Catering food safety dynamic supervision method based on big data analysis
A technology of big data and management methods, applied in the field of big data analysis, can solve the problems of inability to evaluate the state of the region, inability to be dynamic, lack of interaction and participation, etc., to solve the problem of insufficient supervision force, improve the accuracy of strikes, and improve supervision The effect of potency
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Embodiment 1
[0034] Reference figure 1 , Shown as an embodiment of the present invention, a method for dynamic monitoring of food safety based on big data analysis, including the following steps:
[0035] Data access provides multiple interfaces for accessing catering industry data including government regulatory agency data, enterprise self-inspection data, and social evaluation data. The data access is dynamically adjusted according to regulatory requirements. For example, government regulatory department data can include data from the supervision and inspection of the handheld law enforcement system, the food business license system and the "three small and one stall" filing system, business license registration system data, foodborne disease risk monitoring system data, and "dual system" testing. Traceability system data, food material and tableware supervision and sampling system data, practitioner electronic health certificate system data, administrative punishment case system data, onl...
Embodiment 2
[0051] On the basis of embodiment 1, the method for dynamic monitoring of food safety based on big data analysis in the embodiment of the present invention further includes:
[0052] Risk ranking, catering companies are divided into high-risk units, general-risk units and low-risk units according to the types of risk factors.
[0053] In the specific implementation process, risk factors can be classified according to risk categories, such as veto negative information, key negative information, general negative information, and positive information for corresponding deductions and bonus points, such as full marks 100 points, according to 60 and 80 points. Rejecting negative information is the highest weighted serious veto item. Once it appears, it is directly marked as high risk (such as directly deducting 50 points and the positive information is invalid); key negative information has the second highest weight; positive information is a bonus item, Used for repair and promotion.
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Embodiment 3
[0057] Based on the safety scores of catering companies, the safety scores can be used to give users and regulatory agencies certain guidance. Therefore, this embodiment further proposes a four-color dynamic food safety code management method based on changes in food safety index on the basis of embodiment 1, including:
[0058] Data access is used to access catering industry data including government regulatory agency data, enterprise self-inspection data, and social evaluation data. Using big data cloud computing technology, comprehensive evaluation of catering units including AI video analysis within a certain period of time Standardize behavior, site environment and equipment operation IoT sensing, electronic ledger data, personnel training and self-inspection to implement daily management data;
[0059] The food safety index risk factor statistics is used to calculate the access data according to the catering safety risk factors, and perform risk classification and quantitativ...
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