Food price early warning method and device and storage medium
By calculating the actual change rate of food prices and setting a multi-level early warning threshold, the existing food price warning system has solved the problem of insufficient inflation consideration and simple analysis methods, and the accuracy and efficiency of early warning are improved.
Patent Information
- Application Number
- CN202510064623.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-01-15
- Publication Date
- 2025-05-13
AI Technical Summary
The existing food price warning system lacks consideration for inflation. It uses simple statistical analysis methods to make it difficult to dig deep into data, resulting in inaccurate warning results, and lacks intelligent data processing and analysis functions, which are less efficient.
By obtaining the current prices and year-on-year prices of multiple categories of food, calculating the actual price change rate of each category of food, eliminating the impact of inflation, and setting a multi-level warning threshold for each category of food, automatically determining whether the warning conditions are met, and sending warning information to the notification receiving terminal.
It improves the accuracy and efficiency of food price warnings, can understand food price fluctuations more comprehensively, eliminates inflation interference, and achieves differentiated warnings without manual intervention, which improves the efficiency of early warning judgments.
Smart Images
Figure CN119991189A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of data analysis technology, and in particular to a food price early warning method, device and storage medium. Background Art
[0002] In modern society, food price fluctuations have a significant impact on economic stability and public life. As an important economic monitoring tool, the food price early warning system can detect abnormal price fluctuations in a timely manner, provide decision-making basis for governments and enterprises, and thus maintain market stability and consumer interests.
[0003] The existing food price early warning system mainly collects price data manually in the market, and then conducts simple statistical analysis to determine whether to issue an early warning. This food price early warning system has some shortcomings, which are mainly reflected in the following aspects:
[0004] 1. The existing food price early warning system often fails to take into account the impact of inflation on prices, which makes the early warning results easily affected by inflation and unable to accurately reflect the actual changes in food prices, thus affecting the accuracy of the early warning.
[0005] 2. The existing food price early warning system uses simple statistical analysis methods, such as calculating the average price and price fluctuation range, etc. It lacks complex data processing and analysis technology, making it difficult to conduct in-depth data mining, resulting in inaccurate early warning results.
[0006] 3. The existing food price early warning system is mainly manually operated and lacks intelligent data processing and analysis functions. It requires a lot of manpower and has low efficiency. Summary of the invention
[0007] The present invention provides a food price early warning method, device and storage medium, which are used to solve at least one of the above technical problems.
[0008] The present invention adopts the following technical solutions:
[0009] In a first aspect, the present invention provides a food price early warning method, the method comprising: obtaining current prices and year-on-year prices corresponding to multiple categories of food, the current prices at least including daily average prices and weekly average prices, and the year-on-year prices are the current prices of each category of food in historical time; calculating the actual price change rate corresponding to each category of food according to the annual inflation rate, the current prices and the year-on-year prices, the actual price change rate is used to indicate the change in food prices after eliminating the impact of the inflation rate, the actual price change rate at least including daily average price change rate and weekly average price change rate; setting corresponding multi-level early warning thresholds for each category of food; judging whether each category of food meets the preset early warning conditions according to the actual price change rates corresponding to each category of food and the corresponding multi-level early warning thresholds; if so, sending early warning information to a preset notification receiving terminal.
[0010] In a feasible implementation, the actual price change rate is calculated by the following formula:
[0011] F(t)=((t)-((t-1)*(1+))*100% / (t-1); where F(t) is the actual price change rate, P(t) is the current price, P(t-1) is the year-on-year price, and Ct is the annual inflation rate.
[0012] In a feasible implementation, determining whether each category of food meets the preset warning conditions includes: determining one by one whether each category of food meets the preset warning conditions; the preset warning conditions include at least one of the following: the daily average price change rate exceeds the third-level warning threshold for 7 consecutive days, the daily average price change rate exceeds the second-level warning threshold for 5 consecutive days, the daily average price change rate exceeds the first-level warning threshold for 3 consecutive days, the weekly average price change rate exceeds the third-level warning threshold for 2 consecutive weeks, the weekly average price change rate exceeds the second-level warning threshold, and the weekly average price change rate exceeds the first-level warning threshold.
[0013] In a feasible implementation, the method also includes: if the classification basis of multiple categories of food is the major category of food, then setting corresponding multi-level warning thresholds for each category of food, including: setting corresponding three-level warning thresholds for each category of food, wherein the third-level, second-level, and first-level warning thresholds are: grain thresholds: ±10%, ±20%, ±30%, edible oil thresholds: ±20%, ±40%, ±60%, meat thresholds: ±30%, ±50%, ±70%, poultry thresholds: ±40%, ±60%, ±80%, egg thresholds: ±40%, ±60%, ±80%, vegetable thresholds: ±50%, ±70%, ±90%, aquatic product thresholds: ±30%, ±50%, ±70%, fruit thresholds: ±30%, ±50%, ±70%, salt thresholds: ±10%, ±20%, ±30%, milk thresholds: ±10%, ±20%, ±30%.
[0014] In a feasible implementation, obtaining current prices corresponding to multiple categories of food includes: obtaining prices corresponding to multiple specific foods from multiple channels, the multiple channels at least including agricultural product wholesale markets and online sales platforms; determining daily average prices corresponding to multiple categories of food based on the prices corresponding to the multiple specific foods, and storing the daily average prices corresponding to the multiple categories of food in a food price database; calculating weekly average prices corresponding to multiple categories of food based on the daily average prices corresponding to the multiple categories of food stored in the food price database.
[0015] In a feasible implementation, the daily average prices corresponding to multiple categories of food are determined based on the prices corresponding to multiple specific foods, including: determining the specific foods included in each category of food; performing weighted averaging on the prices of the specific foods included in each category of food to obtain the daily average prices corresponding to each category of food, and the weights corresponding to the weighted average processing are determined according to the sales volume of the specific foods.
[0016] In a feasible implementation, sending warning information to a preset notification receiving terminal includes: generating warning information based on the warning conditions met by each category of food, the warning information at least including the category name of each category of food and the warning conditions met by each category of food; sending warning information to the preset notification receiving terminal via system station mail and text messages.
[0017] In a feasible implementation, after sending the warning information to a preset notification receiving terminal, the method also includes: collecting feedback data corresponding to the warning information for multiple days, the feedback data at least including the latest daily average price change rate of the food category corresponding to the warning information; adjusting the multi-level warning thresholds and preset warning conditions according to the latest daily average price change rate.
[0018] In a second aspect, the present invention also provides a food price warning device, which specifically includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor so that the at least one processor can execute a food price warning method as described in any of the above embodiments.
[0019] In a third aspect, the present invention further provides a non-volatile computer storage medium having computer executable instructions stored thereon, wherein the computer executable instructions are configured to execute a food price warning method as in any of the above-mentioned embodiments.
[0020] The food price early warning method, device and storage medium provided by the present invention have the following beneficial effects:
[0021] 1. By obtaining the daily and weekly average prices of food, we can fully understand the fluctuations of food prices from different time scales, avoid the one-sidedness that may be caused by single time scale data, and provide a data basis for improving the accuracy of early warning. By introducing the annual inflation rate and calculating the actual price change rate of each category of food, we can eliminate the interference of inflation on prices and reflect the changes in food prices under actual purchasing power, which is conducive to improving the accuracy of price early warning. By setting corresponding multi-level early warning thresholds for each category of food, differentiated early warnings can be made according to the price fluctuation characteristics and market sensitivity of different foods. By automatically comparing the actual price change rate of each category of food with the multi-level early warning threshold according to the preset judgment rules, it is determined whether it meets the early warning conditions without manual intervention, which improves the efficiency of early warning judgment.
[0022] 2. By obtaining price data of specific foods from multiple channels such as agricultural product wholesale markets and online sales platforms, food price information can be covered more comprehensively, ensuring the diversity and representativeness of data sources. At the same time, by using the weighted average processing method, determining the weight according to the sales volume of specific foods, and calculating the daily average price of each category of food, it can more accurately reflect the actual level and market trend of food prices, avoid deviations caused by a single data source or simple averaging method, and thus provide a more reliable data basis for food price warnings, and improve the accuracy and effectiveness of warnings.
[0023] 3. The adaptability and accuracy of the food price early warning system are enhanced by continuously collecting feedback data and dynamically adjusting the multi-level early warning thresholds and early warning conditions based on the latest daily average price change rate. BRIEF DESCRIPTION OF THE DRAWINGS
[0024] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. In the drawings:
[0025] Figure 1 A flow chart of a food price early warning method provided by the present invention;
[0026] Figure 2 This is a structural schematic diagram of a food price early warning device provided by the present invention. DETAILED DESCRIPTION
[0027] In order to enable those skilled in the art to better understand the technical solutions in the present invention, the technical solutions in the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.
[0028] The method of the present invention is described in detail below with reference to the accompanying drawings.
[0029] Figure 1 A flow chart of a food price early warning method provided by the present invention, such as Figure 1 As shown, the method in the present invention at least includes the following execution steps:
[0030] Step 101: Obtain the current prices and year-on-year prices corresponding to multiple categories of food.
[0031] The current price here refers to the price of each category of food at the current time point or time period. Specifically, it includes the daily average price and the weekly average price. The year-on-year price here refers to the current price of each category of food in the historical time, specifically the current price of each category of food in the previous year.
[0032] Specifically, first, the prices corresponding to multiple specific foods are obtained from multiple channels, where the multiple channels at least include agricultural product wholesale markets and online sales platforms. For agricultural product wholesale markets that have established electronic trading systems or data management systems, wholesale price data of food can be automatically obtained by connecting with the data interface of the market. For other agricultural product wholesale markets, price information of products sold in wholesale markets can be obtained by communicating with the managers of wholesale markets. For online sales platforms, information such as the prices of food sold on the platform can be obtained through API interfaces or by using crawler technology. By obtaining food price data from multiple channels, including agricultural product wholesale markets and online sales platforms, it is possible to fully cover all sources of food prices, ensure the comprehensiveness and diversity of data, and provide more comprehensive basic data support for subsequent price analysis and early warning. By connecting with the data interface of agricultural product wholesale markets and using automated means such as web crawler technology, real-time collection and updating of food price data can be achieved. This enables the food price database to reflect price changes in the market in a timely manner, provide real-time data support for food price early warnings, and help to promptly discover abnormal price fluctuations and take corresponding measures.
[0033] After obtaining the prices of multiple specific foods, it is necessary to classify each specific food into different food categories, that is, to determine the specific foods included in each category. The daily average price corresponding to each type of food can be determined by simply calculating the average price of the specific foods included in each type of food. However, this calculation method is rough and prone to large errors. Therefore, the daily average price corresponding to each type of food can be calculated by combining the sales volume of specific foods and using a weighted average method, where the weight is determined according to the sales volume of specific foods.
[0034] After determining the daily average price of each category of food, the price data is stored in the food price database. The database stores the daily average price of food in the past, so the daily average price of the past 7 days can be extracted from the food price database to calculate the weekly average price corresponding to each category of food. The relevant data of the previous year can also be extracted from the food price database to determine the year-on-year price. Through the query and statistical functions of the database, the daily average price, weekly average price and year-on-year price of various types of food can be easily extracted to provide integrated data support for calculating the actual price change rate and conducting price warnings, avoiding the problems of data dispersion and repeated processing, and improving the efficiency and accuracy of data processing.
[0035] Step 102: Calculate the actual price change rate of each category of food based on the annual inflation rate, current price and year-on-year price.
[0036] The annual inflation rate here can be obtained from the National Bureau of Statistics or other third-party data platforms.
[0037] The formula for determining the actual price change rate for each category of food is:
[0038] F(t)=(P(t)-(P(t-1)*(1+Ct)))*100% / P(t-1);
[0039] Among them, F(t) is the actual price change rate, P(t) is the current price, P(t-1) is the year-on-year price, and C t is the annual inflation rate. The P(t-1)*(1+Ct) in the formula means adjusting the price of the same period last year, P(t-1), according to the inflation rate Ct to get the price that should be reached this year if the price last year increases according to the inflation rate. The (P(t)-(P(t-1)*(1+Ct)) in the formula means the difference between the current price and the inflation-adjusted price, which reflects the actual change in food prices after eliminating the impact of inflation.
[0040] This formula eliminates the impact of inflation on food price changes by taking the inflation rate into account, so that the price change rate can better reflect the actual fluctuations in food prices. It can then more accurately determine whether there are abnormal fluctuations in food prices, thereby improving the accuracy of early warning.
[0041] Step 103: Set corresponding multi-level warning thresholds for each category of food.
[0042] The reason for setting multiple levels of warning thresholds is that such settings can improve the sensitivity and accuracy of the warning system, so that the system can respond in different levels according to the degree of price changes. For example, when the price fluctuates slightly, the third-level warning is triggered to alert the relevant departments to pay attention; when the price fluctuates greatly, a higher-level warning is triggered, prompting the relevant departments to take prompt measures.
[0043] In an example, multiple categories of food are classified based on major food categories, and corresponding three-level warning thresholds are set for each category of food, where the third-level, second-level, and first-level warning thresholds are: grain thresholds: ±10%, ±20%, ±30%, edible oil thresholds: ±20%, ±40%, ±60%, meat thresholds: ±30%, ±50%, ±70%, poultry thresholds: ±40%, ±60%, ±80%, egg thresholds: ±40%, ±60%, ±80%, vegetable thresholds: ±50%, ±70%, ±90%, aquatic product thresholds: ±30%, ±50%, ±70%, fruit thresholds: ±30%, ±50%, ±70%, salt thresholds: ±10%, ±20%, ±30%, milk thresholds: ±10%, ±20%, ±30%.
[0044] Step 104: Determine whether each category of food meets the preset warning conditions based on the actual price change rate corresponding to each category of food and the corresponding multi-level warning threshold.
[0045] Specifically, determine one by one whether each category of food meets the preset warning conditions. The preset warning conditions include at least one of the following: the daily average price change rate exceeds the third-level warning threshold for 7 consecutive days, the daily average price change rate exceeds the second-level warning threshold for 5 consecutive days, the daily average price change rate exceeds the first-level warning threshold for 3 consecutive days, the weekly average price change rate exceeds the third-level warning threshold for 2 consecutive weeks, the weekly average price change rate exceeds the second-level warning threshold, and the weekly average price change rate exceeds the first-level warning threshold.
[0046] In one example, the following program is used to determine whether the daily average price change rate of each category of food meets the preset warning conditions:
[0047] public Boolean warn(){
[0048] Boolean flag7 = true;
[0049] Boolean flag5 = true;
[0050] Boolean flag3 = true;
[0051] / / Daily average price in the last 7 periods compared to the same period last year
[0052] List latest7Day;
[0053] / / The average daily price in the last 5 periods compared with the same period last year
[0054] List latest5Day;
[0055] / / Daily average price in the last three periods compared to the same period last year
[0056] List latest3Day;
[0057] for(int i=0;i<7;i++){
[0058] if(-10 <latest7Day[i]<10){
[0059] flag7 = false;
[0060] break;
[0061] }
[0062] }
[0063] for(int i=0;i<5;i++){
[0064] if(-20 <latest5Day[i]<20){
[0065] flag5 = false;
[0066] break;
[0067] }
[0068] }
[0069] for(int i=0;i<3;i++){
[0070] if(-30 <latest3Day[i]<30){
[0071] flag3 = false;
[0072] break;
[0073] }
[0074] }
[0075] return flag7||flag5||flag3;
[0076] Step 105: If yes, send warning information to the preset notification receiving terminal.
[0077] Specifically, first, the warning information is generated according to the warning conditions that each category of food meets, and the warning information at least includes the category name of each category of food and the warning conditions that each category of food meets. Then, the warning information is sent to the preset notification receiving terminal through the system station letter and SMS.
[0078] In a feasible implementation, since the warning threshold and warning conditions in the food price warning method are not fixed, but need to be appropriately adjusted according to the actual situation. Therefore, after the preset notification receiving terminal sends the warning information, the feedback data corresponding to the warning information is collected for several days, and the feedback data at least includes the latest daily average price change rate of the food category corresponding to the warning information. Then, the multi-level warning threshold and the preset warning conditions are adjusted according to the latest daily average price change rate.
[0079] Based on the same inventive concept, the present invention also provides a food price early warning device, the structure of which is as follows: Figure 2 shown.
[0080] Figure 2 This is a schematic diagram of the structure of a food price early warning device provided by the present invention. Figure 2 As shown, the food price warning device 200 in the present invention specifically includes: at least one processor 201; and a memory 203 that is communicatively connected to the at least one processor (connected via a bus 202); wherein the memory 203 stores instructions that can be executed by the at least one processor 201, so that the at least one processor 201 can execute a food price warning method as described in the above embodiment.
[0081] In one or more possible implementations of the present invention, the aforementioned processor is used to execute, obtain the current prices and year-on-year prices corresponding to multiple categories of food; calculate the actual price change rate corresponding to each category of food based on the annual inflation rate, current prices and year-on-year prices; set corresponding multi-level warning thresholds for each category of food; determine whether each category of food meets the preset warning conditions based on the actual price change rate corresponding to each category of food and the corresponding multi-level warning thresholds; if so, send warning information to a preset notification receiving terminal.
[0082] In addition, the present invention also provides a non-volatile computer storage medium storing computer executable instructions, wherein the computer executable instructions are configured to be able to execute a food price warning method as described in any one of the above embodiments.
[0083] In one or more possible implementations of the present invention, the aforementioned computer executable instructions are configured to be executed to obtain the current prices and year-on-year prices corresponding to multiple categories of food; calculate the actual price change rate corresponding to each category of food based on the annual inflation rate, the current price and the year-on-year price; set a corresponding multi-level warning threshold for each category of food; determine whether each category of food meets the preset warning conditions based on the actual price change rate corresponding to each category of food and the corresponding multi-level warning threshold; if so, send a warning message to a preset notification receiving terminal.
[0084] Each embodiment of the present invention is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the IoT device and medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiments.
[0085] The system and medium provided by the present invention correspond one-to-one to the method, and therefore, the system and medium also have similar beneficial technical effects to the corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the system and medium will not be repeated here.
[0086] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.
[0087] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.
[0088] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.
[0089] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.
[0090] The above are only embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims
1. A food price early warning method, characterized in that: The method comprises: Obtaining the current prices and year-on-year prices corresponding to multiple categories of food, respectively, wherein the current prices include at least the daily average price and the weekly average price, and the year-on-year prices are the current prices of each category of food in historical time; Calculate the actual price change rate corresponding to each category of food according to the annual inflation rate, the current price and the year-on-year price, the actual price change rate is used to indicate the change in food prices after eliminating the impact of the inflation rate, and the actual price change rate at least includes the daily average price change rate and the weekly average price change rate; Set corresponding multi-level warning thresholds for each category of food; According to the actual price change rate of each category of food and the corresponding multi-level warning threshold, it is judged whether each category of food meets the preset warning conditions; If so, an early warning message is sent to the preset notification receiving terminal.
2. A food price early warning method according to claim 1, characterized in that: The actual price change rate is calculated by the following formula: F(t)=(P(t)-(P(t-1)*(1+C t )))*100% / P(t-1); Wherein, F(t) is the actual price change rate, P(t) is the current price, P(t-1) is the year-on-year price, C t is the inflation rate for the stated year.
3. A food price early warning method according to claim 1, characterized in that: Determine whether each category of food meets the preset warning conditions, including: Determine whether each category of food meets the preset warning conditions one by one; The preset warning conditions include at least one of the following: the daily average price change rate exceeds the third-level warning threshold for 7 consecutive days, the daily average price change rate exceeds the second-level warning threshold for 5 consecutive days, the daily average price change rate exceeds the first-level warning threshold for 3 consecutive days, the weekly average price change rate exceeds the third-level warning threshold for 2 consecutive weeks, the weekly average price change rate exceeds the second-level warning threshold, and the weekly average price change rate exceeds the first-level warning threshold.
4. A food price early warning method according to claim 1, characterized in that: The method further comprises: If the classification basis of the multiple categories of food is the major food category, a corresponding multi-level warning threshold is set for each category of food, including: Corresponding three-level warning thresholds are set for each category of food, among which the third, second and first level warning thresholds are: grain thresholds: ±10%, ±20%, ±30%; edible oil thresholds: ±20%, ±40%, ±60%; meat thresholds: ±30%, ±50%, ±70%; poultry thresholds: ±40%, ±60%, ±80%; egg thresholds: ±40%, ±60%, ±80%; vegetable thresholds: ±50%, ±70%, ±90%; aquatic product thresholds: ±30%, ±50%, ±70%; fruit thresholds: ±30%, ±50%, ±70%; salt thresholds: ±10%, ±20%, ±30%; milk thresholds: ±10%, ±20%, ±30%.
5. A food price early warning method according to claim 1, characterized in that: The obtaining of current prices corresponding to multiple categories of food includes: Obtaining prices corresponding to a plurality of specific foods from a plurality of channels, wherein the plurality of channels at least include a wholesale market for agricultural products and an online sales platform; Determine the daily average prices corresponding to the multiple categories of food according to the prices corresponding to the multiple specific foods, and store the daily average prices corresponding to the multiple categories of food in a food price database; The weekly average prices corresponding to the multiple categories of food are calculated according to the daily average prices corresponding to the multiple categories of food stored in the food price database.
6. A food price early warning method according to claim 5, characterized in that: Determining the daily average prices corresponding to the multiple categories of food according to the prices corresponding to the multiple specific foods includes: Identify the specific foods included in each food category; The prices of specific foods included in each category of food are weighted averaged to obtain the daily average price corresponding to each category of food, and the weight corresponding to the weighted average processing is determined according to the sales volume of the specific food.
7. A food price early warning method according to claim 1, characterized in that: The sending of warning information to a preset notification receiving terminal includes: Generate the warning information according to the warning conditions met by the various categories of food, the warning information at least including the category name of the various categories of food and the warning conditions met by the various categories of food; The warning information is sent to the preset notification receiving terminal through the system station message and SMS.
8. A food price early warning method according to claim 1, characterized in that: After sending the warning information to the preset notification receiving terminal, the method further includes: Collecting feedback data corresponding to the warning information for multiple days, wherein the feedback data at least includes the latest daily average price change rate of the food category corresponding to the warning information; The multi-level warning thresholds and preset warning conditions are adjusted according to the latest daily average price change rate.
9. A food price early warning device, characterized in that: The device specifically includes: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, so that the at least one processor can execute a food price early warning method according to any one of claims 1-8.
10. A non-volatile computer storage medium having computer executable instructions stored thereon, characterized in that: The computer executable instructions are configured to execute a food price early warning method according to any one of claims 1-8.