CN111210377A - Network meal ordering supervision system and method based on cloud computing - Google Patents
Network meal ordering supervision system and method based on cloud computing Download PDFInfo
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Abstract
The invention provides a network meal ordering supervision system and method based on cloud computing. The system comprises: the data acquisition module is used for acquiring basic information data of online catering merchants and performing multi-point storage in a cloud database; the data comparison module is used for comparing the acquired basic information data of the online catering commercial tenant with the information data stored in the existing business cloud database; the data analysis module is used for analyzing suspicious matters of the data and adding the merchants with the suspicious matters into a blacklist based on the output result of the comparison module; and the data display module is used for displaying the overall situation of the network ordering supervision work in a multi-dimensional way. The system of the invention has different definitions for violation types aiming at each province, and can flexibly adjust violation models. Aiming at common pain points of online restaurants at the current stage, the method effectively controls the behaviors of certificate non-disclosure, one certificate with multiple purposes, false certificate and the like, forms full-chain closing management and control, and achieves effective and efficient supervision.
Description
Technical Field
The invention belongs to the field of food safety management, and particularly relates to a cloud computing-based online meal ordering supervision system and method.
Background
People eat as the day, and eating is just needed for people. With the increasingly prominent 'house economy' and 'lazy economy' of the Internet, the network ordering and take-away come to the end, the demand of lazy people is met, and the problem of eating by busy people is solved. China has nearly four networking people to use the network takeout service, and the takeout market has huge user scale. The scale of Chinese online catering takeaway users in 2017 reaches 3.05 hundred million people, and in 2018, the scale of Chinese online catering takeaway users reaches 3.55 hundred million people.
The rapid growth of the network ordering industry brings convenience to the life of people and brings problems. Such as: the third party platform is not in place to be responsible for closing the online restaurants, so that some 'three-nothing' restaurants are opened on the network. The online catering enterprise has limited operation management level, simple and crude operation conditions and hidden danger on food safety, and the online catering supervision is an important component of food safety management informatization and is used for food safety supervision departments to realize supervision and management on main bodies of online catering enterprises in jurisdictions and service behaviors of the main bodies.
In the face of massive network meal ordering data, how to realize effective supervision and timely monitoring of network meal ordering becomes an important problem for food safety management departments. Therefore, a method for supervising network ordering based on cloud computing technology is urgently needed in the field.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides a novel cloud computing-based online meal ordering supervision method which is of great significance in key monitoring, guaranteeing online meal ordering food safety and improving the risk prediction and identification capability of supervision departments on online meal delivery.
According to one aspect of the invention, a cloud computing-based network order supervision system is provided, which comprises:
the data acquisition module is used for acquiring basic information data of online catering merchants and performing multi-point storage in a cloud database;
the data comparison module is used for comparing the acquired basic information data of the online catering commercial tenant with the information data stored in the existing business cloud database;
the data analysis module is used for analyzing suspicious matters of the data and adding the merchants with the suspicious matters into a blacklist based on the output result of the comparison module;
and the data display module is used for displaying the overall situation of the network ordering supervision work in a multi-dimensional way.
Furthermore, the data acquisition module acquires business licenses, license information and operation information of online catering merchants through a crawler technology and an OCR (optical character recognition) technology.
Furthermore, the data comparison module compares the business license, license information and license service life of the online catering merchant with information in a business license cloud database and a license cloud database in the existing business cloud database, and judges whether suspicious matters exist or not through comparison.
Further, the data analysis module also performs statistical analysis, and determines a key monitoring area and a key monitoring event through the statistical analysis of the conventional data.
Furthermore, the data comparison module calls policy violation models of different provinces, cities and districts to analyze suspicious matters, so that violation items of different provinces, cities and districts are determined.
Furthermore, the analysis of suspicious items is mainly divided into false business license, false license, one-card multi-purpose and super-validity item analysis.
Further, a business license cloud database in the business cloud database is in butt joint with a market supervision system and a public security system database in provinces, cities and regions; and the license cloud database is in butt joint with the databases of the industrial and commercial systems and the market supervision systems in provinces, cities and regions.
According to another aspect of the invention, a cloud computing-based network order supervision method is provided, and the method comprises the following steps:
acquiring basic information data of online catering merchants, and performing multi-point storage in a cloud database;
comparing the acquired basic information data of the online catering commercial tenant with information data stored in an existing business cloud database;
based on the output result of the comparison module, performing suspicious item analysis on the data, and adding the commercial tenant with the suspicious items into a blacklist;
and displaying the global situation of network ordering supervision work in a multidimensional way.
Further, business license and license information of the online catering merchant and operation information of the online catering merchant are obtained through a crawler technology and an OCR recognition technology: health certificate information of the workers and the permitted operation range;
and acquiring the name, the telephone, the address, the score and the monthly sales volume of the merchant through the platform registration database.
Furthermore, aiming at policy templates of different provinces, cities and districts, a policy violation model corresponding to the provinces, the cities and the districts is called, according to the output result of the comparison module, a false business license, a false license, a single-card multi-purpose merchant with a more than effective period are added into a blacklist, and a rectification notification is sent.
The system of the invention has different definitions for violation types of each province, and can flexibly adjust violation models according to each province. Aiming at common pain points of online restaurants at the current stage, the method effectively controls the behaviors of certificate non-disclosure, one certificate with multiple purposes, false certificate and the like, forms full-chain closing management and control, and achieves effective and efficient supervision.
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The above and other objects, features and advantages of the present disclosure will become more apparent by describing in greater detail exemplary embodiments thereof with reference to the attached drawings, in which like reference numerals generally represent like parts throughout.
Fig. 1 is a flowchart of a cloud-computing-based online meal order supervision method according to an embodiment of the present invention.
Fig. 2 is a functional diagram of a cloud-computing-based network meal ordering management system according to an embodiment of the present invention.
Detailed Description
Preferred embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While the preferred embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
The supervision of the network ordering is an important component of food safety management informatization, and is used for food safety supervision departments to realize supervision and management of network ordering enterprises and service behaviors thereof in jurisdictions. The invention aims to solve the problems that the definition of violation types is different in each province, an algorithm model cannot be flexibly adjusted, and the problems that the certificate of an online restaurant is not disclosed, the certificate has multiple purposes, a false certificate and the like. The method has great significance for key monitoring, guaranteeing food safety of online ordering and improving monitoring and identification capability of a supervision department on online food delivery risks. The food safety of online meal ordering people is guaranteed to a certain extent, the services such as merchant star level reference and the like are provided for the public, and the method has very important significance in the aspects of social service and healthy diet.
As shown in fig. 1, the present disclosure proposes a cloud computing-based network order supervision method, which includes:
acquiring basic information data of online catering merchants, and performing multi-point storage in a cloud database;
comparing the acquired basic information data of the online catering commercial tenant with information data stored in an existing business cloud database;
based on the output result of the comparison module, performing suspicious item analysis on the data, and adding the commercial tenant with the suspicious items into a blacklist;
and displaying the global situation of network ordering supervision work in a multidimensional way.
Firstly, business license and license information of online catering merchants and operation information of the online catering merchants are obtained through a crawler technology and an OCR recognition technology, such as: health certificate information of employees, permitted operation scope, and the like. And acquiring basic information such as merchant names, telephones, merchant addresses, scores, monthly sales and the like through the platform registration database. And storing the acquired data into a cloud database for multi-point storage by using a cloud computing technology.
And comparing the acquired merchant license information and the license service life with information in a business license cloud database and a license cloud database in the existing business cloud database. Wherein the business license cloud database in the business cloud database is in butt joint with the market supervision system of province, city and district and the database of the public security system. The license database is connected with the databases of the industrial and commercial systems and the market supervision systems in provinces, cities and districts. Whether the problems of no-certificate operation, overdue certificate, one certificate with multiple stores and one store with multiple certificates exist is judged through multipoint comparison.
And calling policy violation models corresponding to the province, the city and the district according to the policy templates of different provinces, cities and districts. And analyzing suspicious matters according to the comparison result. The suspicious event analysis is mainly divided into false business license, false license, one-card multi-purpose, super-validity event analysis and the like, and the specific events depend on policy violation models corresponding to provinces, cities and regions. Through analysis, the merchants with false business licenses, false licenses, multiple purposes and a super validity period are added into a blacklist, and a rectification notice is sent out.
Statistical analysis was also performed. For conventional data, each platform orders the number of commercial tenants on the internet, and performs statistical analysis on distribution conditions of provinces, cities and counties in the district, so as to form key monitoring area positioning, perform key monitoring on areas with concentrated commercial tenants, and effectively prevent large-scale regional events. The online ordering of key units such as schools is marked, and key supervision is performed on merchants providing online ordering for schools. The tracking and feedback service function of the key events is realized by tracking the key events, calling key event data, analyzing the key event data and feeding back the key data. The method is characterized in that information of each main link of a key event is recorded in real time, the latest dynamic state is automatically updated, data such as the root of the event occurrence, the event dynamic state, the event influence, public opinion reflection and the like are recorded in a full chain, comparison, analysis and research and judgment are carried out through multiple visual angles and multiple dimensions, and a certain key event is timely fed back to relevant departments by combining multiple factors.
And finally, displaying the overall situation of the network ordering supervision work in a visual mode in a multi-dimension mode. For example, the number of commercial tenants in provinces, cities and counties in the jurisdiction can be collected, the generated various supervision data can be deeply integrated and analyzed, various conditions such as supervision objects, supervision enforcement, time tracking, risk early warning and the like can be visually displayed in various modes such as a graph and a table, and the overall situation of supervision work can be represented in multiple dimensions.
Fig. 2 is a functional diagram of a cloud computing-based network order supervision system according to an embodiment of the present invention, and as shown in fig. 2, the network order supervision system includes:
the data acquisition module is used for acquiring basic information data of online catering merchants and performing multi-point storage in a cloud database;
the data comparison module is used for comparing the acquired basic information data of the online catering commercial tenant with the information data stored in the existing business cloud database;
the data analysis module is used for analyzing suspicious matters of the data and adding the merchants with the suspicious matters into a blacklist based on the output result of the comparison module;
and the data display module is used for displaying the overall situation of the network ordering supervision work in a multi-dimensional way.
The data acquisition module (data crawling and recognition module) acquires business licenses, license information and operation information of online catering merchants by a crawler technology and an OCR recognition technology, such as: health certificate information of employees, permitted operation scope, and the like. The crawler technology acquires usually picture information, and the picture information is converted into data available for the system through an OCR recognition technology.
And (3) acquiring basic information such as the name of a merchant, the telephone, the address of the merchant, the score, the monthly sales volume and the like through a platform registration database, such as a platform of hungry, American group takeout and the like. And storing the acquired data into a cloud database for multi-point storage by using a cloud computing technology.
And comparing the acquired merchant information (such as merchant license information and license service life) with information in a license cloud database and a license cloud database in the existing business cloud database at a data comparison module. Wherein, the business license cloud database in the business cloud database is connected with the market supervision system and the public security system of province, city and district. The license database is connected with the industrial and commercial systems and the market supervision systems of provinces, cities and districts. Whether the problems of no-certificate operation, overdue certificate, one certificate with multiple stores and one store with multiple certificates exist is judged through multipoint comparison. The data comparison module lists all suspicious items found in the comparison process in a table so that the data analysis module can further analyze the suspicious items.
And the data analysis module is used for carrying out suspicious event analysis on all suspicious items found in the data comparison module. The suspicious event analysis is mainly divided into false business license, false license, one-card multi-purpose, super-validity event analysis and the like. And calling policy violation models corresponding to the province, the city and the district according to policy templates of different provinces, cities and districts, wherein violation items contained in the policy violation models, such as a false business license, a false license, a single certificate with multiple purposes, an over-validity period and the like, are added into a blacklist, and a correction notice is sent. The monitoring system of the embodiment can flexibly adjust violation models and determine violation items according to different definitions of the violation types of various provinces, and facilitates the monitoring system to realize monitoring across different provinces.
In addition, the data analysis module carries out statistical analysis on the conventional data to determine important monitoring areas and important monitoring events. For example, the number of online ordering merchants of each platform, the distribution of provinces, cities and counties of the prefecture, the emphasis monitoring merchants and school canteens can be counted … …. By monitoring the key areas, large regional events are effectively prevented from happening. The tracking and feedback service function of the key events is realized by tracking the key events, calling key event data, analyzing the key event data and feeding back the key data. The method is characterized in that information of each main link of a key event is recorded in real time, the latest dynamic state is automatically updated, data such as the root of the event occurrence, the event dynamic state, the event influence, public opinion reflection and the like are recorded in a full chain, comparison, analysis and research and judgment are carried out through multiple visual angles and multiple dimensions, and a certain key event is timely fed back to relevant departments by combining multiple factors.
The data presentation module may include a number of functions: comprehensive query, abnormal information, statistical analysis, intelligent maps and the like.
Based on the analysis result provided by the data analysis module, the data display module visually displays all aspects of conditions such as supervision objects, supervision and enforcement, time tracking, risk early warning and the like in various modes such as a graph, a table and the like.
In addition, the data display module also comprises various geographic information data, such as GPS data, oblique photography data, BIM building model data, an intelligent map and the like, and the merchant filling address and the issuing authority registration address data can be compared through the geographic information data, so that the actual address of the merchant store, the nearby street view data, the three-dimensional map information and the like are displayed, and further, the supervision and law enforcement action can be conveniently carried out.
Having described embodiments of the present disclosure, the foregoing description is intended to be exemplary, not exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen in order to best explain the principles of the embodiments, the practical application, or improvements made to the technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
Claims (10)
1. A cloud computing-based online meal ordering supervisory system, the system comprising:
the data acquisition module is used for acquiring basic information data of online catering merchants and performing multi-point storage in a cloud database;
the data comparison module is used for comparing the acquired basic information data of the online catering commercial tenant with the information data stored in the existing business cloud database;
the data analysis module is used for analyzing suspicious matters of the data and adding the merchants with the suspicious matters into a blacklist based on the output result of the comparison module;
and the data display module is used for displaying the overall situation of the network ordering supervision work in a multi-dimensional way.
2. The online meal ordering supervisory system as recited in claim 1, wherein the data acquisition module acquires business license, license information and operation information of online catering merchants through a crawler technology and an OCR recognition technology.
3. The system of claim 1, wherein the data comparison module compares the business license, license information and license lifetime of the online catering merchant with information in a business license cloud database and a license cloud database in an existing business cloud database, and determines whether suspicious events exist by comparison.
4. The system of claim 1, wherein the data analysis module further performs statistical analysis to determine key monitoring areas and key monitoring events by performing statistical analysis on the regular data.
5. The system of claim 1, wherein the data comparison module invokes policy violation models for different provinces, cities and districts to analyze suspicious events, thereby determining violation items for different provinces, cities and districts.
6. The system of claim 5, wherein the analysis of suspicious events is mainly classified into false license, one-card-multiple-use, and super-validity analysis.
7. The network order supervision system of claim 3 wherein the business license cloud database of the business cloud database interfaces with the market supervision system of province, city, district and the database of the public security system; and the license cloud database is in butt joint with the databases of the industrial and commercial systems and the market supervision systems in provinces, cities and regions.
8. A network ordering supervision method based on cloud computing is characterized by comprising the following steps:
acquiring basic information data of online catering merchants, and performing multi-point storage in a cloud database;
comparing the acquired basic information data of the online catering commercial tenant with information data stored in an existing business cloud database;
based on the output result of the comparison module, performing suspicious item analysis on the data, and adding the commercial tenant with the suspicious items into a blacklist;
and displaying the global situation of network ordering supervision work in a multidimensional way.
9. The online ordering supervision method according to claim 8, wherein the business license and license information of online catering merchants and the operation information of online catering merchants are obtained by a crawler technology and an OCR recognition technology: health certificate information of the workers and the permitted operation range;
and acquiring the name, the telephone, the address, the score and the monthly sales volume of the merchant through the platform registration database.
10. The method of claim 8, wherein policy violation models corresponding to provinces, cities and districts are invoked for policy templates of different provinces, cities and districts, and according to the output result of the comparison module, merchants with false business licenses, false licenses, multiple uses and an expiration date are added to the blacklist, and a rectification notification is sent.
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| CN113256113A (en) * | 2021-05-25 | 2021-08-13 | 华讯高科股份有限公司 | Network meal supervision system and method based on big data platform |
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Application publication date: 20200529 |