An agricultural product fresh-keeping transportation system based on an internet of things

Abstract

This invention relates to the field of agricultural product preservation and transportation technology, and discloses an agricultural product preservation and transportation system based on the Internet of Things. The transportation system includes several packaging modules, a basic data acquisition module, a storage data acquisition module, and an analysis module. The basic data acquisition module collects basic information data of the packaging modules during the storage of agricultural products; the storage information data of the packaging modules is then collected by the data acquisition module; the analysis module analyzes the basic and storage information data of each packaging module to obtain the current status index of each packaging module, and allocates orders according to the current status level of each packaging module. Packaging modules with more mature status are prioritized for allocation to transportation points with higher sales volume and closer distance. Through this intelligent order allocation mechanism, not only can the circulation efficiency of agricultural products be effectively improved, but consumers can also be ensured to receive products of higher quality.

Description

Technical Field

[0001] This invention relates to the field of agricultural product preservation and transportation technology, and specifically to an agricultural product preservation and transportation system based on the Internet of Things. Background Technology

[0002] With the steady advancement of agricultural modernization, my country's agricultural production efficiency has significantly improved, and the output of various agricultural products has achieved a leapfrog growth. This has not only met the basic needs of the domestic market but also secured a certain share in the international market. At the same time, with the continuous improvement of residents' living standards and profound changes in consumption concepts, the market's demand for agricultural products has become increasingly prominent, exhibiting a dual trend of diversification and refinement. Consumers have raised higher requirements for the quality, taste, freshness, and safety of agricultural products. However, agricultural products still face multiple severe challenges in the circulation process from farm to table, such as insufficient cold chain logistics coverage, information asymmetry leading to supply and demand mismatch, and high transportation loss rates. These challenges significantly restrict the efficient circulation and quality improvement of agricultural products, becoming key bottlenecks restricting the high-quality development of agriculture.

[0003] In traditional agricultural product harvesting, losses such as fruit rotting are frequent due to long-distance transportation, prolonged storage, and a lack of effective preservation measures. To minimize transportation losses and ensure economic benefits, farmers often have to harvest agricultural products before they are fully ripe. While this reduces transportation risks to some extent, it also affects the final quality and taste of the agricultural products.

[0004] However, after harvesting, agricultural products are packaged and stored. The internal physiological changes and quality deterioration processes are difficult to monitor in real time with the naked eye. Farmers can only roughly assess the condition of agricultural products based on their experience with the harvest time. Therefore, once factors such as temperature fluctuations or humidity out of control occur in the storage environment, which are detrimental to the preservation of agricultural products, farmers cannot take timely and targeted measures due to the lack of intelligent monitoring and early warning systems. This can easily lead to an accelerated decline in the quality of agricultural products, or even rot and spoilage, resulting in huge economic losses and seriously affecting the sustainable development of the agricultural industry. Summary of the Invention

[0005] The purpose of this invention is to provide an Internet of Things-based agricultural product preservation and transportation system to solve the above-mentioned technical problems.

[0006] The objective of this invention can be achieved through the following technical solutions:

[0007] An Internet of Things (IoT)-based agricultural product preservation and transportation system, the transportation system comprising:

[0008] Several packaging modules for storing agricultural products;

[0009] The basic data acquisition module is used to collect basic information data of the packaging module when storing agricultural products.

[0010] A data acquisition module is provided, corresponding to a packaging module; the data acquisition module is installed in the corresponding packaging module and is used to collect the stored information data of the packaging module.

[0011] The analysis module is used to analyze the basic information data of each packaging module to obtain the initial status index of each packaging module, and then determine the initial acquisition parameters of the storage data acquisition module of each packaging module based on the initial status index. Based on the initial status index and storage information data, it analyzes to obtain the current status index and current acquisition parameters of each packaging module, and determines the current status level of each packaging module based on the current status index. Finally, it allocates orders based on the current status level of each packaging module.

[0012] As a further aspect of the present invention: the basic information data includes packaging time, origin information of agricultural products, initial weight, image information data of agricultural product packaging, and the number identifier of packaging module; the stored information data includes ambient temperature, ambient humidity, and carbon dioxide concentration of packaging module; the acquisition parameters include acquisition interval duration.

[0013] As a further aspect of the present invention: the workflow of the analysis module is as follows:

[0014] S10: The image information data is identified by the recognition unit to identify the types of agricultural products, the quantity of agricultural products, and the maturity of each agricultural product in each packaging module;

[0015] S20: The maturity of agricultural products in each packaging module is analyzed by the analysis unit to obtain the initial state index of the packaging module;

[0016] S30: The analysis unit then analyzes the initial state index to obtain the initial acquisition interval duration;

[0017] S40: Finally, the analysis unit analyzes the initial state index, the initial acquisition interval duration, and the stored information data to obtain the current state index of the packaging module, and determines the current acquisition interval duration based on the current state index.

[0018] As a further aspect of the present invention: through the formula:

[0019]

[0020] Calculate the initial state exponent R for any packaging module. is ;

[0021] Where i is the identifier of any packaging module; f(X) is the first judgment function, when X>0, f(X)=1; when X≤0, f(X)=0; R is0 The basic preset state index; N is the quantity of agricultural products in this packaging module, n∈N; S n S0 represents the maturity of the nth agricultural product within the packaging module; R0 represents the preset maturity; C1 represents the first preset constant; and C2 represents the second preset constant.

[0022] As a further aspect of the present invention: through the formula:

[0023]

[0024] Calculate the initial acquisition interval ΔT is ;

[0025] Where, ΔT is0 C1 is the initial preset acquisition interval duration; C2 is the third preset constant.

[0026] As a further aspect of the present invention: the process of obtaining the current state index and current acquisition parameters of any packaging module is as follows:

[0027] S100: By analyzing the types of agricultural products, ambient temperature, and ambient humidity of the packaging module, the environmental impact index is obtained;

[0028] S200: Analyze the carbon dioxide concentration, initial weight, and initial state index of the packaging module to obtain the current state index;

[0029] S300: The current data collection interval is obtained by analyzing the current state index and environmental impact index.

[0030] As a further aspect of the present invention: In step S100, the formula is used:

[0031]

[0032] Calculate the environmental impact index Y of this packaging module. iE ;

[0033] Among them, Y iE0 The preset environmental impact index; T s The current ambient temperature of the packaging module; m is the number of the agricultural product type inside the packaging module; T m The preset ambient temperature for the types of agricultural products within this packaging module; S s The current ambient humidity of this packaging module; S mThe preset environmental humidity is the type of agricultural product within the packaging module; γ1 is the first weighting coefficient; γ2 is the second weighting coefficient; Z1 is the first preset constant; Z2 is the second preset constant.

[0034] As a further aspect of the present invention: In step S200, the formula is used:

[0035]

[0036] Calculate the current state index R of the packaging module. ie ;

[0037] Where, μ m Q is the adjustment factor for the change in carbon dioxide concentration of agricultural products within this packaging module; ce Q represents the most recently collected carbon dioxide concentration for this packaging module. cs The carbon dioxide concentration collected for the first time after the packaging module is completed; G i This represents the initial weight of the agricultural products within the packaging module.

[0038] As a further aspect of the present invention: In step S300, the formula is used:

[0039]

[0040] Calculate the current acquisition interval ΔT of the packaging module. ie ;

[0041] Wherein, σ1 is the first weighting coefficient; σ2 is the second weighting coefficient; Z3 is the third preset constant; Z4 is the fourth preset constant; and ρ1 is the first preset adjustment coefficient.

[0042] The process for determining the current state level of any packaging module is as follows:

[0043] The current state index R of the packaging module ie Compare with preset thresholds [R1, R2];

[0044] When R ie When R1 is less than or equal to 1, the current state level of this packaging module is immature.

[0045] When R1 <R ie When R2 is less than or equal to 2, the current state level of this packaging module is mature.

[0046] When R2 <R ie At that time, the current status level of the packaging module is over-mature.

[0047] The beneficial effects of this invention are:

[0048] This invention collects basic information data from packaging modules while they store agricultural products. Then, it collects storage information data from storage data acquisition modules within the corresponding packaging modules. Finally, by analyzing the basic information data of each packaging module, an initial state index is obtained, and the initial acquisition parameters of the storage data acquisition modules for each module are determined based on this initial state index. Analysis of the initial state index and storage information data yields the current state index and current acquisition parameters for each packaging module. The current state level of each packaging module is then determined based on its current state index. Orders are allocated based on the current state level of each packaging module. This intelligent order allocation mechanism not only effectively improves the circulation efficiency of agricultural products but also ensures that consumers receive higher-quality products. Attached Figure Description

[0049] The invention will now be further described with reference to the accompanying drawings.

[0050] Figure 1 This is a system module framework diagram of one embodiment of the present invention. Detailed Implementation

[0051] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0052] Please see Figure 1 As shown, in one embodiment, an Internet of Things (IoT)-based agricultural product preservation and transportation system is provided, the transportation system comprising:

[0053] Several packaging modules for storing agricultural products;

[0054] The basic data acquisition module is used to collect basic information data of the packaging module when storing agricultural products.

[0055] A data acquisition module is provided, corresponding to a packaging module; the data acquisition module is installed in the corresponding packaging module and is used to collect the stored information data of the packaging module.

[0056] The analysis module is used to analyze the basic information data of each packaging module to obtain the initial status index of each packaging module, and then determine the initial acquisition parameters of the storage data acquisition module of each packaging module based on the initial status index. Based on the initial status index and storage information data, it analyzes to obtain the current status index and current acquisition parameters of each packaging module, and determines the current status level of each packaging module based on the current status index. Finally, it allocates orders based on the current status level of each packaging module.

[0057] Through the above technical solution, this embodiment collects basic information data of the packaging module when storing agricultural products in the packaging module through the basic data acquisition module; then, it collects storage information data of the packaging module through the storage data acquisition module set in the corresponding packaging module; finally, it obtains the initial state index of each packaging module by analyzing the basic information data of each packaging module, and then determines the initial acquisition parameters of the storage data acquisition module of each packaging module based on the initial state index of each packaging module; it obtains the current state index and current acquisition parameters of each packaging module by analyzing the initial state index and storage information data; and it determines the current state level of each packaging module based on the current state index of each packaging module; it allocates orders according to the current state level of each packaging module, so that packaging modules with more mature state are given priority to be allocated to transportation points with larger sales volume and closer distance. For packaging modules with a state level in the early stage of maturity but not yet reaching the optimal transportation state, the system will include them in a temporary queue and make dynamic adjustments based on the data collected subsequently. Through this intelligent order allocation mechanism, not only can the circulation efficiency of agricultural products be effectively improved, but consumers can also be ensured to receive products of higher quality.

[0058] In one embodiment of the present invention, the basic information data includes packaging time, origin information of agricultural products, initial weight, image information data of agricultural product packaging, and number identification of packaging module; the stored information data includes ambient temperature, ambient humidity, and carbon dioxide concentration of packaging module; the acquisition parameters include acquisition interval duration;

[0059] Through the above technical solution, this embodiment obtains image information data of agricultural products being loaded into the packaging module through an image acquisition device when the agricultural products are loaded into the packaging module; the packaging time, origin information and initial weight of the agricultural products; the method of obtaining the ambient temperature, ambient humidity and carbon dioxide concentration of the packaging module is existing technology and will not be described in detail here.

[0060] In one embodiment of the present invention, the analysis module includes an identification unit and an analysis unit. The identification unit is a trained convolutional neural network model, used to identify based on image information data, and to obtain the types of agricultural products, the quantity of agricultural products, and the maturity of each agricultural product within the packaging module.

[0061] It should be noted that the training process of the convolutional neural network model is existing technology and will not be described in detail here.

[0062] As one embodiment of the present invention, the workflow of the analysis module is as follows:

[0063] S10: The image information data is identified by the recognition unit to identify the types of agricultural products, the quantity of agricultural products, and the maturity of each agricultural product in each packaging module;

[0064] S20: The maturity of agricultural products in each packaging module is analyzed by the analysis unit to obtain the initial state index of the packaging module;

[0065] S30: The analysis unit then analyzes the initial state index to obtain the initial acquisition interval duration;

[0066] S40: Finally, the analysis unit analyzes the initial state index, the initial acquisition interval duration, and the stored information data to obtain the current state index of the packaging module, and determines the current acquisition interval duration based on the current state index.

[0067] Through the above technical solution, this embodiment first identifies the image information data through the recognition unit, identifying the types, quantities, and maturity of agricultural products in each packaging module; then, the analysis unit analyzes the maturity of agricultural products in each packaging module to obtain the initial state index of the packaging module; next, the initial collection interval is obtained based on the initial state index; finally, the analysis unit analyzes the initial state index, the initial collection interval, and the stored information data to obtain the current state index of the packaging module, and determines the current collection interval based on the current state index. This dynamic adjustment of the collection interval can significantly improve the efficiency and accuracy of data collection. Determining the initial collection interval based on the initial state index establishes a reasonable and scientific starting framework for the entire data collection process, avoiding resource waste or data loss caused by blind collection. Flexibly determining the current collection interval based on the current state index allows the system to respond in real time to changes in the state of the packaging modules.

[0068] As one embodiment of the present invention, the formula is as follows:

[0069]

[0070] Calculate the initial state exponent R for any packaging module. is ;

[0071] Where i is the identifier of any packaging module; f(X) is the first judgment function, when X>0, f(X)=1; when X≤0, f(X)=0; R is0 The basic preset state index; N is the quantity of agricultural products in this packaging module, n∈N; S n S0 represents the maturity level of the nth agricultural product within this packaging module; R0 represents the preset maturity level; C1 represents the preset standard deviation; and C2 represents the first preset constant.

[0072] Through the above technical solution, this embodiment The standard deviation of the maturity of all agricultural products within the packaging module is represented by the standard deviation of the maturity of all agricultural products within the packaging module. The larger the standard deviation of the maturity of all agricultural products within the packaging module, the higher the degree of dispersion of the maturity of agricultural products within the module, that is, the more significant the difference in maturity between different agricultural products. This means that in the packaging module, some agricultural products may be overripe, approaching or reaching the end of their optimal consumption period, while other agricultural products may be underripe and need some more time to reach their ideal consumption state. The difference between the preset standard deviation and the standard deviation of maturity of all agricultural products within this packaging module is used in the formula. In the first judgment function f(X), X refers to... Used to determine whether the preset standard deviation exceeds the standard deviation of maturity of all agricultural products within this packaging module; when When the preset standard deviation exceeds the standard deviation of maturity of all agricultural products within the packaging module, it indicates that the dispersion of maturity of all agricultural products within the packaging module is small. This represents the average maturity of all agricultural products within the packaging module. Given the same average maturity, the larger the standard deviation of maturity among all agricultural products within the packaging module, the more likely there are a small number of higher-maturity agricultural products within the module. Therefore, by... This indicates the maturity of the agricultural product in the packaging module; The difference between the maturity of the agricultural product in this packaging module and the preset maturity is the value when... When this occurs, it indicates that the maturity of the agricultural products in the packaging module exceeds the preset maturity level, therefore the initial state index R of the packaging module is [value missing]. is Greater than the basic preset state index R is0 ;when When this occurs, it indicates that the maturity of the agricultural products in the packaging module is less than the preset maturity level. Therefore, the initial state index R of the packaging module is lower. is Less than the basic preset state index R is0 ;when If the preset standard deviation does not exceed the standard deviation of maturity of all agricultural products within the packaging module, then the maturity dispersion of all agricultural products within the packaging module is large, and they cannot be directly stored and transported. They require processing by staff, such as manual sorting to remove those with significantly different maturity levels. Therefore, the initial state exponent R of the packaging module is =0;

[0073] It should be noted that the preset maturity level S0, preset standard deviation R0, first preset constant C1 and second preset constant C2 are preset values ​​obtained based on experience, and will not be described in detail here;

[0074] It should be noted that the preset maturity level S0 for agricultural products in the packaging module corresponds to the basic preset state index R. is0 Basic preset state index R is0 These are preset values, obtained based on experience, and will not be detailed here.

[0075] As one embodiment of the present invention, the formula is as follows:

[0076]

[0077] Calculate the initial acquisition interval ΔT is ;

[0078] Where, ΔT is0 C1 is the initial preset acquisition interval duration; C2 is the third preset constant.

[0079] Through the above technical solution, in this embodiment R is0 -R is The difference between the preset state index and the initial state index of the packaging module; when R is0 -R is If the value is greater than 0, it indicates that the initial state of the packaging module is not yet mature, therefore the initial acquisition interval ΔT is... is Setting a relatively long period can avoid unnecessary burden on the system due to excessively frequent data collection, while also allowing for monitoring of the changing trends of agricultural products within the packaging module to a certain extent.

[0080] It should be noted that the initial preset data collection interval ΔT is0 The third preset constant C3 is a preset value, obtained based on experience, and will not be described in detail here.

[0081] As one embodiment of the present invention, the process of obtaining the current state index and current acquisition parameters of any packaging module is as follows:

[0082] S100: By analyzing the types of agricultural products, ambient temperature, and ambient humidity of the packaging module, the environmental impact index is obtained;

[0083] S200: Analyze the carbon dioxide concentration, initial weight, and initial state index of the packaging module to obtain the current state index;

[0084] S300: The current data collection interval is obtained by analyzing the current state index and environmental impact index;

[0085] Through the above technical solution, this embodiment first analyzes the type of agricultural product, ambient temperature, and ambient humidity of the packaging module to obtain the environmental impact index; then, it analyzes the carbon dioxide concentration, initial weight, and initial state index of the packaging module to obtain the current state index; and finally, it analyzes the current state index and the environmental impact index to obtain the current collection interval. Through this multi-dimensional comprehensive consideration, the collection interval can be dynamically adjusted more scientifically and accurately according to the actual situation of the packaging module and its environment, ensuring the quality and safety of agricultural products during transportation and storage.

[0086] As one embodiment of the present invention, in step S100, the formula is:

[0087]

[0088] Calculate the environmental impact index Y of this packaging module. iE ;

[0089] Among them, Y iE0 The preset environmental impact index; T s The current ambient temperature of the packaging module; m is the number of the agricultural product type inside the packaging module; T m The preset ambient temperature for the types of agricultural products within this packaging module; S s The current ambient humidity of this packaging module; S m The preset environmental humidity for the agricultural products within this packaging module; γ1 is the first weighting coefficient; γ2 is the second weighting coefficient; Z1 is the first preset constant; Z2 is the second preset constant;

[0090] Through the above technical solution, in this embodiment T s -T m The difference between the current ambient temperature of the packaging module and the preset ambient temperature of the agricultural product type inside the packaging module; when T s -T mWhen the temperature is greater than 0, the current ambient temperature of the packaging module is higher than the preset ambient temperature for the agricultural products inside the packaging module, leading to accelerated ripening of the agricultural products. The greater the difference between the current ambient temperature of the packaging module and the preset ambient temperature for the agricultural products inside the packaging module, the higher the environmental impact index Y of the packaging module. iE The larger; when T s -T m When the temperature is less than 0, the current ambient temperature of the packaging module is lower than the preset ambient temperature for the agricultural products inside the module, resulting in slower ripening of the agricultural products. The greater the absolute value of the difference between the current ambient temperature of the packaging module and the preset ambient temperature for the agricultural products inside the module, the higher the environmental impact index Y of the packaging module. iE The smaller; S s -S m The difference between the current ambient humidity of the packaging module and the preset ambient humidity of the agricultural product type inside the packaging module; when S s -S m When the humidity level is greater than 0, the current ambient humidity of the packaging module is higher than the preset ambient humidity for the agricultural products inside the packaging module, leading to accelerated ripening of the agricultural products. The greater the difference between the current ambient humidity of the packaging module and the preset ambient humidity for the agricultural products inside the packaging module, the higher the environmental impact index Y of the packaging module. iE The larger S is; s -S m When the humidity is less than 0, the current ambient humidity of the packaging module is lower than the preset ambient humidity for the agricultural products inside the packaging module, resulting in slower ripening of the agricultural products. The greater the absolute value of the difference between the current ambient humidity of the packaging module and the preset ambient humidity for the agricultural products inside the packaging module, the higher the environmental impact index Y of the packaging module. iE The smaller;

[0091] It should be noted that the preset environmental impact index Y iE0 The first weighting coefficient γ1, the second weighting coefficient γ2, the first preset constant Z1 and the second preset constant Z2 are preset values, obtained based on experience, and will not be described in detail here.

[0092] It should be noted that the preset ambient temperature and humidity for each type of agricultural product are preset values, determined based on the type of agricultural product and obtained through experience, and will not be detailed here.

[0093] As one embodiment of the present invention, in step S200, the formula is:

[0094]

[0095] Calculate the current state index R of the packaging module. ie ;

[0096] Where, μ m Q is the adjustment factor for the change in carbon dioxide concentration of agricultural products within this packaging module; ce Q represents the most recently collected carbon dioxide concentration for this packaging module. cs The carbon dioxide concentration collected for the first time after the packaging module is completed; G i This represents the initial weight of the agricultural products within the packaging module;

[0097] Through the above technical solution, this embodiment Q ce -Q cs The difference between the most recent carbon dioxide concentration collected by the packaging module and the first carbon dioxide concentration collected after the packaging module has finished packaging. This represents the increase in carbon dioxide concentration per unit weight within the packaging module. This represents the increase in carbon dioxide concentration per unit weight of agricultural products within the packaging module; the greater the increase in carbon dioxide concentration per unit weight of agricultural products within the packaging module, the greater the change in the maturity of the agricultural products within the packaging module; therefore, the current state index R... ie Based on the initial state, the greater the degree of maturity, the higher the current state exponent R. ie The larger;

[0098] It should be noted that the adjustment coefficient for carbon dioxide concentration change of agricultural products reflects the difference in the degree of impact of the same increase in carbon dioxide concentration on different agricultural products; it is obtained based on experience and will not be elaborated here.

[0099] As one embodiment of the present invention, in step S300, the formula is:

[0100]

[0101] Calculate the current acquisition interval ΔT of the packaging module. ie ;

[0102] Wherein, σ1 is the first weighting coefficient; σ2 is the second weighting coefficient; Z3 is the third preset constant; Z4 is the fourth preset constant; and ρ1 is the first preset adjustment coefficient.

[0103] Through the above technical solution, in this embodiment R ie -R is This is the difference between the current state index and the initial state index of the packaging module. The larger the difference, the greater the change in maturity of the packaging module relative to its initial state. Therefore, the current data collection interval ΔT is... ie The smaller; Y iE -YiE0 The difference between the environmental impact index of the packaging module and the preset environmental impact index is used. The larger the difference between the environmental impact index of the packaging module and the preset environmental impact index, the more it indicates that the current environment will accelerate the ripening of agricultural products in the packaging module. Through this multi-dimensional comprehensive consideration, the collection interval can be dynamically adjusted more scientifically and accurately according to the actual situation of the packaging module and its environment, so as to ensure the quality and safety of agricultural products during transportation and storage.

[0104] It should be noted that the first weight coefficient σ1, the second weight coefficient σ2, the third preset constant Z3, the fourth preset constant Z4, and the first preset adjustment coefficient ρ1 are preset values ​​obtained based on experience, and will not be described in detail here.

[0105] As one embodiment of the present invention, the process for determining the current state level of any packaging module is as follows:

[0106] The current state index R of the packaging module ie Compare with preset thresholds [R1, R2];

[0107] When R ie When R1 is less than or equal to 1, the current state level of this packaging module is immature.

[0108] When R1 < R ie When R2 is less than or equal to 2, the current state level of this packaging module is mature.

[0109] When R2 < R ie At that time, the current status level of the packaging module is over-mature.

[0110] Through the above technical solution, in this embodiment when R ie When R1 ≤ R1, it indicates that the agricultural products in this packaging module are not yet mature and can be allocated to orders from more distant areas. This allows the agricultural products sufficient time to grow during transportation, ensuring they reach their optimal consumption condition upon arrival at the customer's location. It also allows for more efficient planning of logistics resources and improved transportation efficiency. When R1 < R ie When R2 ≤ R2, it indicates that the agricultural products in the packaging module are mature. In this case, they should be prioritized for orders in the nearest area to shorten transportation time and avoid spoilage or damage due to long-term transportation, thus maximizing the freshness and quality of the agricultural products and improving customer satisfaction. When R2 < Rie, the current status of the packaging module is over-ripe, and the agricultural products are no longer suitable for direct distribution as commodities. For such over-ripe agricultural products, an emergency handling mechanism should be activated immediately. On the one hand, nearby agricultural product processing enterprises can be contacted to quickly sell these agricultural products at a lower price for processing into jams, juices, dried goods, and other processed products, which reduces losses and realizes resource reuse.

[0111] The foregoing has provided a detailed description of one embodiment of the present invention, but this description is merely a preferred embodiment and should not be construed as limiting the scope of the invention. All equivalent variations and modifications made within the scope of the claims of this invention should still fall within the patent coverage of this invention.

Claims

1. An Internet of Things-based agricultural product preservation and transportation system, characterized in that, The transportation system includes: Several packaging modules for storing agricultural products; The basic data acquisition module is used to collect basic information data of the packaging module when storing agricultural products. A data acquisition module is provided, corresponding to a packaging module; the data acquisition module is installed in the corresponding packaging module and is used to collect the stored information data of the packaging module. The analysis module is used to analyze the basic information data of each packaging module to obtain the initial status index of each packaging module, and then determine the initial acquisition parameters of the storage data acquisition module of each packaging module based on the initial status index. Based on the initial status index and storage information data, it analyzes to obtain the current status index and current acquisition parameters of each packaging module, and determines the current status level of each packaging module based on the current status index. Finally, it allocates orders based on the current status level of each packaging module. The workflow of the analysis module is as follows: S10: The image information data is identified by the recognition unit to identify the types of agricultural products, the quantity of agricultural products, and the maturity of each agricultural product in each packaging module; S20: The maturity of agricultural products in each packaging module is analyzed by the analysis unit to obtain the initial state index of the packaging module; S30: The analysis unit then analyzes the initial state index to obtain the initial acquisition interval duration; S40: Finally, the analysis unit analyzes the initial state index, the initial acquisition interval duration, and the stored information data to obtain the current state index of the packaging module, and determines the current acquisition interval duration based on the current state index. Through the formula: ; Calculate the initial state index of any packaging module. ; in, This serves as the identification number for any packaging module; As the first judgment function, when hour, ;when hour, ; Based on the preset state index; This represents the quantity of agricultural products in the packaging module. ; For the first in this packaging module The maturity level of each agricultural product; Preset maturity level; The standard deviation is the preset value. This is the first preset constant; This is the second preset constant.

2. The agricultural product preservation and transportation system based on the Internet of Things according to claim 1, characterized in that, The basic information data includes packaging time, origin information of agricultural products, initial weight, image information data of agricultural product packaging, and the number identification of packaging module; the storage information data includes ambient temperature, ambient humidity, and carbon dioxide concentration of packaging module; the acquisition parameters include acquisition interval duration.

3. The agricultural product preservation and transportation system based on the Internet of Things according to claim 2, characterized in that, Through the formula: ; Calculate the initial acquisition interval duration ; in, This is the initial preset data collection interval duration; This is the third preset constant.

4. The agricultural product preservation and transportation system based on the Internet of Things according to claim 3, characterized in that, The process of obtaining the current state index and current acquisition parameters of any packaging module is as follows: S100: By analyzing the types of agricultural products, ambient temperature, and ambient humidity of the packaging module, the environmental impact index is obtained; S200: Analyze the carbon dioxide concentration, initial weight, and initial state index of the packaging module to obtain the current state index; S300: The current data collection interval is obtained by analyzing the current state index and environmental impact index.

5. The Internet of Things-based agricultural product preservation and transportation system according to claim 4, characterized in that, In step S100, the formula is used: ; Calculate the environmental impact index of this packaging module. ; in, The preset environmental impact index; The current ambient temperature of the packaging module; This refers to the number of the agricultural product type within this packaging module; The preset ambient temperature for the types of agricultural products within this packaging module; The current ambient humidity of the packaging module; The preset ambient humidity for the types of agricultural products within this packaging module; The first weighting coefficient; This is the second weighting coefficient; This is the first preset constant; This is the second preset constant.

6. The agricultural product preservation and transportation system based on the Internet of Things according to claim 5, characterized in that, In step S200, the formula is used: ; Calculate the current state index of the packaging module. ; in, Adjustment coefficient for carbon dioxide concentration variation of agricultural products within this packaging module; This refers to the most recently collected carbon dioxide concentration for this packaging module; The carbon dioxide concentration collected for the first time after the packaging module is completed; This represents the initial weight of the agricultural products within the packaging module.

7. The Internet of Things-based agricultural product preservation and transportation system according to claim 6, characterized in that, In step S300, the formula is used: ; Calculate the current data collection interval of the packaging module. ; in, This is the first weighting coefficient; This is the second weighting coefficient; This is the third preset constant; This is the fourth preset constant; This is the first preset adjustment coefficient.

8. The agricultural product preservation and transportation system based on the Internet of Things according to claim 7, characterized in that, The process for determining the current state level of any packaging module is as follows: The current status index of the packaging module With preset threshold Compare; when At that time, the current status level of the packaging module is immature; when At that time, the current status level of the packaging module is mature; when At that time, the current status level of the packaging module is over-mature.

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