CN114565413A - Method for monitoring resident food consumption data - Google Patents
Method for monitoring resident food consumption data Download PDFInfo
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- CN114565413A CN114565413A CN202210202951.1A CN202210202951A CN114565413A CN 114565413 A CN114565413 A CN 114565413A CN 202210202951 A CN202210202951 A CN 202210202951A CN 114565413 A CN114565413 A CN 114565413A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0201—Market modelling; Market analysis; Collecting market data
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0283—Price estimation or determination
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Abstract
The invention discloses a method for monitoring resident food consumption data, which comprises the following steps: s1, acquiring flow information and price information of each product in the food wholesale market; s2, acquiring the selling quantity and the retail price of each product in the retail shop; s3, comparing the retail price with the current retail price of the product, and determining whether the retail price increase amplitude of each product exceeds a preset price threshold; s4, comparing the retail sales volume of the products in the past year, and determining whether the retail sales volume decline of each product exceeds a sales volume preset threshold; s5, screening out products of which the retail price increase amplitude exceeds a preset price threshold value and the retail sales quantity decrease amplitude exceeds a preset sales quantity threshold value, and carrying out statistics to obtain an abnormal product list; s6, surveying the producing areas of all products in the abnormal product list, and knowing the price abnormal factors of the products; and S7, analyzing and summarizing to obtain abnormal food monitoring and analyzing data.
Description
Technical Field
The invention relates to the field of food data monitoring, in particular to a method for monitoring resident food consumption data.
Background
People take food as days, the food is necessary for normal survival of people, and the social stability is influenced to a certain extent when the food price is in a problem; in order to avoid situations of over-high price of food, people's consumption failure or difficult consumption, it is necessary to monitor the consumption data of food, so as to know the abnormal reason in time and improve the abnormal reason when the price of food is abnormal.
Disclosure of Invention
The invention aims to solve the problems and provides a method for monitoring resident food consumption data, which can analyze abnormal factors of food prices.
In order to achieve the purpose, the technical scheme of the invention is as follows:
a monitoring method for resident food consumption data comprises the following steps:
s1, collecting information of the food wholesale market in the monitoring area, and acquiring flow information and price information of each product in the food wholesale market;
s2, carrying out information acquisition on products to each retail shop according to the acquired product flow information, and acquiring the selling sales volume and retail price of each product in the retail shop;
s3, comparing the obtained retail price of each product with the retail price of the product in the past year, and determining whether the retail price increase amplitude of each product exceeds a preset price threshold value;
s4, comparing the obtained selling quantity of each product with the current year retail sales quantity of the product, and determining whether the retail sales quantity reduction amplitude of each product exceeds a sales quantity preset threshold value;
s5, screening out products of which the retail price increase amplitude exceeds a preset price threshold value and the retail sales amount decrease amplitude exceeds a preset sales amount threshold value, and counting to obtain an abnormal product list;
s6, surveying the producing areas of all products in the abnormal product list according to the flow information, and knowing the price abnormal factors of the products;
and S7, analyzing and summarizing the price abnormal factors of the product to obtain abnormal food monitoring and analyzing data.
Further, the flow information in the step S1 includes the information of the shipment origin of the product, the information of the vendor purchase, and the information of the vendor shop location.
Further, the preset price threshold in step S3 is five percent of the average value of the retail prices of the same month in the same year on the product.
Further, the preset threshold of sales in step S4 is ten percent of the average value of retail sales in the same month of the year on the product.
Further, in step S6, the price anomaly factor of the product includes abnormal yield information, abnormal transportation information, and abnormal natural disaster information.
Compared with the prior art, the invention has the advantages and positive effects that:
the flow information and the price information are acquired in the food wholesale market, so that retail shop information and food origin information of goods fed in the food wholesale market can be accurately found, then the price information and the sales information of the retail food products can be acquired and compared through the retail shop information, then the food origin is investigated and analyzed through a comparison result, and finally food price abnormal factors are obtained, the operation steps are simple and quick, the price abnormal reasons of the abnormal food products can be known in time, and the stability of the food price is effectively guaranteed; in addition, the retail price increase range and the retail sales reduction range of the food product are comprehensively compared, so that the influence degree of the food price abnormity on people is reflected, the subsequent processing operation is conveniently carried out according to the influence degree, the condition that the food price abnormity influences the life of people is further avoided, and the stability of the life of residents is ensured.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived from the embodiments of the present invention by a person skilled in the art without any creative effort, should be included in the protection scope of the present invention.
The embodiment discloses a monitoring method of resident food consumption data, which comprises the following steps:
s1, collecting information of the food wholesale market in the monitoring area, and acquiring flow information and price information of each product in the food wholesale market;
the mobile information comprises the information of the product's stocking origin, the information of the vendor's purchase and the information of the vendor's shop position;
s2, carrying out information acquisition on products to each retail shop according to the obtained product flow information, and obtaining the selling sales volume and the retail price of each product in the retail shop;
s3, comparing the obtained retail price of each product with the retail price of the product in the past year, and determining whether the retail price increase amplitude of each product exceeds a preset price threshold value;
the preset price threshold value is five percent of the average value of the retail price of the product in the same month in the last year;
s4, comparing the obtained selling sales volume of each product with the current year retail sales volume of the product, and determining whether the retail sales volume reduction range of each product exceeds a sales volume preset threshold value;
the preset sales threshold is ten percent of the average value of the retail sales of the same month in the same year of the product;
s5, screening out products of which the retail price increase amplitude exceeds a preset price threshold value and the retail sales quantity decrease amplitude exceeds a preset sales quantity threshold value, and carrying out statistics to obtain an abnormal product list;
s6, surveying the producing areas of all products in the abnormal product list according to the flow information, and knowing the price abnormal factors of the products;
the price abnormal factors of the product comprise abnormal yield information, abnormal transportation information and abnormal natural disaster information;
and S7, analyzing and summarizing the price abnormal factors of the product to obtain abnormal food monitoring and analyzing data.
The flow information and the price information are acquired in the food wholesale market, so that retail shop information and food origin information of goods fed in the food wholesale market can be accurately found, then the price information and the sales information of the retail food products can be acquired and compared through the retail shop information, then the food origin is investigated and analyzed through a comparison result, and finally food price abnormal factors are obtained, the operation steps are simple and quick, the price abnormal reasons of the abnormal food products can be known in time, and the stability of the food price is effectively guaranteed; in addition, the retail price increase range and the retail sales reduction range of the food product are comprehensively compared, so that the influence degree of the food price abnormity on people is reflected, the subsequent processing operation is conveniently carried out according to the influence degree, the condition that the food price abnormity influences the life of people is further avoided, and the stability of the life of residents is ensured.
Claims (5)
1. A monitoring method for resident food consumption data is characterized in that: the method comprises the following steps:
s1, collecting information of the food wholesale market in the monitoring area, and acquiring flow information and price information of each product in the food wholesale market;
s2, carrying out information acquisition on products to each retail shop according to the acquired product flow information, and acquiring the selling sales volume and retail price of each product in the retail shop;
s3, comparing the obtained retail price of each product with the retail price of the product in the past year, and determining whether the retail price increase amplitude of each product exceeds a preset price threshold value;
s4, comparing the obtained selling quantity of each product with the current year retail sales quantity of the product, and determining whether the retail sales quantity reduction amplitude of each product exceeds a sales quantity preset threshold value;
s5, screening out products of which the retail price increase amplitude exceeds a preset price threshold value and the retail sales quantity decrease amplitude exceeds a preset sales quantity threshold value, and carrying out statistics to obtain an abnormal product list;
s6, surveying the producing areas of all products in the abnormal product list according to the flow information, and knowing the price abnormal factors of the products;
and S7, analyzing and summarizing the price abnormal factors of the product to obtain abnormal food monitoring and analyzing data.
2. The resident food consumption data monitoring method in accordance with claim 1, wherein: the floating information in the step S1 includes the shipment origin information, the vendor purchase information, and the vendor shop location information of the product.
3. The resident food consumption data monitoring method in accordance with claim 2, wherein: the preset price threshold in step S3 is five percent of the average value of the retail prices of the same month in the last year of the product.
4. A resident food consumption data monitoring method in accordance with claim 3, wherein: the preset threshold for sales in step S4 is ten percent of the average retail sales in the same month of the year on the product.
5. The resident food consumption data monitoring method in accordance with claim 4, wherein: in step S6, the price anomaly factors of the product include abnormal yield information, abnormal transportation information, and abnormal natural disaster information.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210202951.1A CN114565413A (en) | 2022-03-03 | 2022-03-03 | Method for monitoring resident food consumption data |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210202951.1A CN114565413A (en) | 2022-03-03 | 2022-03-03 | Method for monitoring resident food consumption data |
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| Publication Number | Publication Date |
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| CN114565413A true CN114565413A (en) | 2022-05-31 |
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| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210202951.1A Pending CN114565413A (en) | 2022-03-03 | 2022-03-03 | Method for monitoring resident food consumption data |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116957751A (en) * | 2023-09-20 | 2023-10-27 | 淄博海草软件服务有限公司 | Order service abnormity monitoring method and system |
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2022
- 2022-03-03 CN CN202210202951.1A patent/CN114565413A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116957751A (en) * | 2023-09-20 | 2023-10-27 | 淄博海草软件服务有限公司 | Order service abnormity monitoring method and system |
| CN116957751B (en) * | 2023-09-20 | 2023-12-19 | 淄博海草软件服务有限公司 | Order service abnormity monitoring method and system |
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