CN113837773A - Data transmission system and method based on Internet of things - Google Patents
Data transmission system and method based on Internet of things Download PDFInfo
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- CN113837773A CN113837773A CN202111124382.5A CN202111124382A CN113837773A CN 113837773 A CN113837773 A CN 113837773A CN 202111124382 A CN202111124382 A CN 202111124382A CN 113837773 A CN113837773 A CN 113837773A
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
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Abstract
The invention discloses a data transmission system and a method based on the Internet of things, wherein the system comprises a food spot check detection module, a data security analysis module and a data traceability analysis module, the food spot check detection module is used for detecting and verifying food production information during spot check of food, the data security analysis module is used for reading and storing the commodity information through an EPCIS middleware when the food is transported to a specified destination, different checking authorities are set at different checking ports, the information stored in an EPC is ensured not to be easily attacked, the security of data is ensured, the data traceability analysis module to be analyzed is used for acquiring the information in the node of the Internet of things and comparing the information by calling the commodity information produced in the same batch; the food spot check detection module is used for judging whether the data information of the food is changed or not, so that the user can safely feel relieved when using the food, and whether the abnormal data information is modified by people or not can be analyzed.
Description
Technical Field
The invention relates to the technical field of Internet of things food safety, in particular to a data transmission system and method based on the Internet of things.
Background
Along with the gradual increase of the living standard of people, more and more people pay attention to food safety, particularly fast selling industry, like milk, fresh milk and other industries, the quality guarantee date is extremely short, so people pay more attention to the production date and the quality guarantee date, but some manufacturers will sell the milk that is close to being overdue and has not been sold together with other commodities, sell the milk at a lower price, at the same time, the manufacturer can reprocess some milk products with quick expiration, add new production date and remit the milk products to the market again, and the operation can reduce the loss of the food which is not sold for the manufacturer, therefore, when the production date on the food becomes fuzzy or residual ink marks are arranged around the date, the color and luster are extremely dark, that is, the current date of production is reprocessed, and the normal date of stamping cannot be erased, so the date of production of food should be paid particular attention.
The safety of food is analyzed through the Internet of things, logistics operations such as inspection, loading, unloading, carrying, warehousing and the like can be rapidly carried out on the food through the radio frequency reader in the goods delivery process, information is transmitted to the system, when the food is sold, the production date and the serial number code change, the external package, the color, the fixed quality guarantee date, the type, the specification and the like do not change, the food is identified through the reader in every dynamic state, the related information of the food and the goods is confirmed, and the food in each link can be tracked
The authenticity of the food and the transaction information of the food can be inquired from the food logistics information through the Internet of things, and the fake food is prevented from entering a circulation link, so that each transaction link of the food can be clearly seen through the Internet of things, and the safety of the food is ensured;
the EPC is an electronic product code, which is equivalent to a human identification, each batch of products corresponds to different identification tags, the content of an internal tag attached to food can be detected by a held tag reader, and tag information of the food is submitted to the EPCIS for processing, the EPCIS provides a shared platform, so that data can be shared and has the characteristic of openness, and although convenience is brought, information stored in the EPCIS is also easily tampered, and therefore, a data transmission system based on the internet of things is needed to solve the above problems.
Disclosure of Invention
The invention aims to provide a data transmission system and a data transmission method based on the Internet of things, so as to solve the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: a data transmission system based on the Internet of things comprises a food spot check detection module, a data security analysis module and a data traceability analysis module, the food spot check detection module is used for detecting and verifying food production information during food spot check, thereby judging whether the data information of the food is changed or not, ensuring that the user can safely and reassurantly use the food, the data security analysis module is used for reading and storing commodity information through the EPCIS middleware when the food is transported to a designated destination, different viewing authorities are set at different viewing ports to ensure that the information stored in the EPC is not easily attacked and ensure the safety of data, the data tracing to-be-analyzed module is used for acquiring the information in the nodes of the Internet of things, and the reason for the data modification is judged by calling and comparing the information of the production commodities in the same batch.
Further, the data security analysis module comprises a static data authentication unit, a dynamic data change unit, a data transmission unit, a data malicious modification unit and a checking authority authentication unit, wherein the static data authentication unit is used for acquiring the weight, temperature and shelf life information of different foods, the dynamic data change unit is used for judging warehousing information and ex-warehouse information of the foods so that a merchant can update the actual time of a production date according to the dynamic information of the foods to ensure the safety of the foods, the data transmission unit is used for transmitting the static data and the dynamic data to the system, the data malicious modification unit is used for judging whether the dynamic data is modified when detecting that the uploaded production date does not accord with the actual production date, thereby analyzing the reason why the data is modified, and the checking authority authentication unit is used for authenticating the authority of different merchants for acquiring the data from the system EPCIS, different people can check different data information, and therefore the safety of data in the system is guaranteed.
Further, the food spot check detection module comprises a food information acquisition unit, a keyword positioning position fuzzy unit, a fuzzy degree analysis unit, a production date background color comparison unit, an inventory production date comparison unit and a data abnormal alarm unit, wherein the food information acquisition unit is used for acquiring production date and quality guarantee period information on food packages and judging the safety of food according to the key information, the keyword positioning position fuzzy unit is used for analyzing the position of the production date on the food and judging whether the production date on the food becomes fuzzy by photographing, so that a user can accurately find the position of the production date and verify whether the current food is overdue, the fuzzy degree analysis unit is used for analyzing the fuzzy degree of the production date of the food and judging whether the fuzzy degree of the keyword influences the calculation of the quality guarantee period of the food, the food safety monitoring system comprises a production date background color comparison unit, an inventory production date comparison unit, a data abnormality alarming unit and a data abnormality alarming unit, wherein the production date background color comparison unit is used for detecting whether a background color of a production date is consistent with a package color or not so as to prevent a user from being capable of timely acquiring contents on the production date of food, the inventory production date comparison unit is used for detecting whether the production date of the food placed in inventory in the same batch is matched with the production date of the food, and judging whether the production date can be matched or not, and the data abnormality alarming unit is used for early warning the batch of food when the production date is detected to be not matched with the production date of the food in inventory.
Further, the data tracing analysis module comprises a node information acquisition unit, a quantity information comparison unit and a logistics information matching unit, wherein the node information acquisition unit is used for acquiring a food production origin place with abnormal production date and analyzing information of a manufacturer, the quantity information comparison unit is used for calling and comparing production quantity information of food with the latest batch of the batch with good machine condition, judging whether the production date of the abnormal food is fake or not, and the logistics information matching unit is used for acquiring logistics time of food delivery and calculating time from the food production origin place to a sales place, so that whether the production date of the food is changed or not is judged, and the safety of the food is ensured.
Further, the method comprises the following steps:
z01: the method comprises the steps that when dynamic data and static data of food are obtained through a data security analysis module and are uploaded to a system, whether the data change or not is detected in real time, so that the data are abnormal, different authorities of the system are set for different users, and the security of the data is guaranteed;
z02: detecting the production date of the food by a food spot check detection module to judge whether the keyword information in the production date of the food is fuzzy, comparing the keyword information with the production date information of the food in the same batch to judge whether the food is in the quality guarantee period, alarming the batch information of the food with higher fuzzy degree and incapable of judging the quality guarantee period of the food, and inquiring the tracing source of the modified food data;
z03: the data tracing analysis module is used for acquiring information of a same-batch food factory with abnormal data through the Internet of things node, judging quantity information of the food production of the same batch of food in the latest batch, calculating delivery time and arrival time of food logistics, and judging whether the abnormal food production date is artificially modified or is the reason of system network delay.
In step Z02, the step of determining that the food data is abnormal is as follows:
g1: acquiring the positions of production date and quality guarantee period on a food package, and acquiring photographing authority to photograph key data of the production date and the quality guarantee period;
g2: judging the fuzzy degree of the keywords in the picture, and judging whether the fuzzy positions of the keywords influence the safety of food;
g3: if the shelf life of the food is not influenced by the step G2, the safety of the food is high;
g4: if the quality guarantee period of the food is influenced by the step G2, the safety degree of the food is low, whether the food in the same batch has the food with higher similarity with the production date of the food is judged, if so, the information is obtained and compared; if the similarity is low, the current data is abnormal.
The content of the position information of the current keyword on the food package is set as
Refers to the content of the first-order key,
the last content of the displayed length key word includes the final length of the compared key word in the stock, and the content of the food package position information stored in the database is
Is the last bit of the displayed length key;
the detected fuzzy degree of the key word is
；
The influence degree D of the detected key words is as follows:
；
wherein:
it is referred to the degree of the initial influence,
the food information is the influence degree caused by the ith fuzzy bit in the food information, and the standard X shelf life;
when the keyword fuzzy degree is detected to be 1 and
comparing the content of each position on the keyword with the food keywords in the stock;
by the formula:
when the similarity between the ith keyword and the food keyword in the stock is detected to be close to 1, the similarity is high, the user can judge whether the current food is in the quality guarantee time, and when the similarity between the ith keyword and the food keyword in the stock is detected to be far from 1, the similarity is low, and whether the food is in the quality guarantee time cannot be judged.
In the step Z03, obtaining the information of the food factory in the same batch with abnormal food data in the node of the internet of things, and after GPS positioning detection, the coordinate positions of the food factory and the current selling node in the two-dimensional plane model are respectively (a)1,b1) And (a)2,b2) The number of machines in the food factory produced in good condition is N, and the number produced is
Supply goods to the current selling node, and the goods are all in fixed time T at each time1The speed at which the vehicle travels is v;
according to the formula:
the time for the vehicle to arrive at the selling node from the food factory is
Wherein
Delay time and error time of vehicles on the road;
when the quantity of the food on the same production date is detected
When it is shown as
The production date of the food quantity isWhen the time that the vehicle arrives at the selling node from the food factory is detected to be less than the time marked by the food production date, the production date of the food is shown to be fake, and the artificially modified food production date information is shown;
in step Z03, the steps of setting different permissions for each account in the EPCIS are as follows:
s1: acquiring information of a login EPCIS account, judging whether the login account exists in a database in the EPCIS, if not, not acquiring the information in the EPCIS, and if so, displaying different system contents according to account authority;
s2: if account information exists, judging whether data history information in different accounts comprises inheritance and inherited relationships, acquiring the times of the inheritance and inherited relationships in the history accounts, and setting the authority;
s3: when the account acquires the inheritance content and acquires other data within preset time, and the data is detected to have no inheritance relation with any data checked by the account, the account cannot acquire the information in the authority;
s4: when the account wants to acquire data without an inheritance relationship in step S3, a user with the inheritance relationship is required to perform authorization.
The production date refers to a specific time composition, and the shelf life of the food consists of specific time or months, wherein the specific time refers to the exact year, month and day, and the months are independent months.
Compared with the prior art, the invention has the following beneficial effects:
1. by detecting the production date in the food, whether the production date on the food is worn or not can be judged, and whether the consumer is influenced to calculate whether the food is in the quality guarantee period or not is judged according to the wear degree of the production date; when the date of the food is not within the shelf life, judging whether the production date of the same batch of the food can be found for a consumer to calculate the shelf life, deducing the production date of the food according to the same batch of the food to help judge whether the food is overdue or not, ensuring that the consumer can eat the food safely, and when the date similar to the food is not found in the same batch of the food, processing the food as abnormal data and analyzing the reason of fuzzy production date in a tracing way;
2. through a data security analysis module, commodity information is stored and analyzed through an EPCIS middleware, permissions are set to grant different account numbers, whether information checked by the account numbers comprises an inheritance relationship and an inherited relationship is judged, when the account has data contents with the inheritance relationship checked in historical data, the user can check the contents of the authority of the account numbers, the privacy of the information is ensured, when the existing account checks that the data checked with the history does not have the inheritance relationship, the account cannot check the contents of the data, the account with the inheritance relationship needs to be authorized to check the data, the privacy of the data is ensured, and the information in the EPCIS middleware is ensured not to be easily modified;
3. through the data traceability analysis module, information manufactured by the same batch of food factories can be acquired by calling information in the nodes of the Internet of things, the delivery time and the arrival time of food logistics are judged, the capability of the food factories in manufacturing food is judged and analyzed, whether the factories can produce food with corresponding quantity at corresponding time is judged, whether the food is artificially modified or the reason of network delay is analyzed, and when the production date of the food is artificially modified, early warning is carried out on the food.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
fig. 1 is a schematic diagram illustrating steps of a data transmission system and method based on the internet of things according to the present invention;
fig. 2 is a schematic diagram of module components of a data transmission system and method based on the internet of things.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in 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 by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-2, the present invention provides a technical solution:
a data transmission system based on the Internet of things comprises a food spot check detection module, a data security analysis module and a data traceability analysis module, the food spot check detection module is used for detecting and verifying food production information during food spot check, thereby judging whether the data information of the food is changed or not, ensuring that the user can safely and reassurantly use the food, the data security analysis module is used for reading and storing commodity information through the EPCIS middleware when the food is transported to a designated destination, different viewing authorities are set at different viewing ports to ensure that the information stored in the EPC is not easily attacked and ensure the safety of data, the data tracing to-be-analyzed module is used for acquiring the information in the nodes of the Internet of things, and the reason for the data modification is judged by calling and comparing the information of the production commodities in the same batch.
Further, the data security analysis module comprises a static data authentication unit, a dynamic data change unit, a data transmission unit, a data malicious modification unit and a checking authority authentication unit, wherein the static data authentication unit is used for acquiring the weight, temperature and shelf life information of different foods, the dynamic data change unit is used for judging warehousing information and ex-warehouse information of the foods so that a merchant can update the actual time of a production date according to the dynamic information of the foods to ensure the safety of the foods, the data transmission unit is used for transmitting the static data and the dynamic data to the system, the data malicious modification unit is used for judging whether the dynamic data is modified when detecting that the uploaded production date does not accord with the actual production date, thereby analyzing the reason why the data is modified, and the checking authority authentication unit is used for authenticating the authority of different merchants for acquiring the data from the system EPCIS, different people can check different data information, and therefore the safety of data in the system is guaranteed.
Further, the food spot check detection module comprises a food information acquisition unit, a keyword positioning position fuzzy unit, a fuzzy degree analysis unit, a production date background color comparison unit, an inventory production date comparison unit and a data abnormal alarm unit, wherein the food information acquisition unit is used for acquiring production date and quality guarantee period information on food packages and judging the safety of food according to the key information, the keyword positioning position fuzzy unit is used for analyzing the position of the production date on the food and judging whether the production date on the food becomes fuzzy by photographing, so that a user can accurately find the position of the production date and verify whether the current food is overdue, the fuzzy degree analysis unit is used for analyzing the fuzzy degree of the production date of the food and judging whether the fuzzy degree of the keyword influences the calculation of the quality guarantee period of the food, the food safety monitoring system comprises a production date background color comparison unit, an inventory production date comparison unit, a data abnormality alarming unit and a data abnormality alarming unit, wherein the production date background color comparison unit is used for detecting whether a background color of a production date is consistent with a package color or not so as to prevent a user from being capable of timely acquiring contents on the production date of food, the inventory production date comparison unit is used for detecting whether the production date of the food placed in inventory in the same batch is matched with the production date of the food, and judging whether the production date can be matched or not, and the data abnormality alarming unit is used for early warning the batch of food when the production date is detected to be not matched with the production date of the food in inventory.
Further, the data tracing analysis module comprises a node information acquisition unit, a quantity information comparison unit and a logistics information matching unit, wherein the node information acquisition unit is used for acquiring a food production origin place with abnormal production date and analyzing information of a manufacturer, the quantity information comparison unit is used for calling and comparing production quantity information of food with the latest batch of the batch with good machine condition, judging whether the production date of the abnormal food is fake or not, and the logistics information matching unit is used for acquiring logistics time of food delivery and calculating time from the food production origin place to a sales place, so that whether the production date of the food is changed or not is judged, and the safety of the food is ensured.
Further, the method comprises the following steps:
z01: the method comprises the steps that when dynamic data and static data of food are obtained through a data security analysis module and are uploaded to a system, whether the data change or not is detected in real time, so that the data are abnormal, different authorities of the system are set for different users, and the security of the data is guaranteed;
z02: detecting the production date of the food by a food spot check detection module to judge whether the keyword information in the production date of the food is fuzzy, comparing the keyword information with the production date information of the food in the same batch to judge whether the food is in the quality guarantee period, alarming the batch information of the food with higher fuzzy degree and incapable of judging the quality guarantee period of the food, and inquiring the tracing source of the modified food data;
z03: the data tracing analysis module is used for acquiring information of a same-batch food factory with abnormal data through the Internet of things node, judging quantity information of the food production of the same batch of food in the latest batch, calculating delivery time and arrival time of food logistics, and judging whether the abnormal food production date is artificially modified or is the reason of system network delay.
In step Z02, the step of determining that the food data is abnormal is as follows:
g1: acquiring the positions of production date and quality guarantee period on a food package, and acquiring photographing authority to photograph key data of the production date and the quality guarantee period;
g2: judging the fuzzy degree of the keywords in the picture, and judging whether the fuzzy positions of the keywords influence the safety of food;
g3: if the shelf life of the food is not influenced by the step G2, the safety of the food is high;
g4: if the quality guarantee period of the food is influenced by the step G2, the safety degree of the food is low, whether the food in the same batch has the food with higher similarity with the production date of the food is judged, if so, the information is obtained and compared; if the similarity is low, the current data is abnormal.
The content of the position information of the current keyword on the food package is set as
Refers to the content of the first-order key,
the last content of the displayed length key word includes the final length of the compared key word in the stock, and the content of the food package position information stored in the database is
The last content of the displayed length keyword is referred to, because the keyword is composed of numbers, each number needs to be compared with the numbers in the stock;
the detected fuzzy degree of the key word is
；
The influence degree D of the detected key words is as follows:
；
wherein:
it is referred to the degree of the initial influence,
the food information is the influence degree caused by the ith fuzzy bit in the food information, and the standard X shelf life;
when the keyword fuzzy degree is detected to be 1 and
for each of the keywordsComparing the content of the position with the food keywords in the stock;
by the formula:
when the similarity between the ith keyword and the food keyword in the stock is detected to be close to 1, the similarity is high, a user can judge whether the current food is in the quality guarantee time, and when the similarity between the ith keyword and the food keyword in the stock is detected to be far from 1, the similarity is low, and whether the food is in the quality guarantee time cannot be judged;
the influence degree of the current keyword can be judged by setting the fuzzy degree of the keyword, the set C-W is used for judging whether the production date of the food is within the preset time, and the cosine similarity formula is used for comparing whether the food with the production date of the food in the same batch exists or not by calculating the sim value, so that consumers can purchase the food at ease.
In the step Z03, the information of the food factory in the same batch with abnormal food data in the node of the internet of things is obtained, and through GPS positioning detection, the coordinate positions of the food factory and the current selling node in the two-dimensional plane model are respectively
And
the number of machines in the food factory produced in good condition is N, and the number produced is
Supply goods to the current selling node, and the goods are all in fixed time T at each time1The speed at which the vehicle travels is v;
according to the formula:
the time for the vehicle to arrive at the selling node from the food factory is
Wherein
Delay time and error time of vehicles on the road;
when the quantity of the food on the same production date is detected
When it is shown as
When the time that the vehicle arrives at the selling node from the food factory is detected to be less than the time marked by the food production date, the production date of the food is shown to be fake, and the artificially modified food production date information is shown;
by setting T2, the method utilizes T1,
By passing
The method is characterized in that extra time spent by a vehicle on a road during freight is taken, wherein T1 is calculated by analyzing the distance between positions through the positions of two fixed places, the arrival time of the vehicle is judged according to the speed per hour of the vehicle, the latest arrival time and the fastest arrival time of the vehicle can be judged through the calculation of the time, the latest time and the latest time set on the production date of the food can be analyzed according to the comparison between the latest arrival time and the time on the production date, and whether the production date on the food is modified or not is judged;
the time from the production date of the fresh food to the delivery date is the time for putting the fresh food into storage instead of the time for producing the fresh food, so that the actual production date of the food needs to be concerned all the time, and even more, some manufacturers can modify the time for putting the fresh food into storage in order to prolong the quality guarantee time and increase the freshness of the fresh food.
In step Z03, the steps of setting different permissions for each account in the EPCIS are as follows:
s1: acquiring information of a login EPCIS account, judging whether the login account exists in a database in the EPCIS, if not, not acquiring the information in the EPCIS, and if so, displaying different system contents according to account authority;
s2: if account information exists, judging whether data history information in different accounts comprises inheritance and inherited relationships, acquiring the times of the inheritance and inherited relationships in the history accounts, and setting the authority;
s3: when the account acquires the inheritance content and acquires other data within preset time, and the data is detected to have no inheritance relation with any data checked by the account, the account cannot acquire the information in the authority;
s4: when the account wants to acquire data without an inheritance relationship in step S3, a user with the inheritance relationship is required to perform authorization;
the above analysis of whether the account can read the information content by inheriting and inheriting the relationship is different from the way of using the blockchain, the blockchain is that the account can only obtain the content stored in the corresponding node but cannot obtain other content in the blockchain node, if the content in the blockchain node is to be obtained, the information can be obtained only under the consent of all the blockchain link points or the consent of a single blockchain link point, but the technical scheme is as follows: the number of times of calling account history viewing is judged to judge whether the account has the authority to judge whether the data viewed by the account has the inheritance relationship, when the node data viewed by the account has the inheritance relationship with a plurality of nodes, a plurality of data contents can be viewed, and the flexibility of setting of the node points is higher compared with that of the block chain;
meanwhile, the content of the set permission is different when the data is checked on the account, and the set permission is 'access permission and modification permission', so that the data content in the EPCIS system can not be modified, and the safety of the data is ensured;
when the user wants to acquire the content without the inherited relationship, the application times and time of the account are recorded, whether the account agrees to check or not is recorded, and other accounts have the right to refuse the account to check the information without the inherited relationship, so that the operation safety of the whole system is ensured.
The production date refers to a specific time composition, and the shelf life of the food consists of specific time or months, wherein the specific time refers to the exact year, month and day, and the months are independent months.
For example: the shelf life is 24 months or 2021 years, 12 months and 25 days.
Example 1: the content of the position information of the keywords on the food package is
The content of the first key word comprises the final length of the compared key word in the stock, and the content of the food package position information stored in the database is
According to detection, the fuzzy degree U =0 of the keywords in the food does not influence the judgment of the safety degree of the food, and whether the food is in the shelf life or not can be completely verified;
example 2: the content of the position information of the keywords on the food package is
The content of the first key word and the content of the food package position information stored in the database are
Through detection, the fuzzy degree of the keywords is U =1, the safety of food is affected, and data is abnormal;
the influence degree D of the detected key words is as follows:
；
detecting that the influence degree value of the keyword is maximum;
when the keyword fuzzy degree is detected to be 1 and
comparing the content of each position on the keyword with the food keywords in the stock;
by the formula:
when the similarity between the ith keyword and the food keyword in the stock is close to 1, the similarity is high, and the user can judge whether the current food is in the guarantee period.
Example 3: the content of the position information of the keywords on the food package is
,
The content of the first key word and the content of the food package position information stored in the database are
Through detection, the fuzzy degree of the keywords is U =1, the safety of food is affected, and data is abnormal;
the influence degree D of the detected key words is as follows:
；
detecting that the influence degree value of the keyword is maximum;
when the keyword fuzzy degree is detected to be 1 and
comparing the content of each position on the keyword with the food keywords in the stock;
by the formula:
when the result is far less than 1, the similarity is low, and whether the food is in the newspaper time or not cannot be judged, and the tracing of the food in the stock needs to be checked.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A data transmission system based on the Internet of things is characterized in that: the system comprises a food spot check detection module, a data security analysis module and a data traceability analysis module, wherein the food spot check detection module is used for detecting and verifying food production information when food spot check is carried out, the data security analysis module is used for reading and storing commodity information through an EPCIS middleware when food is transported to a specified destination, different viewing authorities are set at different viewing ports, the data traceability analysis module is used for acquiring information in nodes of the Internet of things, and the commodity information is compared by calling the commodity information produced in the same batch.
2. The internet of things-based data transmission system according to claim 1, wherein: the data security analysis module comprises a static data authentication unit, a dynamic data change unit, a data transmission unit, a data malicious modification unit and a checking authority authentication unit, wherein the static data authentication unit is used for acquiring the weight, temperature and shelf life information of different foods, the dynamic data change unit is used for judging warehousing information and ex-warehouse information of the foods, the data transmission unit is used for transmitting the static data and the dynamic data to the system, the data malicious modification unit is used for judging whether the dynamic data is modified or not when the uploaded production date is not consistent with the actual date, and the checking authority authentication unit is used for authenticating the authority of different merchants for acquiring the data from the system EPCIS.
3. The internet of things-based data transmission system according to claim 1, wherein: the food spot check detection module comprises a food information acquisition unit, a keyword positioning position fuzzy unit, a fuzzy degree analysis unit, a production date background color comparison unit, an inventory production date comparison unit and a data abnormal alarm unit, wherein the food information acquisition unit is used for acquiring production date and quality guarantee period information on food packages and judging the safety of food according to the key information, the keyword positioning position fuzzy unit is used for analyzing the position of the production date on the food, judging whether the production date on the food becomes fuzzy or not by photographing and verifying whether the current food is overdue or not, the fuzzy degree analysis unit is used for analyzing the fuzzy degree of the production date of the food and judging whether the fuzzy degree of the keyword influences the calculation of the quality guarantee period of the food, and the production date background color comparison unit is used for detecting whether the background color of the production date is consistent with the package color or not, the inventory production date comparing unit is used for detecting that the production dates of the food in the same batch are placed in the inventory and corresponding to the production dates of the food in the same batch, and judging whether the production dates can be matched or not, and the data abnormality alarming unit is used for early warning the batch of food when detecting that the production dates cannot be matched with the production dates of the food in the inventory.
4. The internet of things-based data transmission system according to claim 1, wherein: the data tracing analysis module comprises a node information acquisition unit, a quantity information comparison unit, a GPS positioning unit, a two-dimensional plane model display unit and a logistics information matching unit, the node information acquisition unit is used for acquiring a food production origin with abnormal production date, and analyzing the information of the manufacturer, the quantity information comparison unit is used for calling and comparing the production quantity information of the food with the latest batch of the food with good machine condition to judge whether the production date of the abnormal food is counterfeit or not, the GPS positioning unit is used for detecting the position of the vehicle during transportation, the two-dimensional plane model display unit is used for displaying the transportation position of the vehicle on a map in real time, the logistics information matching unit is used for acquiring the logistics time of food delivery and calculating the time from a food production manufacturing place to a store.
5. A data transmission method based on the Internet of things is characterized in that: the method comprises the following steps:
z01: the method comprises the steps that when dynamic data and static data of food are obtained through a data security analysis module and are uploaded to a system, whether the data change or not is detected in real time, so that the data are abnormal, different authorities of the system are set for different users, and the security of the data is guaranteed;
z02: detecting the production date of the food by a food spot check detection module to judge whether the keyword information in the production date of the food is fuzzy, comparing the keyword information with the production date information of the food in the same batch to judge whether the food is in the quality guarantee period, alarming the batch information of the food with higher fuzzy degree and incapable of judging the quality guarantee period of the food, and inquiring the tracing source of the modified food data;
z03: the data tracing analysis module is used for acquiring information of a same-batch food factory with abnormal data through the Internet of things node, judging quantity information of the food production of the same batch of food in the latest batch, calculating delivery time and arrival time of food logistics, and judging whether the abnormal food production date is artificially modified or is the reason of system network delay.
6. The data transmission method based on the internet of things as claimed in claim 5, wherein: in step Z02, the step of determining that the food data is abnormal is as follows:
g1: acquiring the positions of production date and quality guarantee period on a food package, and acquiring photographing authority to photograph key data of the production date and the quality guarantee period;
g2: judging the fuzzy degree of the keywords in the picture, and judging whether the fuzzy positions of the keywords influence the safety of food;
g3: if the shelf life of the food is not influenced by the step G2, the safety of the food is high;
g4: if the quality guarantee period of the food is influenced by the step G2, the safety degree of the food is low, whether the food in the same batch has the food with higher similarity with the production date of the food is judged, if so, the information is obtained and compared; if the similarity is low, the current data is abnormal.
7. The data transmission method based on the internet of things as claimed in claim 6, wherein: the content of the position information of the keywords on the food package is
Refers to the content of the first-order key,
the last content of the displayed length key word includes the final length of the compared key word in the stock, and the content of the food package position information stored in the database is
The last bit of the displayed length of the keyword is referred to;
the detected fuzzy degree of the key word is
；
The influence degree D of the detected key words is as follows:
wherein:
it is referred to the degree of the initial influence,
the influence degree caused by the ith fuzzy in the food information, X standard shelf life, wherein
When the keyword fuzzy degree is detected to be 1 and
comparing the content of each position on the keyword with the food keywords in the stock;
by the formula:
when the similarity between the ith keyword and the food keyword in the stock is detected to be close to 1, the similarity is high, the user can judge whether the current food is in the quality guarantee time, and when the similarity between the ith keyword and the food keyword in the stock is detected to be far from 1, the similarity is low, and whether the food is in the quality guarantee time cannot be judged.
8. The data transmission method based on the internet of things as claimed in claim 5, wherein: in the step Z03, obtaining the information of the food factory in the same batch with abnormal food data in the node of the internet of things, and after GPS positioning detection, the coordinate positions of the food factory and the current selling node in the two-dimensional plane model are respectively (a)1,b1) And (a)2,b2) The number of machines in the food factory produced in good condition is N, and the number produced is
Supplying goods to the current selling node, wherein the running speed of the vehicle is v;
according to the formula:
the time for the vehicle to arrive at the selling node from the food factory is
Wherein
Delay time and error time of vehicles on the road;
when the quantity of the food on the same production date is detected
When it is shown as
Is in the production date of the food, and when the time of the vehicle arriving at the selling node from the food factory is detected to be less than the time marked by the production date of the food, the production date of the food is shown to be fake, and the food is shown to be artificially modifiedFood production date information.
9. The data transmission method based on the internet of things as claimed in claim 6, wherein: in step Z03, the steps of setting different permissions for each account in the EPCIS are as follows:
s1: acquiring information of a login EPCIS account, judging whether the login account exists in a database in the EPCIS, if not, not acquiring the information in the EPCIS, and if so, displaying different system contents according to account authority;
s2: if account information exists, judging whether data history information in different accounts comprises inheritance and inherited relationships, acquiring the times of the inheritance and inherited relationships in the history accounts, and setting the authority;
s3: when the account acquires the inheritance content and acquires other data within preset time, and the data is detected to have no inheritance relation with any data checked by the account, the account cannot acquire the information in the authority;
s4: when the account wants to acquire data without an inheritance relationship in step S3, a user with the inheritance relationship is required to perform authorization.
10. The data transmission method based on the internet of things as claimed in claim 1, wherein: the production date refers to a specific time composition, and the shelf life of the food consists of specific time or months, wherein the specific time refers to the exact year, month and day, and the months are independent months.
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| CN202111124382.5A CN113837773A (en) | 2021-09-24 | 2021-09-24 | Data transmission system and method based on Internet of things |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115438754A (en) * | 2022-11-08 | 2022-12-06 | 湖南鼎誉检验检测股份有限公司 | Food safety detection method, system and storage medium |
| CN117372051A (en) * | 2023-12-08 | 2024-01-09 | 龙岩市新罗区鞠翰食品有限公司 | Eight delicacies cake food processing information management system that traces to source |
-
2021
- 2021-09-24 CN CN202111124382.5A patent/CN113837773A/en not_active Withdrawn
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115438754A (en) * | 2022-11-08 | 2022-12-06 | 湖南鼎誉检验检测股份有限公司 | Food safety detection method, system and storage medium |
| CN117372051A (en) * | 2023-12-08 | 2024-01-09 | 龙岩市新罗区鞠翰食品有限公司 | Eight delicacies cake food processing information management system that traces to source |
| CN117372051B (en) * | 2023-12-08 | 2024-03-08 | 龙岩市新罗区鞠翰食品有限公司 | Eight delicacies cake food processing information management system that traces to source |
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