CN111552775B - Food data processing method and system - Google Patents
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- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
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Abstract
The invention discloses a food data processing method and a system, wherein the method comprises the following steps: collecting food data; judging whether food corresponding to the food data is abnormal or not according to the collected food data, and acquiring food abnormality information if the food is abnormal; and carrying out inspection according to the acquired food abnormality information. By the technical scheme, manpower and material resources consumed in searching and analyzing the abnormal information of the food are saved, and potential safety hazards of the food are avoided.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a food data processing method and system.
Background
Food safety (food safety) is always a social hotspot problem, and food safety refers to food which is nontoxic and harmless, meets the corresponding nutritional requirements, and does not cause any acute, subacute or chronic harm to human health. At present, supervision of food, search and analysis of abnormal information of the food rely on human labor to check, a large amount of manpower and material resources are consumed, and abnormal analysis of the whole quality of the food cannot be accurately performed, so that potential safety hazards of the food can be caused.
Disclosure of Invention
The invention provides a food data processing method, which comprises the following steps:
collecting food data;
judging whether food corresponding to the food data is abnormal or not according to the collected food data, and acquiring food abnormality information if the food is abnormal;
and carrying out inspection according to the acquired food abnormality information.
In one embodiment, the step of collecting food data comprises:
acquiring data acquisition service requirements;
configuring a data acquisition task rule according to the data acquisition service requirement; wherein the data acquisition task rule corresponds to at least one acquisition characteristic information;
and carrying out data acquisition according to the acquisition task rule to obtain the food data.
In one embodiment, the step of collecting food data further comprises:
detecting food keywords in a target website, an application APP or a target scene, wherein the food keywords are common words in the food industry;
when food keywords are detected in the target website, application APP or target scene, determining an information segment where the detected food keywords are located;
determining the information section where the detected food keywords are located as food characteristic information;
judging whether the food characteristic information is matched with the acquisition characteristic information in the data acquisition task rule,
and if so, carrying out data acquisition in the target website, the application APP or the target scene according to the acquisition task rule so as to obtain the food data.
In one embodiment, when collecting food data, further comprising:
acquiring the current time when the food data are acquired, wherein the current time comprises years, months, days, hours, minutes and seconds;
judging whether the food data meets the standards of the private information, storing the food data in an encryption mode according to the moment when the food data meets the standards of the private information,
and when the food data does not meet the standards of the private information, storing the food data in a non-encryption mode according to the moment.
In one embodiment, the step of determining whether the food corresponding to the food data is abnormal according to the collected food data, and if so, acquiring food abnormality information includes:
converting the collected food data and the data in the food data standard library into a data structure in a preset table form;
searching the food data standard library for an original standard data set which is the same as at least one constituent of food corresponding to the food data in the food data;
searching and screening the original standard data set according to the food names in the food data to obtain a current standard data set;
performing similarity calculation on the current standard data set according to all the components of the food corresponding to the food data to obtain the similarity between the food data and any piece of data in the current standard data set;
determining data with highest similarity with the food data in the current standard data set according to the similarity;
judging whether the data with highest similarity with the food data in the current standard data set is the same as the food data,
if the food data are different, determining that the food corresponding to the food data is abnormal, and acquiring food abnormality information;
wherein the composition comprises ingredient composition and/or nutritional composition.
In one embodiment, the step of performing inspection according to the obtained food anomaly information includes:
acquiring the food abnormality information;
acquiring a patrol instruction;
based on the inspection instruction, performing inspection according to the food abnormal information to obtain an inspection result;
sending out a prompt according to the inspection result;
and carrying out label processing or extraction processing on the food corresponding to the food abnormality information according to the prompt.
In one embodiment, the food data includes any one or more of a food name, a food production date, a food shelf life, a composition, a place of origin, and a production license number.
In one embodiment, further comprising:
and carrying out pollution-free recovery or destruction on the food corresponding to the food abnormality information.
In one embodiment, determining whether the food corresponding to the food data is abnormal according to the collected food data specifically includes:
A. preliminary judgment is carried out on the food corresponding to the food data according to the food data;
wherein delta is the preliminary judgment value of the food corresponding to the food data, and x i An i-th data value of the food data, n being the number of data contained in the food data, [ m ] i ,n i ]A normal value range for the ith data of the food data;
when delta is larger than a preset judgment value, the food corresponding to the food data is suspected to be abnormal, further judgment is needed to be carried out on the food corresponding to the food data which is suspected to be abnormal according to B, otherwise, the food corresponding to the food data is normal, and B is not needed. .
B. Further judging the food corresponding to the food data suspected to be abnormal;
calculating the judging value of the chemical attribute data and the physical attribute data of the food corresponding to the food data;
in the above formula, k i Is the judgment value alpha of the ith data in the chemical attribute of the food corresponding to the food data i An ith data value, a, in the chemical attribute of the food corresponding to the food data i The lower limit of the normal range of the ith data in the chemical attribute of the food corresponding to the food data, b i G, the upper limit of the normal range of the ith data in the chemical attribute of the food corresponding to the food data i Is the judgment value of the ith data in the physical attributes of the foods corresponding to the food data, beta i The ith data, z in the physical attribute of the food corresponding to the food data i And (3) the ith data standard value in the physical attributes of the foods corresponding to the food data, exp is an exponential function, lg is a logarithmic function, and e is a natural number.
Obtaining a further judgment result;
wherein ,k is the further judging result of the food corresponding to the food data i G, determining the ith data in the chemical attribute of the food corresponding to the food data i A is the judgment value of the ith data in the physical attributes of the foods corresponding to the food data i To preset the confidence interval of the ith data in the chemical attribute of the food corresponding to the food data, p i And presetting a limit value of the ith data in the physical attribute of the food corresponding to the food data, wherein 1 represents abnormal food corresponding to the food data, and 0 represents normal food corresponding to the food data.
The present invention provides a food data processing system comprising:
the data acquisition end is connected with the server end and is used for acquiring food data and transmitting the food data to the server end;
the server side is respectively connected with the data acquisition side and the inspection side, and is used for receiving the food data sent by the data acquisition side, judging whether food corresponding to the food data is abnormal or not according to the food data, and acquiring food abnormality information and sending the food abnormality information to the inspection side if the food is abnormal;
the inspection terminal is used for receiving the food abnormal information sent by the server terminal so as to conduct inspection according to the food abnormal information.
The technical scheme provided by the embodiment of the invention can have the following beneficial effects:
firstly, collecting food data; then judging whether food corresponding to the food data is abnormal or not according to the food data, and acquiring food abnormality information if the food is abnormal; and finally, carrying out inspection according to the abnormal information of the food. According to the technical scheme, food data are not required to be checked and analyzed artificially, a large amount of manpower and material resources are saved, the whole quality of the food can be analyzed abnormally, abnormal food conditions are acquired accurately according to the food data, and potential food safety hazards are avoided.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention may be realized and attained by the structure particularly pointed out in the written description and drawings.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a flow chart of a method for processing food data according to an embodiment of the invention;
FIG. 2 is a flow chart of another method for processing food data according to an embodiment of the invention;
FIG. 3 is a flow chart of a method for processing food data according to another embodiment of the present invention;
FIG. 4 is a flow chart of a method for processing food data according to another embodiment of the present invention;
FIG. 5 is a block diagram of a food data processing system in accordance with an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, it being understood that the preferred embodiments described herein are for illustration and explanation of the present invention only, and are not intended to limit the present invention.
The invention provides a food data processing method, as shown in figure 1, comprising the following steps:
step 1: collecting food data;
step 2: judging whether food corresponding to the food data is abnormal or not according to the collected food data, and acquiring food abnormality information if the food is abnormal;
step 3: and carrying out inspection according to the acquired food abnormality information.
Food data includes, but is not limited to, food name, date of food manufacture, food shelf life, composition, place of origin, and production license number.
The abnormal information of the food includes, but is not limited to, food which is already an expired product and is not produced by the production license, taste which is caused by the fact that the composition of the food is not standard, and the like.
Firstly, collecting food data; then judging whether food corresponding to the food data is abnormal or not according to the food data, and acquiring food abnormality information if the food is abnormal; and finally, carrying out inspection according to the food abnormality information. According to the technical scheme, food data are not required to be checked and analyzed artificially, a large amount of manpower and material resources are saved, the whole quality of the food can be analyzed abnormally, abnormal food conditions are acquired accurately according to the food data, and potential food safety hazards are avoided.
In one embodiment, as shown in fig. 2, the step of collecting food data includes:
step 11: acquiring data acquisition service requirements;
step 12: configuring a data acquisition task rule according to the data acquisition service requirement; wherein the data acquisition task rule corresponds to at least one acquisition characteristic information;
step 13: and carrying out data acquisition according to the acquisition task rule to obtain the food data.
The requirement of the collection business refers to the requirements of the variety of food data to be collected (the variety of the food is various, such as beverage and snack, and the beverage and snack can be further accurate to what brand, such as cola, etc.), the quantity of the collected food data, etc., while the rule of the data collection task is the materialization of the requirement of the data collection business, and the collection characteristic information can be specific collection quantity, specific collection variety, etc.
In this embodiment, a data acquisition service requirement is acquired; then, configuring a data acquisition task rule according to the data acquisition service requirement; furthermore, the data acquisition is performed according to the acquisition task rule, so that the food data can be obtained, and the food data can be acquired in a targeted and purposeful manner through configuring the data acquisition task rule, so that the efficiency is increased.
In one embodiment, as shown in fig. 3, the step of collecting food data further includes:
step 111: detecting food keywords in a target website, an application APP or a target scene, wherein the food keywords are common words in the food industry;
step 112: when food keywords are detected in the target website, application APP or target scene, determining an information segment where the detected food keywords are located;
step 113: determining the information section where the detected food keywords are located as food characteristic information;
step 114: judging whether the food characteristic information is matched with the acquisition characteristic information in the data acquisition task rule,
step 115: and if so, carrying out data acquisition in the target website, the application APP or the target scene according to the acquisition task rule so as to obtain the food data.
In this embodiment, the target website or application APP may be a website or APP on which the user sells goods, and the purpose of collecting data from the website or APP is to prevent errors in data logged on the website or APP or have expired to cause adverse effects on customers, the target scene may be a food production place, supermarket, shopping mall, etc., and the food keyword may be a food name, food advertisement word, food manufacturer, food component, etc.
The information section of the food keywords refers to sentences or paragraphs of the food keywords, for example, the information section of the food keywords is that "the real fruit grains are the first generation of milk beverage containing chewable fruit grains in the world, which is pushed out by Mongolian groups, and a great deal of innovation attracts a lot of customers. As the fruit granule milk beverage with the most abundant taste at present, the real fruit granule has five flavors of strawberry, kiwi fruit, coconut fruit, yellow peach and aloe. The requirements of consumers with different preferences at different times, different occasions and even different moods are met, and food keywords are included in the requirements, for example: "real fruit granule, mongolian cattle group, milk beverage" etc.
For example, the information segment where the food keyword is located is "the real fruit is a new generation milk beverage containing chewable fruit, which is introduced by Mongolian cattle group, and the great innovation attracts a lot of customers", if the food feature information is "the real fruit", the two are directly matched, and if the food feature information is "cola", the two are not matched.
In the embodiment, food keywords are detected in a target website, an application APP or a target scene; when food keywords are detected in the target website, application APP or target scene, determining an information segment where the detected food keywords are located; secondly, determining the information section where the detected food keywords are located as food characteristic information; and finally, judging whether the food characteristic information is matched with the acquisition characteristic information in the data acquisition task rule, and if so, carrying out data acquisition in the target website, the application APP or the target scene according to the acquisition task rule to obtain the food data. By adding a matching mechanism between food characteristic information and acquisition characteristic information, food data meeting requirements of a target website, application APP or target scene can be acquired more rapidly and accurately.
In one embodiment, when collecting food data, further comprising:
acquiring the current time when the food data are acquired, wherein the current time comprises years, months, days, hours, minutes and seconds;
judging whether the food data meets the standards of the private information, storing the food data in an encryption mode according to the moment when the food data meets the standards of the private information,
and when the food data does not meet the standards of the private information, storing the food data in a non-encryption mode according to the moment.
In this embodiment, the time of day refers to the time at which food data is collected, for example, 16 minutes and 30 seconds at 10 days of 2020, 04 months.
In this embodiment, the time instant when the food data is acquired; judging whether the food data meets the standard of private information, storing the food data in an encryption mode according to the time when the food data meets the standard of the private information, and storing the food data in a non-encryption mode according to the time when the food data does not meet the standard of the private information. By adding an encryption mode or a non-encryption mode to classify the food information, the storage pressure caused by the storage of a single mode can be avoided, and the food data meeting the private information can be prevented from being leaked by the storage of the encryption mode.
In one embodiment, as shown in fig. 4, the step of determining whether the food corresponding to the food data is abnormal according to the collected food data, and if so, acquiring food abnormality information includes:
step 41: converting the collected food data and the data in the food data standard library into a data structure in a preset table form;
step 42: searching the food data standard library for an original standard data set which is the same as at least one constituent of food corresponding to the food data in the food data;
step 43: searching and screening the original standard data set according to the food names in the food data to obtain a current standard data set;
step 44: performing similarity calculation on the current standard data set according to all the components of the food corresponding to the food data to obtain the similarity between the food data and any piece of data in the current standard data set;
step 45: determining data with highest similarity with the food data in the current standard data set according to the similarity;
step 46: judging whether the data with highest similarity with the food data in the current standard data set is the same as the food data,
if the food data are different, determining that the food corresponding to the food data is abnormal, and acquiring food abnormality information;
wherein the composition comprises ingredient composition and/or nutritional composition.
In this embodiment, the preset table format may be data in an Excel table format, for example, the first column is a food name, the second column is food production date information, and the information about food in the food data standard library (such as food name, food production date, food shelf life, composition, production place and production license number), food safety standard, etc. may be set according to specific requirements of the user.
Wherein, for example, the food corresponding to the food data is searched in the food data standard by using 2.5g of sorbitol which is an ingredient component and fat which is a nutrient component, a plurality of pieces of food data meeting the characteristics appear, and the original standard data set consists of the plurality of pieces of food data.
In the embodiment, the collected food data and the data in the food data standard library are converted into a data structure in a preset table form; searching the food data standard library for an original standard data set which is the same as at least one constituent of food corresponding to the food data in the food data; secondly, searching and screening the original standard data set according to the food names in the food data to obtain a current standard data set; then, carrying out similarity calculation on a current standard data set according to all components of food corresponding to the food data to obtain the similarity of the food data and any piece of data in the current standard data set; and further, determining the data with the highest similarity with the food data in the current standard data set according to the similarity. Judging whether the data with highest similarity with the food data in the current standard data set is the same as the food data, if not, determining that the food corresponding to the food data is abnormal, and acquiring food abnormality information; by performing a series of operations and calculations according to the food data and the data in the food data standard library, food abnormality information corresponding to the food data can be clearly obtained, and specific abnormality positions can be obtained.
In one embodiment, the ingredients, including ingredients and/or nutritional ingredients.
For example, a product named as a mouth-cleaning prebiotics fruit-flavored lozenge candy comprises the ingredients of sorbitol, fructo-oligosaccharide (five percent of additive), inulin (five percent of additive), citric acid, magnesium stearate, food essence, DL malic acid, aspartame (containing phenylalanine), lemon yellow and allure red. The nutritional components of the food are respectively 1742kj (eleven percent), 0g of protein (zero percent), 2.5g of fat (four percent), 97.0g of carbohydrate (thirty-two percent) and 80mg of sodium (four percent).
In one embodiment, the step of performing inspection according to the obtained food anomaly information includes:
acquiring the food abnormality information;
acquiring a patrol instruction;
based on the inspection instruction, performing inspection according to the food abnormal information to obtain an inspection result;
sending out a prompt according to the inspection result;
and carrying out label processing or extraction processing on the food corresponding to the food abnormality information according to the prompt.
In this embodiment, the inspection instruction may be initiated by a user, so as to trigger the operation of the training module, that is, the inspection module may perform the operation only when receiving the inspection instruction, and may not perform the operation when not receiving the inspection instruction.
The inspection result can be the position of the food corresponding to the food abnormal information.
And carrying out label processing or extraction processing on the food corresponding to the food abnormal information according to the prompt, wherein the label processing refers to labeling or marking the position of the food corresponding to the food abnormal information, and the extraction processing refers to extracting the food from a target scene or putting the food on or off a target website APP.
In this embodiment, the abnormal food information sent by the server is received; acquiring a patrol instruction; secondly, based on the inspection instruction, performing inspection according to the food abnormal information to obtain an inspection result; then, sending out a prompt according to the inspection result; and finally, carrying out label processing or extraction processing on the food corresponding to the food abnormality information according to the prompt. The sent prompt can timely carry out label processing or extraction processing on the food corresponding to the food abnormal information.
In one embodiment, the food data includes any one or more of a food name, a food production date, a food shelf life, a composition, a place of origin, and a production license number.
In this embodiment, different food data are obtained to analyze abnormal food information, so that the data can be used for more analysis, and the analysis result is accurate.
In one embodiment, the method further comprises the step of carrying out pollution-free recovery or destruction on the food corresponding to the food abnormality information.
In one embodiment, the food corresponding to the food abnormality information is recovered or destroyed in a nuisanceless manner, so that injury to customers or pollution to the environment can be avoided.
In one embodiment, determining whether the food corresponding to the food data is abnormal according to the collected food data specifically includes:
A. preliminary judgment is carried out on the food corresponding to the food data according to the food data;
wherein delta is the preliminary judgment value of the food corresponding to the food data, and x i An i-th data value of the food data, n being the number of data contained in the food data, [ m ] i ,n i ]A normal value range for the ith data of the food data;
when delta is larger than a preset judgment value, the food corresponding to the food data is suspected to be abnormal, further judgment is needed to be carried out on the food corresponding to the food data which is suspected to be abnormal according to B, otherwise, the food corresponding to the food data is normal, and B is not needed. .
B. Further judging the food corresponding to the food data suspected to be abnormal;
calculating the judging value of the chemical attribute data and the physical attribute data of the food corresponding to the food data;
in the above formula, k i Is the judgment value alpha of the ith data in the chemical attribute of the food corresponding to the food data i In the chemical attribute of the food corresponding to the food dataIth data value, a i The lower limit of the normal range of the ith data in the chemical attribute of the food corresponding to the food data, b i G, the upper limit of the normal range of the ith data in the chemical attribute of the food corresponding to the food data i Is the judgment value of the ith data in the physical attributes of the foods corresponding to the food data, beta i The ith data, z in the physical attribute of the food corresponding to the food data i And (3) the ith data standard value in the physical attributes of the foods corresponding to the food data, exp is an exponential function, lg is a logarithmic function, and e is a natural number.
Obtaining a further judgment result;
wherein ,k is the further judging result of the food corresponding to the food data i G, determining the ith data in the chemical attribute of the food corresponding to the food data i A is the judgment value of the ith data in the physical attributes of the foods corresponding to the food data i To preset the confidence interval of the ith data in the chemical attribute of the food corresponding to the food data, p i And presetting a limit value of the ith data in the physical attribute of the food corresponding to the food data, wherein 1 represents abnormal food corresponding to the food data, and 0 represents normal food corresponding to the food data.
The beneficial effects of this embodiment are: according to the technical scheme, whether the food corresponding to the food data is abnormal or not is judged, whether the food corresponding to the food data is suspected to be abnormal or not is judged first, then the suspected abnormal food is further judged, misjudgment can be effectively avoided through secondary judgment, judgment can be more accurate according to the physical attribute and the chemical attribute of the food corresponding to the food data during further judgment, and the whole judgment can be realized through a computer, and is rapid and convenient.
The present invention provides a food data processing system, as shown in fig. 5, comprising:
the data acquisition end 11 is connected with the server end 12 and is used for acquiring food data and transmitting the food data to the server end 12;
the server side 12 is respectively connected with the data acquisition side 11 and the inspection side 13, and is used for receiving the food data sent by the data acquisition side 11, judging whether food corresponding to the food data is abnormal according to the food data, and acquiring food abnormality information and sending the food abnormality information to the inspection side if the food is abnormal;
the inspection terminal 13 is configured to receive the food anomaly information sent by the server terminal 12, so as to perform inspection according to the food anomaly information.
The beneficial effects of this embodiment are: the food data is not required to be checked and analyzed artificially, a large amount of manpower and material resources are saved, the whole quality of the food can be accurately analyzed abnormally, abnormal food conditions are accurately obtained according to the food data, and the potential safety hazards of the food are avoided.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (8)
1. A method of food data processing comprising:
collecting food data;
judging whether food corresponding to the food data is abnormal or not according to the collected food data, and acquiring food abnormality information if the food is abnormal;
performing inspection according to the obtained food abnormal information;
judging whether food corresponding to the food data is abnormal or not according to the collected food data specifically comprises:
A. preliminary judgment is carried out on the food corresponding to the food data according to the food data;
wherein ,preliminary judgment value of food corresponding to the food data, < > for the food corresponding to the food data>For the ith data value of said food data, n is the number of data comprised by said food data,/for each item of food data>A normal value range for the ith data of the food data;
when (when)When the food data is larger than a preset judgment value, the food corresponding to the food data is suspicious to be abnormal, the food corresponding to the food data which is suspicious to be abnormal needs to be further judged according to the B, otherwise, the food corresponding to the food data is normal, and the B is not needed;
B. further judging the food corresponding to the food data suspected to be abnormal;
calculating the judging value of the chemical attribute data and the physical attribute data of the food corresponding to the food data;
in the above-mentioned formula(s),judging the value of the ith data in the chemical attribute of the food corresponding to the food data, namely, the +_f>For the ith data value in the chemical attribute of the food corresponding to the food data,/th data value in the chemical attribute of the food corresponding to the food data>For the lower limit of the normal range of the ith data in the chemical attribute of the food corresponding to the food data,/item>An upper limit of a normal range of the ith data in the chemical attribute of the food corresponding to the food data,/for the food data>Judging the value of the ith data in the physical attribute of the food corresponding to the food data, and (I) is the value of the judgment of the ith data in the physical attribute of the food corresponding to the food data>For the ith data in the physical attribute of the food corresponding to the food data,/th data in the physical attribute of the food corresponding to the food data>An ith data standard value in the physical attribute of the food corresponding to the food data, exp is an exponential function, lg is a logarithmic function, and e is a natural number;
obtaining a further judgment result;
wherein ,for the further judgment result of the food corresponding to the food data,/I>Judging the value of the ith data in the chemical attribute of the food corresponding to the food data, namely, the +_f>Judging the value of the ith data in the physical attribute of the food corresponding to the food data, and (I) is the value of the judgment of the ith data in the physical attribute of the food corresponding to the food data>For presetting the confidence interval of the ith data in the chemical attribute of the food corresponding to the food data,/item>And presetting a limit value of the ith data in the physical attribute of the food corresponding to the food data, wherein 1 represents abnormal food corresponding to the food data, and 0 represents normal food corresponding to the food data.
2. The method of claim 1, wherein the step of collecting food data comprises:
acquiring data acquisition service requirements;
configuring a data acquisition task rule according to the data acquisition service requirement; wherein the data acquisition task rule corresponds to at least one acquisition characteristic information;
and carrying out data acquisition according to the acquisition task rule to obtain the food data.
3. The method of claim 2, wherein the step of collecting food data further comprises:
detecting food keywords in a target website, an application APP or a target scene, wherein the food keywords are common words in the food industry;
when food keywords are detected in the target website, application APP or target scene, determining an information segment where the detected food keywords are located;
determining the information section where the detected food keywords are located as food characteristic information;
judging whether the food characteristic information is matched with the acquisition characteristic information in the data acquisition task rule,
and if so, carrying out data acquisition in the target website, the application APP or the target scene according to the acquisition task rule so as to obtain the food data.
4. The method of claim 1, wherein upon collecting food data, further comprising:
acquiring the current time when the food data are acquired, wherein the current time comprises years, months, days, hours, minutes and seconds;
judging whether the food data meets the standards of the private information, storing the food data in an encryption mode according to the moment when the food data meets the standards of the private information,
and when the food data does not meet the standards of the private information, storing the food data in a non-encryption mode according to the moment.
5. The method of claim 1, wherein the step of performing a patrol based on the obtained food anomaly information comprises:
acquiring the food abnormality information;
acquiring a patrol instruction;
based on the inspection instruction, performing inspection according to the food abnormal information to obtain an inspection result;
sending out a prompt according to the inspection result;
and carrying out label processing or extraction processing on the food corresponding to the food abnormality information according to the prompt.
6. The method of any one of claims 1-4, wherein the food data comprises any one or more of a food name, a date of manufacture of the food, a shelf life of the food, a composition, a place of production, and a production license number.
7. The method as recited in claim 1, further comprising:
and carrying out pollution-free recovery or destruction on the food corresponding to the food abnormality information.
8. A food data processing system, comprising:
the data acquisition end is connected with the server end and is used for acquiring food data and transmitting the food data to the server end;
the server side is respectively connected with the data acquisition side and the inspection side, and is used for receiving the food data sent by the data acquisition side, judging whether food corresponding to the food data is abnormal or not according to the food data, and acquiring food abnormality information and sending the food abnormality information to the inspection side if the food is abnormal;
the inspection terminal is used for receiving the food abnormal information sent by the server terminal so as to carry out inspection according to the food abnormal information;
judging whether food corresponding to the food data is abnormal or not according to the collected food data specifically comprises:
A. preliminary judgment is carried out on the food corresponding to the food data according to the food data;
wherein ,preliminary judgment value of food corresponding to the food data, < > for the food corresponding to the food data>For the ith data value of said food data, n is the number of data comprised by said food data,/for each item of food data>A normal value range for the ith data of the food data;
when (when)When the food data is larger than a preset judgment value, the food corresponding to the food data is suspicious to be abnormal, the food corresponding to the food data which is suspicious to be abnormal needs to be further judged according to the B, otherwise, the food corresponding to the food data is normal, and the B is not needed;
B. further judging the food corresponding to the food data suspected to be abnormal;
calculating the judging value of the chemical attribute data and the physical attribute data of the food corresponding to the food data;
in the above-mentioned formula(s),judging the value of the ith data in the chemical attribute of the food corresponding to the food data, namely, the +_f>For the ith data value in the chemical attribute of the food corresponding to the food data,/th data value in the chemical attribute of the food corresponding to the food data>For the lower limit of the normal range of the ith data in the chemical attribute of the food corresponding to the food data,/item>An upper limit of a normal range of the ith data in the chemical attribute of the food corresponding to the food data,/for the food data>Judging the value of the ith data in the physical attribute of the food corresponding to the food data, and (I) is the value of the judgment of the ith data in the physical attribute of the food corresponding to the food data>For the ith data in the physical attribute of the food corresponding to the food data,/th data in the physical attribute of the food corresponding to the food data>An ith data standard value in the physical attribute of the food corresponding to the food data, exp is an exponential function, lg is a logarithmic function, and e is a natural number;
obtaining a further judgment result;
wherein ,for the further judgment result of the food corresponding to the food data,/I>Judging the value of the ith data in the chemical attribute of the food corresponding to the food data, namely, the +_f>Judging the value of the ith data in the physical attribute of the food corresponding to the food data, and (I) is the value of the judgment of the ith data in the physical attribute of the food corresponding to the food data>For presetting the confidence interval of the ith data in the chemical attribute of the food corresponding to the food data,/item>And presetting a limit value of the ith data in the physical attribute of the food corresponding to the food data, wherein 1 represents abnormal food corresponding to the food data, and 0 represents normal food corresponding to the food data.
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