A smart agricultural product traceability and health evaluation method, system, device and storage medium based on Beidou grid code

Abstract

The present invention discloses a smart agricultural product traceability and health evaluation method based on Beidou grid code, comprising the following steps: obtaining regional information, planting information and sales information of agricultural products, encoding the area where agricultural products are planted through Beidou grid code; associating the regional information, planting information and sales information of agricultural products with Beidou grid code, storing the regional information, planting information and sales information of agricultural products in a traceability database; setting a companion robot to obtain the regional information, planting information and sales information of agricultural products, and setting fuzzy evaluation rules for agricultural products; the companion robot makes health evaluation suggestions according to the fuzzy evaluation rules for agricultural products. The planting plot and planting area information of agricultural products are obtained through the Beidou navigation system. The present invention can realize the traceability of the planting and sales information of agricultural products, and provide dietary suggestions for the elderly based on the planting and sales information of agricultural products.

Description

Technical Field

[0001] The present invention relates to the technical field of agricultural product safety management, and in particular to a smart agricultural product traceability and health evaluation method, system, device and storage medium based on Beidou grid code. Background Art

[0002] With the rapid development of society, the aging population is getting worse and the size of the elderly population is expanding. Against this background, the health issues of the elderly are receiving more and more attention. However, there are many uncertainties in the current agricultural product market. On the one hand, the sources of agricultural products are complex and diverse, and different pesticides and fertilizers may be used in the planting process, making it difficult for consumers to know the quality and safety of agricultural products. On the other hand, there are many circulation links of agricultural products in the market, and there is a lack of effective traceability methods. Once a problem occurs, it is difficult to quickly and accurately find the source of the problem.

[0003] In addition, the elderly are physically weaker and have higher requirements for the health and quality of their diet. If the safety and suitability of agricultural products cannot be guaranteed, it will directly affect the physical health and quality of life of the elderly. At the same time, most of the existing companion robots only have simple companionship and entertainment functions, and do not have the function of tracing the source of agricultural products and providing dietary evaluation for the elderly. Summary of the invention

[0004] The present invention provides a method, system, device and storage medium for smart agricultural product traceability and health evaluation based on Beidou grid code, which can trace the planting and sales information of agricultural products and provide dietary advice for the elderly based on the planting and sales information of agricultural products. The specific technical solution is as follows:

[0005] A smart agricultural product traceability and health evaluation method based on Beidou grid code includes the following steps:

[0006] Obtain regional information, planting information, and sales information of agricultural products, and encode the areas where agricultural products are planted using Beidou grid codes;

[0007] The regional information, planting information and sales information of agricultural products are associated with the Beidou grid code, and the regional information, planting information and sales information of agricultural products are stored in the traceability database;

[0008] Set up a companion robot to obtain regional information, planting information, and sales information of agricultural products, and set up fuzzy evaluation rules for agricultural products;

[0009] The companion robot makes health evaluation suggestions based on fuzzy evaluation rules of agricultural products.

[0010] Preferably, when encoding the area where agricultural products are planted by means of Beidou grid code, the agricultural products are coded at the planting plot level and the planting area level.

[0011] Preferably, the step of performing planting plot level coding and planting area level coding on the agricultural products comprises the following steps:

[0012] Obtain the planting plots of agricultural products and the planting areas to which the agricultural products belong through the Beidou navigation system;

[0013] The planting plots of agricultural products are Beidou grid coded, and the planting areas to which the agricultural products belong are Beidou grid coded.

[0014] Preferably, associating the regional information, planting information and sales information of the agricultural products with the Beidou grid code comprises the following steps:

[0015] Use Beidou grid codes as retrieval indexes for regional information, planting information, and sales information of agricultural products;

[0016] Set up the traceability database index structure and establish the mapping relationship between the regional information, planting information and sales information of agricultural products and the Beidou grid code.

[0017] Preferably, the setting of fuzzy evaluation rules for agricultural products comprises the following steps:

[0018] According to the planting information of agricultural products, the planting health evaluation factors of agricultural products are set; according to the sales information of agricultural products, the sales evaluation factors of agricultural products are set;

[0019] The evaluation fuzzy set of agricultural products is set according to the evaluation factors of agricultural product planting health and sales;

[0020] Agricultural products are evaluated based on their evaluation fuzzy sets.

[0021] Preferably, the companion robot makes health evaluation suggestions according to the fuzzy evaluation rules of agricultural products, including the following steps:

[0022] Obtain planting and sales information of agricultural products, and obtain users' daily diet information;

[0023] Make active daily diet recommendations to users based on their daily diet information, planting information, and sales information; receive diet recommendation requests from users, and make passive daily diet recommendations to users based on the planting information and sales information of agricultural products;

[0024] The user's current diet information is obtained, and the user's current diet is evaluated based on active daily diet recommendations or passive daily diet recommendations.

[0025] A smart agricultural product traceability and health evaluation method based on Beidou grid code includes a first computing unit for obtaining regional information, planting information and sales information of agricultural products, and encoding the area where agricultural products are planted through Beidou grid code;

[0026] In the second computing unit, the user associates the regional information, planting information and sales information of the agricultural products with the Beidou grid code, and stores the regional information, planting information and sales information of the agricultural products in the traceability database;

[0027] The third computing unit is used to set the companion robot to obtain regional information, planting information and sales information of agricultural products, and to set fuzzy evaluation rules for agricultural products;

[0028] The fourth computing unit is used for the companion robot to make health evaluation suggestions based on the fuzzy evaluation rules of agricultural products.

[0029] A smart agricultural product traceability and health evaluation device based on Beidou grid code, the device comprising a processor and a memory; the memory is used to store program code and transmit the program code to the processor;

[0030] The processor is used to execute the steps of the above-mentioned Beidou grid code-based smart agricultural product traceability and health evaluation method according to the instructions in the program code.

[0031] A computer-readable storage medium is used to store program code, and the program code is used to execute the steps of the above-mentioned smart agricultural product traceability and health evaluation method based on Beidou grid code.

[0032] Compared with the prior art, the present invention has the following beneficial effects:

[0033] The present invention encodes the area where agricultural products are planted through the Beidou grid code, which can accurately locate the source of agricultural products and ensure their traceability. The regional information, planting information and sales information of agricultural products are obtained, and this information is associated with the Beidou grid code and stored in the traceability database. In this way, both consumers and regulatory authorities can query the detailed information of agricultural products at any time to understand the entire process from the field to the table. At the same time, a companion robot is set to obtain the regional information, planting information and sales information of agricultural products, and provide health evaluation suggestions for the elderly according to the preset fuzzy evaluation rules. The companion robot can recommend agricultural products suitable for them according to the physical condition, eating habits and health needs of the elderly, and provide dietary matching suggestions, which helps to ensure the health and quality of the elderly's diet, and can also improve their quality of life and sense of happiness. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following is a brief introduction to the drawings required for the specific embodiments or the description of the prior art. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn according to the actual scale.

[0035] Figure 1 The present invention is a flow chart of the method. DETAILED DESCRIPTION

[0036] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions 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.

[0037] It should be understood that when used in this specification and the appended claims, the terms "include" and "comprises" indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0038] It should also be understood that the terms used in the present specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the present specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0039] It should be further understood that the term "and / or" used in the present description and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0040] Example 1

[0041] As shown in the figure, a smart agricultural product traceability and health evaluation method based on Beidou grid code includes the following steps:

[0042] Obtain regional information, planting information, and sales information of agricultural products, and encode the areas where agricultural products are planted using Beidou grid codes;

[0043] The regional information, planting information and sales information of agricultural products are associated with the Beidou grid code, and the regional information, planting information and sales information of agricultural products are stored in the traceability database;

[0044] Set up a companion robot to obtain regional information, planting information, and sales information of agricultural products, and set up fuzzy evaluation rules for agricultural products;

[0045] The companion robot makes health evaluation suggestions based on fuzzy evaluation rules of agricultural products.

[0046] The planting plots and planting area information of agricultural products are obtained through the Beidou navigation system. The planting plots are coded with high-precision Beidou grids, and the planting areas are coded with relatively low-precision Beidou grids, thus realizing hierarchical positioning coding of the source of agricultural product planting.

[0047] The Beidou grid code is used as a search index, and the traceability database index structure is set to establish a mapping relationship between the regional information, planting information, and sales information of agricultural products and the Beidou grid code. When you need to query the information of a specific agricultural product, you can quickly locate the relevant data through the Beidou grid code to improve the efficiency of information retrieval. The information related to agricultural products is stored in the traceability database to ensure the integrity and traceability of the data.

[0048] Planting health evaluation factors are set according to the planting information of agricultural products, such as soil fertility, irrigation water quality, fertilizer use, pest and disease control measures, etc.; sales evaluation factors are set according to sales information, such as market reputation, brand awareness, after-sales service, etc. Fuzzy reasoning and evaluation are performed based on the input agricultural product information, and specific health evaluation suggestions are finally obtained.

[0049] The companion robot obtains regional information, planting information, and sales information of agricultural products, as well as the user's daily diet information through the traceability database. Based on the user's daily diet information, planting information, and sales information, it makes active daily diet recommendations to the user, such as providing personalized diet recommendations based on the user's health goals and the health evaluation results of agricultural products. After receiving the diet recommendation request sent by the user, it makes passive daily diet recommendations to the user based on the planting information and sales information of agricultural products, and provides more detailed agricultural product information and cooking methods. It obtains the user's current diet information, evaluates the user's current diet based on active or passive daily diet recommendations, and provides feedback and improvement suggestions to the user.

[0050] Example 2

[0051] This embodiment is different from Embodiment 1 in that, when encoding the area where agricultural products are planted by using the Beidou grid code, the agricultural products are coded at the planting plot level and the planting area level.

[0052] Agricultural products are coded at the planting plot level and planting area level. Through the positioning function of the Beidou navigation system, the specific planting plots of agricultural products and the larger planting areas to which they belong can be distinguished. Through the positioning function of the Beidou navigation system, a larger planting area can be determined, which may cover multiple planting plots and different growers. The planting area level coding is mainly used to manage and analyze the planting situation of agricultural products within a certain range from a macro perspective. Through the planting area level coding, we can quickly understand the overall layout of agricultural product planting, planting area, main planting varieties and other information in a certain area, and then store the relevant information of agricultural products in the area in the traceability database.

[0053] Example 3

[0054] The difference between this embodiment and embodiment 2 is that the step of performing planting plot level coding and planting area level coding on the agricultural products comprises the following steps:

[0055] Obtain the planting plots of agricultural products and the planting areas to which the agricultural products belong through the Beidou navigation system;

[0056] The planting plots of agricultural products are Beidou grid coded, and the planting areas to which the agricultural products belong are Beidou grid coded.

[0057] After obtaining the planting plots and planting areas of agricultural products through the Beidou navigation system, Beidou grid coding is performed on them respectively. For the coding of planting plots, the location information of each plot is recorded, which provides a search index for the subsequent tracing of the growth environment and planting process of individual agricultural products. The coding of planting areas facilitates the classification and management of multiple planting plots, such as statistics on the output and quality of agricultural products in a certain area. This coding method enables multi-level query and analysis from micro planting plots to macro planting areas in the process of agricultural product traceability, which improves the accuracy and comprehensiveness of traceability.

[0058] Example 4

[0059] This embodiment is different from Embodiment 3 in that associating the regional information, planting information and sales information of the agricultural products with the Beidou grid code comprises the following steps:

[0060] Use Beidou grid codes as retrieval indexes for regional information, planting information, and sales information of agricultural products;

[0061] Set up the traceability database index structure and establish the mapping relationship between the regional information, planting information and sales information of agricultural products and the Beidou grid code.

[0062] Associate the regional information, planting information and sales information of agricultural products with the Beidou grid code. Use the Beidou grid code as a search index. When you need to query the relevant information of a certain agricultural product, you can quickly locate the specific data of the agricultural product by entering the corresponding Beidou grid code. Set up the traceability database index structure and establish a mapping relationship between agricultural product information and Beidou grid code, so that the database is more efficient in storing and retrieving data. For example, when a specific Beidou grid code is entered, the database can quickly find the corresponding agricultural product regional information, planting information and sales information, providing timely and accurate traceability services for consumers, regulatory authorities, etc.

[0063] Example 5

[0064] The difference between this embodiment and embodiment 4 is that the setting of fuzzy evaluation rules for agricultural products includes the following steps:

[0065] According to the planting information of agricultural products, the planting health evaluation factors of agricultural products are set; according to the sales information of agricultural products, the sales evaluation factors of agricultural products are set;

[0066] The evaluation fuzzy set of agricultural products is set according to the evaluation factors of agricultural product planting health and sales;

[0067] Agricultural products are evaluated based on their evaluation fuzzy sets.

[0068] Set up fuzzy evaluation rules for agricultural products. First, set up planting health evaluation factors based on the planting information of agricultural products. These factors reflect the health of agricultural products during the growth process, such as soil quality, irrigation water source, fertilization, and pest and disease control measures. Then, set up sales evaluation factors based on sales information, including market reputation, reliability of sales channels, after-sales service, etc. Set up evaluation fuzzy sets based on these factors, and evaluate agricultural products by determining fuzzy grades and membership functions. This evaluation method can more comprehensively and objectively reflect the quality and value of agricultural products, and provide consumers with more valuable health evaluation suggestions.

[0069] Example 6

[0070] This embodiment is different from Embodiment 5 in that the companion robot makes health evaluation suggestions according to the fuzzy evaluation rules of agricultural products, including the following steps:

[0071] Obtain planting and sales information of agricultural products, and obtain users' daily diet information;

[0072] Make active daily diet recommendations to users based on their daily diet information, planting information, and sales information; receive diet recommendation requests from users, and make passive daily diet recommendations to users based on the planting information and sales information of agricultural products;

[0073] The user's current diet information is obtained, and the user's current diet is evaluated based on active daily diet recommendations or passive daily diet recommendations.

[0074] The companion robot first obtains the planting and sales information of agricultural products, and the user's daily diet information. Based on the user's daily diet information, planting information and sales information, it makes active daily diet recommendations to the user, such as recommending suitable agricultural product combinations and diet plans based on the user's health needs and the characteristics of agricultural products. When receiving a diet recommendation request sent by the user, it makes passive daily diet recommendations to the user based on the planting and sales information of agricultural products, and provides more detailed agricultural product information and cooking suggestions. Finally, it obtains the user's current diet information, and evaluates the user's current diet based on active or passive daily diet recommendations, helping the user to better understand their dietary health status and adjust their eating habits.

[0075] Example 7

[0076] A smart agricultural product traceability and health evaluation system based on Beidou grid code includes a first computing unit for obtaining regional information, planting information and sales information of agricultural products, and encoding the area where agricultural products are planted through Beidou grid code;

[0077] In the second computing unit, the user associates the regional information, planting information and sales information of the agricultural products with the Beidou grid code, and stores the regional information, planting information and sales information of the agricultural products in the traceability database;

[0078] The third computing unit is used to set the companion robot to obtain regional information, planting information and sales information of agricultural products, and to set fuzzy evaluation rules for agricultural products;

[0079] The fourth computing unit is used for the companion robot to make health evaluation suggestions based on the fuzzy evaluation rules of agricultural products.

[0080] Example 8

[0081] A smart agricultural product traceability and health evaluation device based on Beidou grid code, the device comprising a processor and a memory; the memory is used to store program code and transmit the program code to the processor;

[0082] The processor is used to execute the steps of the smart agricultural product traceability and health evaluation method based on Beidou grid code described in Examples 1-6 according to the instructions in the program code.

[0083] Example 9

[0084] A computer-readable storage medium, wherein the computer-readable storage medium is used to store program code, and the program code is used to execute the steps of the smart agricultural product traceability and health evaluation method based on Beidou grid code described in Examples 1-6.

[0085] In summary, the present invention encodes the area where agricultural products are planted through the Beidou grid code, which can accurately locate the source of agricultural products and ensure their traceability. The regional information, planting information and sales information of agricultural products are obtained, and these information are associated with the Beidou grid code and stored in the traceability database. In this way, both consumers and regulatory authorities can query the detailed information of agricultural products at any time to understand the entire process from the field to the table. At the same time, a companion robot is set to obtain the regional information, planting information and sales information of agricultural products, and provide health evaluation suggestions for the elderly according to the preset fuzzy evaluation rules. The companion robot can recommend agricultural products suitable for them according to the physical condition, eating habits and health needs of the elderly, and provide dietary matching suggestions, which helps to ensure the health and quality of the elderly's diet, and can also improve their quality of life and sense of happiness.

[0086] Those of ordinary skill in the art will appreciate that the units of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition of each example has been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0087] In the embodiments provided by the present invention, it should be understood that the division of units is only a logical function division, and there may be other division methods in actual implementation, for example, multiple units can be combined into one unit, one unit can be split into multiple units, or some features can be ignored, etc.

[0088] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0089] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-0nlyMemory), random access memory (RAM, RandomAccessMemory), mobile hard disk, magnetic disk or optical disk, etc., which can store program code.

[0090] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. These modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and specification of the present invention.

Claims

1. A smart agricultural product traceability and health evaluation method based on Beidou grid code, characterized in that: The following steps are involved: Obtain regional information, planting information, and sales information of agricultural products, and encode the areas where agricultural products are planted using Beidou grid codes; The regional information, planting information and sales information of agricultural products are associated with the Beidou grid code, and the regional information, planting information and sales information of agricultural products are stored in the traceability database; Set up a companion robot to obtain regional information, planting information, and sales information of agricultural products, and set up fuzzy evaluation rules for agricultural products; The companion robot makes health evaluation suggestions based on fuzzy evaluation rules of agricultural products.

2. According to claim 1, a smart agricultural product traceability and health evaluation method based on Beidou grid code is characterized in that: When encoding the area where agricultural products are planted by Beidou grid code, the agricultural products are coded at the planting plot level and the planting area level.

3. According to claim 1, a smart agricultural product traceability and health evaluation method based on Beidou grid code is characterized in that: The step of performing planting plot level coding and planting area level coding on agricultural products comprises the following steps: Obtain the planting plots of agricultural products and the planting areas to which the agricultural products belong through the Beidou navigation system; The planting plots of agricultural products are Beidou grid coded, and the planting areas to which the agricultural products belong are Beidou grid coded.

4. According to claim 1, a smart agricultural product traceability and health evaluation method based on Beidou grid code is characterized in that: The step of associating the regional information, planting information and sales information of the agricultural products with the Beidou grid code comprises the following steps: Use Beidou grid codes as retrieval indexes for regional information, planting information, and sales information of agricultural products; Set up the traceability database index structure and establish the mapping relationship between the regional information, planting information and sales information of agricultural products and the Beidou grid code.

5. According to claim 1, a smart agricultural product traceability and health evaluation method based on Beidou grid code is characterized in that: The fuzzy evaluation rules for agricultural products are set, including the following steps: According to the planting information of agricultural products, the planting health evaluation factors of agricultural products are set; according to the sales information of agricultural products, the sales evaluation factors of agricultural products are set; The evaluation fuzzy set of agricultural products is set according to the evaluation factors of agricultural product planting health and sales; Agricultural products are evaluated based on their evaluation fuzzy sets.

6. According to claim 1, a smart agricultural product traceability and health evaluation method based on Beidou grid code is characterized in that: The companion robot makes health evaluation suggestions according to the fuzzy evaluation rules of agricultural products, including the following steps: Obtain planting and sales information of agricultural products, and obtain users' daily diet information; Make active daily diet recommendations to users based on their daily diet information, planting information, and sales information; receive diet recommendation requests from users, and make passive daily diet recommendations to users based on the planting information and sales information of agricultural products; The user's current diet information is obtained, and the user's current diet is evaluated based on active daily diet recommendations or passive daily diet recommendations.

7. A smart agricultural product traceability and health evaluation method based on Beidou grid code, characterized in that: It includes a first computing unit, which is used to obtain regional information, planting information and sales information of agricultural products, and encode the area where the agricultural products are planted through Beidou grid code; In the second computing unit, the user associates the regional information, planting information and sales information of the agricultural products with the Beidou grid code, and stores the regional information, planting information and sales information of the agricultural products in the traceability database; The third computing unit is used to set the companion robot to obtain regional information, planting information and sales information of agricultural products, and to set fuzzy evaluation rules for agricultural products; The fourth computing unit is used for the companion robot to make health evaluation suggestions based on the fuzzy evaluation rules of agricultural products.

8. A smart agricultural product traceability and health evaluation device based on Beidou grid code, characterized in that: The device comprises a processor and a memory; the memory is used to store program code and transmit the program code to the processor; The processor is used to execute the steps of the smart agricultural product traceability and health evaluation method based on Beidou grid code described in claims 1-6 according to the instructions in the program code.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium is used to store program code, and the program code is used to execute the steps of the smart agricultural product traceability and health evaluation method based on Beidou grid code described in claims 1-6.

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