through the cloud database and avoids the plurality of sub-data spaces; An access analysis point is set in the communication channel, and the access analysis point is connected to the obfuscation port of the communication channel; The confusion port leads to the information area.

[0009] In a preferred embodiment, the step of collecting food safety detection parameters based on the food safety traceability chain and storing the safety detection parameters in a cloud database includes: According to the food production links in the food safety traceability chain, the corresponding safety detection parameter types of the food are tested to obtain safety detection parameters; The safety detection parameters are stored in the sub-data space corresponding to the food production link.

[0010] In a preferred embodiment, the step of evaluating the safety risk of food based on the food safety detection parameters to obtain the evaluation result comprises: Formulate corresponding preset safety parameters for corresponding safety detection parameter types; Obtain the safety detection parameters in the entire food production process and compare them with the corresponding preset safety parameters, and regard the safety detection parameters that do not meet the preset safety parameters as abnormal parameters; An assessment result is obtained based on the abnormal parameters and the gap values ​​that do not meet the preset safety parameters, wherein the assessment result is a risk assessment table of the abnormal parameters and the corresponding gap values ​​that do not meet the preset safety parameters.

[0011] The present invention also provides a food safety risk assessment system based on smart agricultural wholesale supervision, comprising: A formulation module is used to formulate safety assessment items for agricultural batch foods, and to build a food safety traceability chain based on the safety assessment items for agricultural batch foods, wherein the food safety traceability chain includes the types of safety testing parameters corresponding to the food production link and the food formation link; A setting module, connected to the formulation module, for setting a cloud database corresponding to the food safety traceability chain, and setting a safety egg corresponding to the cloud database, wherein the safety egg includes a plurality of obfuscation ports and an information area; A storage module, connected to the setting module, for collecting food safety detection parameters based on the food safety traceability chain and storing the safety detection parameters in a cloud database; The evaluation module is connected to the storage module and is used to evaluate the safety risk of the food based on the safety detection parameters of the food to obtain the evaluation result.

[0012] In the above technical solution, the technical effects and advantages provided by the present invention are: When the external access of the present invention selects the decoy port, it can obtain the decoy data in the information area through a decoy port group. The decoy port is open in the information area. Even when the data port is selected, the external access can be screened by the characteristic information through the connection group. The external access that meets the characteristic information is guided to the corresponding decoy port through the transfer port that meets the characteristic information, so that it obtains the decoy data in the information area. The access screened by the connection group will normally access the data end through the main data port. It can have a good cloud database security protection function, can ensure the subsequent preservation of food safety detection data, avoid malicious behavior to access and modify the food safety detection data, ensure the accuracy of food safety assessment, and have a good food safety management function. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0014] Figure 1 The present invention is a flow chart of the method.

[0015] Figure 2 It is a system block diagram of the present invention. DETAILED DESCRIPTION

[0016] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0017] Example 1, please refer to Figure 1 As shown, the food safety risk assessment method based on smart agricultural wholesale supervision described in this embodiment includes the following steps: S1. Formulate a safety assessment project for agricultural wholesale food and build a food safety traceability chain based on the safety assessment project for agricultural wholesale food. The food safety traceability chain includes the types of safety testing parameters corresponding to the food production link and the food formation link; S2. A cloud database is set up corresponding to the food safety traceability chain, and a safety egg is set up corresponding to the cloud database, wherein the safety egg includes a plurality of obfuscation ports and an information area; S3. Collect food safety testing parameters based on the food safety traceability chain and store the safety testing parameters in a cloud database; S4. Evaluate the food safety risk based on the food safety testing parameters and obtain the evaluation results; As described in the above steps S1-S4, when an obfuscation port is selected, external access can obtain the obfuscated data in the information area through a obfuscation port group. The obfuscation port is open in the information area. Even if a data port is selected, the external access can be screened by the characteristic information through the connection group. The external access that meets the characteristic information is guided to the corresponding obfuscation port through the transfer port that meets the characteristic information, so that it obtains the obfuscated data in the information area. The access screened by the connection group will access the data end normally through the main data port. It can have a good cloud database security protection function, can ensure the subsequent preservation of food safety detection data, avoid malicious behavior to access and modify the food safety detection data, ensure the accuracy of food safety assessment, and have a good food safety management function.

[0018] In one embodiment, the step S1 of formulating the safety assessment items for the agricultural batch food and building the food safety traceability chain based on the safety assessment items for the agricultural batch food comprises: S11. Determine the safety assessment items for agricultural food; S12. Determine the food production links of agricultural food and match the corresponding safety assessment items; S13. Determine the corresponding safety detection parameter type according to the safety assessment project, sort the food production links, and bind the corresponding safety detection parameter types of the food production links to obtain a food safety traceability chain; As described in the above steps S11-S13, the safety assessment items of agricultural bulk food are determined, where the safety assessment items of agricultural bulk food are the detection of agricultural residues in raw materials, vegetables and other agricultural products, and additives in the food processing link. Then, the food production link is determined, which includes the raw material (agricultural product) link and multiple processing links of processing raw materials into food. Then, corresponding safety assessment items are configured for the multiple links, and agricultural residue items are detected in the raw material link. In the subsequent multiple processing links of processing raw materials into food, additive detection items are detected. Then, corresponding safety detection parameter types are determined for the corresponding safety assessment items, for example, various types of agricultural drugs acting on raw materials in the agricultural residue detection items, and types of additives in multiple processing links of processing raw materials into food; the food production links are sorted, and the safety detection parameter types corresponding to the food formation links are bound to obtain a food safety traceability chain.

[0019] In one embodiment, the step S2 of setting up a cloud database corresponding to the food safety traceability chain and setting up a safety egg corresponding to the cloud database includes: S21. Configure a cloud database corresponding to the food safety traceability chain, and divide the cloud database into equal parts according to multiple processing links in the food production process to obtain multiple sub-data spaces; S22, one-to-one correspondence between the multiple sub-data spaces and the multiple processing links in the food production link, and sorting the multiple sub-data spaces according to the corresponding processing links and the corresponding food production links; S23, setting a data port on the cloud database, setting a plurality of obfuscated ports corresponding to the cloud database, and setting an information area as a safety egg; As described in the above steps S21-S23, a cloud database is configured corresponding to the food safety traceability chain, and the cloud database is used to store the subsequent safety detection parameters in the food safety traceability chain. The cloud database is divided into multiple sub-data spaces according to the same number of multiple processing links in the food production link to obtain multiple sub-data spaces, and the corresponding processing links store the corresponding safety detection parameters in the corresponding sub-data spaces; the multiple sub-data spaces are matched one by one with the multiple processing links in the food production link, and the multiple sub-data spaces are sorted according to the corresponding processing links corresponding to the food production links. The sub-data spaces are arranged according to the food safety traceability chain, wherein the food production link in the food safety traceability chain includes all links in the food processing process. Since the cloud database is used to store subsequent safety detection parameters, in order to ensure the security of storage, a data port is set on the cloud database, and the data port here is used for the cloud database to communicate with the outside world for use by special personnel. The cloud database sets multiple obfuscation ports to avoid external network attacks on the database in the cloud database, and the corresponding cloud database sets an information area, and the information area, multiple obfuscation ports and data ports are used as security eggs, which can optimize the structure of the database and ensure the security of data storage.

[0020] In one embodiment, the step S23 of setting a data port on the cloud database, setting a plurality of decoy ports corresponding to the cloud database, and setting an information area as a safe egg includes: S231, setting an information area outside the cloud database, and storing deceptive data in the information area; S232, combining the multiple obfuscation ports in the cloud database in pairs without duplication to obtain multiple obfuscation port groups, respectively establishing communication channels between two obfuscation ports in the multiple obfuscation port groups, setting access analysis points in the communication channels, and connecting the obfuscation ports to the information area; S233, setting a connection group and a main data port in the data port, the main data port is connected to the cloud database, wherein the connection group is composed of a plurality of transfer ports, the number of the transfer ports is the same as the number of the obfuscation port groups, the transfer ports are matched one-to-one with the obfuscation port groups, and the transfer ports are connected to any one of the obfuscation ports in the corresponding obfuscation port groups; In one embodiment, the step S232 of establishing a communication channel between two decoy ports of the plurality of decoy port groups, setting an access analysis point in the communication channel, and connecting the decoy port to the information area comprises: S2321, establishing a communication channel between two decoy ports of multiple decoy port groups, where the communication channel passes through the cloud database and avoids multiple sub-data spaces; S2322, setting an access analysis point in the communication channel, wherein the access analysis point is connected to the obfuscation port of the communication channel; S2323, the obfuscation port leads to the information area; As described in the above steps 231-233, the information area is a larger database, and the cloud database is stored in the database. The storage space between the database and the cloud database is used as the information area, and the obfuscated information is stored in the information area. The obfuscated information here is useless and messy information. The multiple obfuscated ports set on the cloud database are combined in pairs without duplication. For example, A1, A2, A3 and A4 are used to represent four obfuscated ports. The non-repeating combination of two pairs can be combined into A1 and A2 and A3 and A4, which means that a obfuscated port can only participate in one combination, and repeated combinations cannot occur. After that, the two obfuscated ports after the combination are used as an obfuscated port group, and a communication channel is established between two obfuscated ports of the multiple obfuscated port groups. An access analysis point is set in the communication channel, wherein the access analysis point is used to transmit to another obfuscation port of the combination through the transmission channel when an external network invades the obfuscation port. During the transmission of the transmission channel, the characteristic information of the external network invasion can be analyzed through the access analysis point, and the characteristic information here includes the network address and identity of the external network invasion. Since the access analysis point is connected to the obfuscation port of the communication channel, the analyzed characteristic information can be provided to the obfuscation port. The number of transfer ports is the same as the number of obfuscation port groups. The transfer port is one-to-one corresponding to the obfuscation port group, and the transfer port is connected to any obfuscation port in the corresponding obfuscation port group. After that, the obfuscation port can provide the characteristic information to the corresponding transfer port in the connection group. The port can be transferred to store characteristic information. The main data port is close to the cloud database, and the connection group is far away from the database. When there is data access, it is necessary to pass through the connection group first, and then the access after passing the connection group will be formally accessed through the main data port to access the cloud database. A communication channel between two obfuscated ports of multiple obfuscated port groups is established. The communication channel passes through the cloud database and avoids multiple sub-data spaces. There are storage space intervals in multiple sub-data spaces. The communication channels of multiple obfuscated port groups can avoid the sub-data spaces, which can enable external networks to directly pass through the cloud database through the transmission channel, and cannot obtain data in the cloud database. The use of the security egg on the cloud database is as follows: Due to the existence of multiple obfuscated ports, external access is easy to select the obfuscated ports. The port greatly improves the security protection of the cloud database. When the external access selects the obfuscation port, the characteristic information will be analyzed through the corresponding transmission channel, and then the characteristic information will be provided to the corresponding obfuscation port through the access analysis point. Then the obfuscation port provides the characteristic information to the corresponding transfer port, and the characteristic information is stored through the transfer port. In this way, when the external access selects the obfuscation port, it can obtain the obfuscated data in the information area through a obfuscation port group. The obfuscation port is open in the information area. Even if the data port is selected, the external access can be screened by the characteristic information through the connection group, and the external access that meets the characteristic information is guided to the corresponding obfuscation port through the transfer port that meets the characteristic information, so that it can obtain the obfuscated data in the information area.The access that passes the connection group screening can access the data end normally through the main data port, which can have a good cloud database security protection effect, can ensure the subsequent preservation of food safety detection data, avoid malicious behavior to access and modify food safety detection data, ensure the accuracy of food safety assessment, and have a good food safety management effect; In one embodiment, the step S3 of collecting food safety detection parameters based on the food safety traceability chain and storing the safety detection parameters in a cloud database includes: S31. Detect the food safety detection parameter types corresponding to the food production links in the food safety traceability chain to obtain safety detection parameters; S32, storing the safety detection parameters in the sub-data space corresponding to the food production link; As described in the above steps S31 and S32, the safety detection parameter types corresponding to the food production links in the food safety traceability chain are detected to obtain safety detection parameters, which are specific food safety component parameters. The safety detection parameters are then stored in the sub-data space corresponding to the food production link. The safety detection parameters in the sub-data space can be securely guaranteed through the safety egg.

[0021] In one embodiment, the step S4 of evaluating the safety risk of food based on the food safety detection parameters to obtain the evaluation result includes: S41, formulate corresponding preset security parameters corresponding to the security detection parameter type; S42, obtaining safety detection parameters in the entire food production process and comparing them with corresponding preset safety parameters, and treating safety detection parameters that do not meet the preset safety parameters as abnormal parameters; S43, obtaining an assessment result based on the abnormal parameters and the gap values ​​that do not meet the preset safety parameters, wherein the assessment result is a risk assessment table of the abnormal parameters and the corresponding gap values ​​that do not meet the preset safety parameters; As described in the above steps S41-S43, corresponding preset safety parameters are formulated for corresponding safety detection parameter types as a standard for abnormal judgment, and the safety detection parameters in the entire food production link are obtained and compared with the corresponding preset safety parameters respectively. The safety detection parameters that do not meet the preset safety parameters are taken as abnormal parameters, and then the abnormal parameters and the gap values ​​that do not meet the preset safety parameters are evaluated to obtain evaluation results. The evaluation results are risk assessment tables of abnormal parameters and corresponding gap values ​​that do not meet the preset safety parameters, which can provide staff with information about safety risks in the food production link and have a good food safety risk management effect.

[0022] Example 2, please refer to Figure 2As shown, the food safety risk assessment system based on smart agricultural wholesale supervision described in this embodiment includes: A formulation module is used to formulate safety assessment items for agricultural batch foods, and to build a food safety traceability chain based on the safety assessment items for agricultural batch foods, wherein the food safety traceability chain includes the types of safety testing parameters corresponding to the food production link and the food formation link; A setting module, connected to the formulation module, for setting a cloud database corresponding to the food safety traceability chain, and setting a safety egg corresponding to the cloud database, wherein the safety egg includes a plurality of obfuscation ports and an information area; A storage module, connected to the setting module, for collecting food safety detection parameters based on the food safety traceability chain and storing the safety detection parameters in a cloud database; The evaluation module is connected to the storage module and is used to evaluate the safety risk of the food based on the safety detection parameters of the food to obtain the evaluation result.

[0023] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A food safety risk assessment method based on smart agricultural wholesale supervision, characterized in that: The following steps are involved: Formulate a safety assessment project for agricultural wholesale food, and build a food safety traceability chain based on the safety assessment project for agricultural wholesale food, where the food safety traceability chain includes the types of safety testing parameters corresponding to the food production link and the food formation link; A cloud database is set up corresponding to the food safety traceability chain, and a safety egg is set up corresponding to the cloud database, wherein the safety egg includes multiple obfuscation ports and information areas; Collect food safety testing parameters based on the food safety traceability chain and store the safety testing parameters in the cloud database; The food safety risk is assessed based on the food safety testing parameters to obtain the assessment results.

2. A food safety risk assessment method based on smart agricultural wholesale supervision according to claim 1, characterized in that: The steps of formulating the safety assessment project for agricultural food and building a food safety traceability chain based on the safety assessment project for agricultural food include: Determine the safety assessment items for agricultural and wholesale food; Determine the food production links of agricultural food and match the corresponding safety assessment items; Determine the corresponding safety detection parameter type according to the safety assessment project, sort the food production links, and bind the corresponding safety detection parameter types of the food production links to obtain the food safety traceability chain.

3. The food safety risk assessment method based on smart agricultural wholesale supervision according to claim 1 is characterized in that: The steps of setting up a cloud database corresponding to the food safety traceability chain and setting up a safety egg corresponding to the cloud database include: Configure a cloud database corresponding to the food safety traceability chain, divide the cloud database into multiple processing links in the food production process in equal quantities, and obtain multiple sub-data spaces; One-to-one correspondence is made between the multiple sub-data spaces and the multiple processing links in the food production link, and the multiple sub-data spaces are sorted according to the corresponding processing links and the corresponding food production links; A data port is set on the cloud database, multiple obfuscation ports are set corresponding to the cloud database, and an information area is set as a safety egg.

4. A food safety risk assessment method based on smart agricultural wholesale supervision according to claim 3, characterized in that: The steps of setting a data port on the cloud database, setting a plurality of obfuscated ports corresponding to the cloud database, and setting an information area as a safety egg include: An information area is set outside the cloud database, and obfuscated data is stored in the information area; Combining multiple obfuscation ports in the cloud database in pairs without duplication to obtain multiple obfuscation port groups, establishing communication channels between two obfuscation ports in the multiple obfuscation port groups, setting access analysis points in the communication channels, and connecting the obfuscation ports to the information area; A connection group and a main data port are set in the data port, and the main data port is connected to the cloud database. The connection group is composed of multiple transfer ports, and the number of transfer ports is the same as the number of obfuscation port groups. The transfer ports are matched one-to-one with the obfuscation port groups, and the transfer ports are connected to any obfuscation port in the corresponding obfuscation port group.

5. A food safety risk assessment method based on smart agricultural wholesale supervision according to claim 4, characterized in that: The steps of establishing a communication channel between two decoy ports of the plurality of decoy port groups, setting an access analysis point in the communication channel, and connecting the decoy port to the information area include: Establishing a communication channel between two obfuscation ports of the plurality of obfuscation port groups, wherein the communication channel passes through the cloud database and avoids the plurality of sub-data spaces; An access analysis point is set in the communication channel, and the access analysis point is connected to the obfuscation port of the communication channel; The confusion port leads to the information area.

6. The food safety risk assessment method based on smart agricultural wholesale supervision according to claim 1 is characterized in that: The step of collecting food safety detection parameters based on the food safety traceability chain and storing the safety detection parameters in a cloud database includes: According to the food production links in the food safety traceability chain, the corresponding safety detection parameter types of the food are tested to obtain safety detection parameters; The safety detection parameters are stored in the sub-data space corresponding to the food production link.

7. The food safety risk assessment method based on smart agricultural wholesale supervision according to claim 1 is characterized in that: The step of evaluating the food safety risk based on the food safety detection parameters to obtain the evaluation result comprises: Formulate corresponding preset safety parameters for corresponding safety detection parameter types; Obtain the safety detection parameters in the entire food production process and compare them with the corresponding preset safety parameters, and regard the safety detection parameters that do not meet the preset safety parameters as abnormal parameters; An assessment result is obtained based on the abnormal parameters and the gap values ​​that do not meet the preset safety parameters, wherein the assessment result is a risk assessment table of the abnormal parameters and the corresponding gap values ​​that do not meet the preset safety parameters.

8. A food safety risk assessment system based on smart agricultural wholesale supervision, used to implement a food safety risk assessment method based on smart agricultural wholesale supervision as described in any one of claims 1 to 7, characterized in that: include: A formulation module is used to formulate safety assessment items for agricultural batch foods, and to build a food safety traceability chain based on the safety assessment items for agricultural batch foods, wherein the food safety traceability chain includes the types of safety testing parameters corresponding to the food production link and the food formation link; A setting module, connected to the formulation module, for setting a cloud database corresponding to the food safety traceability chain, and setting a safety egg corresponding to the cloud database, wherein the safety egg includes a plurality of obfuscation ports and an information area; A storage module, connected to the setting module, for collecting food safety detection parameters based on the food safety traceability chain and storing the safety detection parameters in a cloud database; The evaluation module is connected to the storage module and is used to evaluate the safety risk of the food based on the safety detection parameters of the food to obtain the evaluation result.

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