Intelligent early warning system based on dish production

Abstract

The intelligent early warning system comprises a raw material database, a to-be-processed material optical recording module, a processing module, a finished product warehouse, a finished product optical analysis module and a processing analysis module. Wherein the raw material database and the finished product database are color databases in food material processing and non-processing states, the processing module obtains color original points in the databases to fit the safety processing process, the processing analysis module calls the data, and the data are collected through the to-be-processed material optical recording module and the finished product optical analysis module; whether the actual machining process is within the safety range or not is obtained. According to the characteristic that food material changes are continuous in a safety range, overall inference is carried out according to color expression and processing safety of dish products and color expression of raw material safety, and whether the food material processing process is in a food material safety state or not is judged.

Description

Technical Field

[0001] This invention relates to the field of monitoring, and in particular to an intelligent early warning system based on the production of dishes. Background Technology

[0002] Currently, the information-based management of food safety in public canteens is in its initial stage, and the self-discipline of canteen management is weak in the whole-process supervision of food safety. This necessitates the intervention of process informatization. At present, in the kitchens of public canteens, food safety management by canteen operators is still at the stage of sample retention. Sample retention as a food safety measure has a high degree of lag. Once a problem occurs, a food safety incident has already happened. Therefore, there is currently a lack of means to intercept food safety problems at the processing stage.

[0003] Based on the above reasons, an intelligent early warning system based on the production of dishes is needed to solve the above problems. Summary of the Invention

[0004] This invention addresses the current food safety issues in public canteens, where food safety management by canteen operators is still largely limited to sample retention. Sample retention, as a food safety measure, is highly reactive; by the time a problem occurs, a food safety incident has already taken place. Therefore, there is a lack of means to intercept food safety problems at the processing stage. This invention provides an intelligent early warning system based on the finished food product, solving the aforementioned problems.

[0005] This invention provides an intelligent early warning system based on food production, including a raw material database, an optical recording module for materials to be processed, a processing module, a finished product database, a finished product optical analysis module, and a processing analysis module.

[0006] The raw material database is used to record the optical safety status data of raw materials and the semantics of images based on various states of raw materials, and to perform regression on the optical safety status data of materials in the color gamut to obtain the material safety curve and set the tolerance range.

[0007] The optical module for materials to be processed is used to collect optical data of raw materials at the time of their departure from the warehouse.

[0008] The processing module is used to record different processing methods of raw materials, and set the standard color of raw materials before processing and the standard color of food after processing according to the processing method. Based on the standard color, the origin is set in the color gamut. According to the color change of raw materials in various processing scenarios over time, the standard color of raw materials before processing and the standard color of food after processing are connected in the color gamut to form a processing curve, and a tolerance range is set.

[0009] The finished product library is used to record the semantics of images of different finished dishes and to record the types of raw materials corresponding to each finished dish;

[0010] The finished product optical analysis module is used to collect optical information of the processed finished products, rather than comparing with the finished product database to determine the type of finished product and then determining the corresponding raw materials based on the type of finished product.

[0011] The processing analysis module compares the currently detected finished product with the finished product data from the finished product optical analysis module to obtain the current finished product raw material list. It then combines the current finished product's processing curve with the corresponding material safety curve to determine whether the current finished product's optical data falls at the intersection of the processing tolerance range and the material safety curve's tolerance range. If so, no warning is issued; otherwise, an alarm is triggered.

[0012] This invention provides an intelligent early warning system based on food production. As a preferred embodiment, the processing analysis module sets the safety zone in the following way:

[0013] The processing module is also used to separately record the processing methods that cause non-linear color development of raw materials during the processing process, and to set a tolerance range within the color gamut based on the standard color of the raw materials with non-linear color development in the standard state of each processing node.

[0014] This invention provides an intelligent early warning system based on the output of dishes. As a preferred method, the color gamut adopts the cyan-green high-performance color gamut.

[0015] This invention provides an intelligent early warning system based on the output of dishes. As a preferred method, the color gamut adopted is Adobe RGB.

[0016] This invention provides an intelligent early warning system based on the output of dishes. As a preferred embodiment, the intelligent early warning system based on the output of dishes also includes a weighing module, which is used to record the weight of each raw material and the weight loss during processing, and assists the finished product optical analysis module in determining the type of finished product.

[0017] In this technical solution, the raw material database and the finished product database are color databases of food in processed and unprocessed states. The processing module obtains the color origin from the database to fit a safe processing process. The processing analysis module retrieves the above data and collects it through the optical recording module of the material to be processed and the optical analysis module of the finished product to determine whether the actual processing process is within the safe range.

[0018] The beneficial effects of this invention are as follows:

[0019] This invention, by taking advantage of the continuous nature of changes in ingredients within a safe range, makes an overall inference based on the color appearance of the finished dish, the safety of processing, and the color appearance of raw materials to determine whether the food processing process is in a safe state. Attached Figure Description

[0020] Figure 1This is a schematic diagram of an intelligent early warning system based on the output of dishes.

[0021] Figure label:

[0022] 1. Raw material database; 2. Optical recording module for materials to be processed; 3. Processing module; 4. Finished product library; 5. Optical analysis module for finished products; 6. Processing analysis module. Detailed Implementation

[0023] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0024] Example 1

[0025] like Figure 1 As shown, an intelligent early warning system based on dish production includes a raw material database 1, an optical recording module for materials to be processed 2, a processing module 3, a finished product database 4, a finished product optical analysis module 5, and a processing analysis module 6.

[0026] The raw material database 1 is used to record the optical safety status data of raw materials and the semantics of images based on various states of raw materials, and to perform regression on the optical safety status data of materials in the color gamut to obtain the material safety curve and set the tolerance range.

[0027] The optical recording module 2 for materials to be processed is used to collect optical data of raw materials at the time of their departure from the warehouse;

[0028] The processing module 3 is used to record different processing methods of raw materials, and set the standard color of raw materials before processing and the standard color of food after processing according to the processing method. Based on the standard color, the origin is set in the color gamut. According to the color change of raw materials in various processing scenarios over time, the standard color of raw materials before processing and the standard color of food after processing are connected in the color gamut to form a processing curve, and a tolerance range is set.

[0029] Finished Product Library 4 is used to record the semantics of images of different finished dishes and to record the types of raw materials corresponding to each finished dish;

[0030] The finished product optical analysis module 5 is used to collect optical information of the processed finished products, not to compare with the finished product library 4 to determine the type of finished product, and then to determine the corresponding raw materials based on the type of finished product.

[0031] The processing analysis module 6 compares the currently detected finished product with the finished product data of the finished product optical analysis module 5 to obtain the current finished product raw material list. It then combines the processing curve of the current finished product with the corresponding material safety curve to determine whether the current finished product optical data falls at the intersection of the processing tolerance range and the material safety curve range. If so, no warning is given; otherwise, an alarm is triggered.

[0032] Specifically, the processing analysis module 6 sets the safety zone in the following way:

[0033] Processing module 3 is also used to separately record the processing methods that cause non-linear color development of raw materials during the processing process, and to set a width limit range within the color gamut based on the standard color of the raw materials with non-linear color development in the standard state of each processing node.

[0034] In this embodiment, the color gamut used is the cyan-green high-performance color gamut.

[0035] Furthermore, in this embodiment, the color gamut adopted is the Adobe RGB color gamut.

[0036] Example 2

[0037] Based on Example 1, the intelligent early warning system based on dish output also includes a weighing module, which is used to record the weight of each raw material and the weight loss during processing, and assists the finished product optical analysis module 5 in determining the type of finished product.

[0038] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. An intelligent early warning system based on dish production, characterized in that: It includes a raw material database (1), an optical recording module for materials to be processed (2), a processing module (3), a finished product database (4), a finished product optical analysis module (5), and a processing analysis module (6). The raw material database (1) is used to record the optical safety status data of raw materials and the semantics of images based on various states of raw materials, and to perform regression on the optical safety status data of materials in the color gamut to obtain the material safety curve and set the tolerance range. The optical recording module (2) for the material to be processed is used to collect optical data of the raw materials at the time of their departure from the warehouse; The processing module (3) is used to record different processing methods of raw materials, and set the standard color of raw materials before processing and the standard color of food after processing according to the processing method. Based on the standard color, the origin is set in the color gamut. According to the color change of raw materials in various processing scenarios, the standard color of raw materials before processing and the standard color of food after processing are connected in the color gamut to form a processing curve, and a width limit is set. The finished product library (4) is used to record the semantics of the images of different finished dishes and to record the types of raw materials corresponding to each finished dish; The finished product optical analysis module (5) is used to collect optical information of the processed finished product, not by comparing it with the finished product library (4), to determine the type of finished product, and then to determine the corresponding raw materials based on the type of finished product; The processing analysis module (6) matches the currently detected finished product with the finished product data of the finished product optical analysis module (5) to obtain the current finished product raw material list, and combines the current finished product processing curve and the corresponding material safety curve to determine whether the current finished product optical data falls at the intersection of the processing tolerance range and the material safety curve range. If yes, it determines that there is no warning; otherwise, it alarms.

2. The intelligent early warning system based on dish production according to claim 1, characterized in that: The processing analysis module (6) sets the safety zone in the following way: The processing module (3) is also used to separately record the processing method that causes the raw material to develop non-linear color during the raw material processing process, and to set a width limit range in the color gamut based on the standard color of the raw material with non-linear color development in the standard state of each processing node.

3. The intelligent early warning system based on dish production according to claim 1, characterized in that: The color gamut used is the cyan-green high-performance color gamut.

4. The intelligent early warning system based on dish production according to claim 3, characterized in that: The color gamut used is the Adobe RGB color gamut.

5. The intelligent early warning system based on dish production according to claim 1, characterized in that: The intelligent early warning system based on the dish output also includes a weighing module, which is used to record the weight of each raw material and the weight loss during processing, and assists the finished product optical analysis module (5) in determining the type of finished product.

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