Intelligent access system and method for reserved sample cabinet based on block chain

Abstract

The invention relates to the technical field of food reserved sample intelligent management, and discloses a reserved sample cabinet intelligent access system and method based on a block chain, and the system comprises a reserved sample food sample information processing module, a reserved sample food sample management module and a reserved sample food sampling management module. According to sample storage food object identity information, in combination with an intelligent identification algorithm and sample storage food standard sample storage scheme information based on big data storage, sample storage food sample storage scheme intelligent planning is carried out, and a food sample storage scheme is finely and scientifically planned based on sample storage food feature types. According to the sample storage process record information of the reserved sample food, the identity information of the food sampling administrator and the block chain technology, the storage and sampling information of the reserved sample food is dynamically and reliably recorded, the whole storage and sampling process information of the reserved sample food is intelligently and safely recorded, and the applicability and safety of the reserved sample food management are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent management of food sample retention, and specifically to a blockchain-based intelligent storage and access system and method for sample retention cabinets. Background Art

[0002] Food sampling is an important part of food safety management, mainly used to trace food safety issues, deal with disputes or cooperate with regulatory investigations. The management of food samples mainly includes the following aspects: sample scope, sample quantity, sample time, sample container, and sample management; the sample scope includes school canteens, nursing home canteens, medical institution canteens, central kitchens, collective dining distribution units, construction site canteens, and catering service providers; sample quantity: the sample quantity of each food must be sufficient for inspection and testing, and no less than 125 grams23; sample time: sampled food should be refrigerated in special refrigeration equipment for at least 48 hours24; sample container: sampled food should be placed separately in sealed special containers that have been cleaned and disinfected to prevent contamination between samples24; sample management: a dedicated person should be responsible for sample retention and record detailed information, including the date, time, product name, and person who retained the sample; the existing food sample storage and retrieval process relies entirely on the sample administrator to classify the sampled food, formulate the sample plan, and record the sample information. It cannot achieve efficient and intelligent management of food sample operations, nor can it achieve safe and efficient recording of food sample information, reducing the efficiency and safety of food sample management.

[0003] The Chinese invention patent with announcement number CN118333344B discloses a food safety supervision system based on a cloud platform and the Internet of Things. By recording the information of food entering the warehouse, the optimal storage parameters of the food to be stored are determined and the food is stored in different areas; the information of food leaving the warehouse is recorded, and combined with the food knowledge graph, food leaving the warehouse prompt information is generated; the optimal cleaning parameters are determined, and the automatic cleaning equipment is controlled to clean the food to be processed, and color image information of multiple processing areas is obtained to generate food processing prompt information; the color images of food samples are recorded, and color image information of the sales area is obtained to generate food sample prompt information; the operation information of the canteen is obtained, a disinfection plan is formulated, and the disinfection robot is controlled to execute; however, the above technical solutions cannot realize the intelligent control of the food sampling process and the safe recording of the sample information. Summary of the Invention

[0004] (1) Technical problems solved

[0005] In order to solve the problem that the sample storage and retrieval process of the above-mentioned existing food sampling operation completely relies on the sample administrator to classify the sample food, formulate the sample plan, and record the sample information, it cannot realize efficient and intelligent management of the food sampling operation, nor can it realize safe and efficient recording of the food sample information, which reduces the efficiency and safety of food sampling management, the above purpose is to accurately judge the sample storage authority of the food sample administrator, independently generate the identity information of the sample food object, intelligently plan the sample storage plan information of the sample food, accurately execute the sample storage operation of the sample food, scientifically construct the sample storage record information of the sample food, accurately judge the sampling authority of the food sample administrator, obtain the sample storage record information of the sample food, accurately execute the sample sampling operation of the sample food, and scientifically construct the storage and retrieval record information of the sample food.

[0006] (2) Technical solution

[0007] The present invention is implemented through the following technical solution: a blockchain-based intelligent storage and access method for sample cabinets, the method comprising the following steps:

[0008] S1. Collect the identity data of the food sample storage manager;

[0009] S2. Performing sample storage authority determination processing on the food sample storage administrator based on the identity characteristic data of the food sample storage administrator and the identity characteristic data of the food sample registration administrator, generating sample storage authority determination data for the food sample storage administrator, and prompting the food sample storage administrator that the food sample storage administrator does not have sample storage authority if the administrator does not have sample storage authority;

[0010] S3. When the sample storage authority is granted, collect the sample storage characteristic data of the retained food and perform identity information generation processing on the retained food. Generate the identity characteristic data of the retained food object and perform sample storage plan processing on the retained food in the sample cabinet with the retained food standard sample storage plan data. Generate the retained food sample storage plan data and perform the retained food sample storage operation.

[0011] S4. Processing information records during the food sample storage phase based on the identity data of the food sample storage administrator and the identity data of the sampled food object to construct data recording the food sample storage process;

[0012] S5. Collect the identity characteristic data of the food sampling administrator and perform sampling authority determination processing on the food sampling administrator together with the identity characteristic data of the food sampling registration administrator to generate sampling authority determination data of the food sampling administrator. If the food sampling administrator does not have sampling authority, it is prompted that the food sampling administrator does not have sampling operation authority;

[0013] S6. When the sampling authority is granted, obtain the sample storage process record data of the reserved food and perform the reserved food sampling operation;

[0014] S7. Perform information recording processing on the stage of food sample storage and sampling according to the sample storage process record data and the identity characteristic data of the food sampling administrator to construct the sample storage and sampling process record data.

[0015] Preferably, the steps for processing the food sample storage administrator's identity characteristic data are as follows:

[0016] S11. Collect online the identity feature information of the manager who stores food samples in the sample cabinet during the food sampling operation through the sample cabinet control panel, and generate food sample manager identity feature data I, wherein the food sample manager identity feature data includes the name text information and facial image information of the food sample manager.

[0017] Preferably, the sample storage authority of the food sample storage administrator is judged based on the identity feature data of the food sample storage administrator and the identity feature data of the food sample registration administrator to generate sample storage authority judgment data of the food sample storage administrator. When there is no sample storage authority, the operation steps of prompting the food sample storage administrator that there is no sample storage operation authority are as follows:

[0018] S21. Establish the identity characteristic data matrix Y = (y1,…,y a ,…,y α ), a=1,2,3,…,α; where y a represents the identity characteristic data of the food sample registration administrator corresponding to the a-th food sample administrator, and α represents the maximum number of food sample administrators; the identity characteristic data of the food sample registration administrator represents the identity characteristic information of the food sample administrator registered in the sample cabinet control panel;

[0019] S22, using XGBoost search algorithm to compare the food sample storage administrator identity feature data I with the food sample registration administrator identity feature data matrix Y a Perform identity feature information matching and generate food sample storage authority judgment data Y based on the identity feature information matching results cunyang ;

[0020] When I and y a If the identity feature information is matched successfully, it means that the manager who performs food sampling is a food sampling registration manager, then the food sampling manager's sample storage authority judgment data Y is output. cunyang Have the permission to store samples;

[0021] When I and y a If the identity feature information is not matched successfully, it means that the manager who performs food sampling is not a registered food sampling manager, then the food sampling manager's sample storage authority judgment data Y is output.cunyang The user does not have the permission to store samples, and the sample cabinet control panel outputs a prompt that the food sample administrator does not have the permission to store samples.

[0022] Preferably, when there is sample storage authority, the sample storage characteristic data of the reserved food is collected and the identity information of the reserved food is generated, the identity characteristic data of the reserved food object is generated and the sample storage plan planning processing of the reserved food in the sample cabinet is performed with the standard sample storage plan data of the reserved food, the sample storage plan planning data of the reserved food is generated and the operation steps of performing the sample storage operation of the reserved food are as follows:

[0023] S31, when the food sample administrator stores the sample authority judgment data Y cunyang When the user has the sample storage permission, the sample storage feature text information of the sampled food in the food sample storage operation is collected online through the sample storage cabinet control panel, and the sample storage feature data O of the sampled food is generated. The sample storage feature data of the sampled food includes the weight text information of the sampled food, the sample storage time text information, the dish text information and the meal number text information;

[0024] S32, using the sample retention date and the daily food sample retention operation sequence number to perform the sample food identity information combination identification processing on the sample food storage feature data O, and generate the sample food object identity feature data O. shenfen The identity characteristic data of the sample food object includes the sample characteristic information and the sample identification number of the sample food;

[0025] S33, establish the data matrix Q = (q1, ..., q b ,…,q β ), b=1,2,3,…,β; where q b represents the standard storage plan data for retained food corresponding to the b-th type of food retained sample feature combination type, β represents the maximum number of food retained sample feature combination types; the food retained sample feature combination type represents an index data type formed by combining the weight information of the retained food and the dish information through data for searching for the standard storage plan information for the retained food; the standard storage plan data for retained food represents the optimal retained food storage plan information set for different types of retained food combination features, and the standard storage plan data for retained food includes the storage location information, storage temperature information, and storage humidity information of the retained food in the sample cabinet;

[0026] S34, the identity feature data of the sample food object O shenfen The standard sample storage plan data q of the sample food standard storage plan data matrix Q b Perform food sample feature keyword matching to search for the identity feature data of the sampled food object. shenfenThe corresponding standard sample storage plan data q b , and generate sample food storage plan data q through data identification mubiao ; Execute and generate the sample food storage plan planning data q mubiao The specific steps are as follows:

[0027] S341, initializing parameters and updating the maximum number of iterations T of the algorithm;

[0028] S342, initializing the sample storage plan to identify the position of the seagull population, and the sample storage plan to identify the position of the seagull population updated in the search space of the data matrix Q of the sample storage plan for the reserved food standard;

[0029] S343, calculate all the standard sample storage plan data q of the food sample standard storage plan data matrix Q according to the food sample feature keyword matching. b and the identity characteristic data of the sample food object shenfen The fitness value is retained in the search space of the sample food standard storage plan data matrix Q and the sample food object identity feature data O shenfen The standard sample storage plan data q of the reserved food with the largest fitness value b The global optimal position of

[0030] S344, migration, global search: There are three main steps in the sample scheme to identify the migration behavior of seagulls. The first is to meet the conditions of avoiding collisions between seagulls identified by different sample schemes in the search space of the sample food standard sample scheme data matrix Q; the second is to match the food sample feature keywords in the search space of the sample food standard sample scheme data matrix Q with the sample food object identity feature data O shenfen The matching sample food standard storage sample plan data q b The optimal position direction; third according to the identity characteristic data of the food object O shenfen The best matching sample standard storage plan data q b Move to the new position in the direction of the best position;

[0031] S3441, calculating the new position R'(t) of the sample storage scheme identification seagull in the search space of the sample storage scheme data matrix Q without colliding with the adjacent sample storage scheme identification seagull; R'(t) = ω × R(t), Wherein R(t) represents the current position of the sample identification seagull in the search space of the sample storage plan data matrix Q of the sample storage plan of the sample food, t represents the current iteration number; ω represents the movement behavior of the sample identification seagull in the search space of the sample storage plan data matrix Q of the sample storage plan of the sample food; ξ represents the function that controls the frequency of change of ω, and T represents the maximum number of iterations;

[0032] S3442, according to the food sample feature keyword matching calculation, in the search space of the sample food standard storage plan data matrix Q and the sample food object identity feature data O shenfen The matching sample food standard storage sample plan data q b The optimal position direction Φ(t); Φ(t)=Θ×(R best (t)-R(t)), Θ=2×ω 2 ×ψ, where R best (t) represents the search space of the sample food standard storage sample plan data matrix Q, and searches for the identity feature data O of the sample food object according to the food sample feature keyword matching. shenfen The matching sample food standard storage sample plan data q b The current best position of , Θ represents a random number that balances global and local search capabilities, and ψ represents a random number in the interval [0,1];

[0033] S3443, according to the identity characteristic data of the sample food object shenfen The best matching sample standard storage plan data q b The direction of the optimal position is moved to the new position Λ(t), Λ(t) = |R'(t) + Φ(t)|, that is, according to the direction of the optimal position, the identity feature data O of the sample food object is searched in the search space of the sample food standard storage plan data matrix Q according to the food sample feature keyword matching. shenfen The matching sample food standard storage sample plan data q b new location;

[0034] S345. Attack prey, local search, sample storage scheme identification: When the seagull attacks the prey in the search space of the standard sample storage scheme data matrix Q of the retained food sample, it performs a spiral motion in the air. The sample storage scheme identifies the new position Λ'(t) of the seagull after attacking the prey, Λ'(t)=Λ(t)+R best (t), the sample storage scheme identification seagull searches for the identity feature data O of the sample food object in the search space of the sample storage scheme data matrix Q according to the food sample feature keyword matching. shenfen The matching sample food standard storage sample plan data q b of prey;

[0035] S346: Determine whether the maximum number of iterations is met, and then output the identity feature data of the sample food object. shenfen The matching sample food standard storage sample plan data q b ; If not satisfied, return to step S343;

[0036] S347, the identity characteristic data of the sample food object outputted in step S346 shenfen The matching sample food standard storage sample plan data q b And generate sample food storage plan data q through data identification mubiao ;

[0037] S35, the sample cabinet control terminal plans data q according to the sample storage plan mubiao The industrial robot is controlled in an orderly manner to place the retained food samples into the designated storage location in the sample cabinet, and the operating status of the sample cabinet is adjusted to perform the retained food sample storage operation.

[0038] Preferably, the information recording process of the sampled food storage stage is performed based on the identity characteristic data of the food sample storage administrator and the identity characteristic data of the sampled food object, and the operation steps for constructing the sampled food storage process record data are as follows:

[0039] S41, the food sample manager identity feature data I, the sample food object identity feature data O shenfen The blockchain storage method is used to construct the sample storage process record data H through data combination identification. cunyang , where H cunyang =(I,O shenfen ).

[0040] Preferably, the steps of collecting the identity feature data of the food sampling administrator and performing sampling authority judgment processing on the food sampling administrator together with the identity feature data of the food sampling registration administrator to generate sampling authority judgment data of the food sampling administrator are as follows:

[0041] S51. Collecting identity feature information of a manager who takes food samples and places them into the sample cabinet during a food sampling operation online through the sample cabinet control panel, and generating food sampling manager identity feature data J, wherein the food sampling manager identity feature data J includes the name text information and facial image information of the food sampling manager;

[0042] S52, using XGBoost search algorithm to compare the food sampling administrator identity feature data J with the food sample registration administrator identity feature data matrix Y.a Perform identity feature information matching and generate food sample administrator sampling authority judgment data P based on the identity feature information matching results. quyang ;

[0043] When J and y a If the identity feature information is matched successfully, it means that the manager who performs food sampling is a registered food sampling manager, and the sampling authority judgment data P of the food sampling manager is output. quyang To have sampling authority;

[0044] When J and y a If the identity feature information is not matched successfully, it means that the manager who performs the food sampling is not a registered food sampling manager, then the sampling authority judgment data P of the food sampling manager is output. quyang The user has no sampling authority, and the sample cabinet control panel outputs a prompt that the food sample administrator has no sampling operation authority.

[0045] Preferably, when the sampling authority is granted, the steps for obtaining the sample storage process record data of the reserved food and performing the reserved food sampling operation are as follows:

[0046] S61, when the food sample administrator's sampling authority determines data P quyang When the sampling authority is granted, the food sample management personnel obtains the sample storage process record data H of the sample storage cabinet control panel. cunyang ;

[0047] S62, the sample cabinet control terminal obtains the sample storage process record data H of the sample food cunyang Control the industrial robot to take out the reserved food samples from the designated storage location in the sample cabinet and perform the reserved food sampling operation.

[0048] Preferably, the information recording and processing of the sample food storage and sampling stage is performed based on the sample food storage process record data and the identity characteristic data of the food sampling administrator, and the operation steps for constructing the sample food storage and sampling process record data are as follows:

[0049] S71, obtaining the food sample storage process record data H cunyang , the identity characteristic data J of the food sampling administrator;

[0050] S72, recording the sample storage process data H cunyang The food sampling administrator's identity feature data J is stored in a blockchain manner and the sample storage and sampling process record data G is constructed through data combination identification. quyang , where G quyang =(J,H cunyang ).

[0051] A blockchain-based intelligent storage and access system for sample cabinets, used to implement the blockchain-based intelligent storage and access method for sample cabinets, the system including a sample food storage information processing module, a sample food storage management module, and a sample food sampling management module;

[0052] The sample food storage information processing module includes a food storage administrator information collection unit, a food sample registration administrator information storage unit, a food sample administrator storage authority judgment unit, a sample food storage information collection unit, and a sample food object identity information generation unit;

[0053] The food sample storage administrator information collection unit collects the identity characteristic data of the food sample storage administrator through the sample storage cabinet control panel; the food sample registration administrator information storage unit is used to store the identity characteristic data of the food sample registration administrator; the food sample storage authority judgment unit performs a sample storage authority judgment process on the food sample storage administrator based on the identity characteristic data of the food sample storage administrator and the identity characteristic data of the food sample registration administrator, and generates the sample storage authority judgment data of the food sample storage administrator; the sample storage information collection unit collects the sample storage characteristic data of the sampled food through the sample storage cabinet control panel; the sampled food object identity information generation unit performs a sample storage information generation process on the sampled food based on the sample storage characteristic data of the sampled food, and generates the identity characteristic data of the sampled food object;

[0054] The sample storage management module includes a sample storage plan storage unit for sample food standards, a sample storage plan planning unit for sample food, a sample storage operation execution unit for sample food, and a sample storage record information construction unit for sample food;

[0055] The standard storage plan storage unit for retained food samples is used to store standard storage plan data for retained food samples; the storage plan planning unit for retained food samples performs storage plan processing for retained food samples in the sample cabinet based on the identity feature data of the retained food samples and the standard storage plan data for retained food samples, and generates storage plan planning data for retained food samples; the storage operation execution unit for retained food samples performs storage operations for retained food samples based on the storage plan planning data for retained food samples in combination with the sample cabinet control terminal, the industrial robot and the sample cabinet; the storage record information construction unit for retained food samples performs information record processing at the storage stage of retained food samples based on the identity feature data of the food storage administrator and the identity feature data of the stored food samples in combination with blockchain technology, and constructs storage process record data for retained food samples;

[0056] The sample food sampling management module includes a food sampling administrator information collection unit, a food sample administrator sampling authority judgment unit, a sample food storage record information acquisition unit, a sample food sampling operation execution unit, and a sample food storage and sampling record information construction unit;

[0057] The food sampling administrator information collection unit collects the identity characteristic data of the food sampling administrator through the sample cabinet control panel; the food sample administrator sampling authority judgment unit performs sampling authority judgment processing on the food sample administrator based on the identity characteristic data of the food sampling administrator and the identity characteristic data of the food sample registration administrator, and generates food sample administrator sampling authority judgment data; the sample food storage record information acquisition unit is used to obtain the sample food storage process record data; the sample food sampling operation execution unit performs the sample food sampling operation based on the sample food storage process record data in combination with the sample cabinet control terminal, industrial robot and sample cabinet; the sample food storage and sampling record information construction unit performs information record processing on the sample food storage and sampling stage based on the sample food storage process record data, the food sampling administrator identity characteristic data and blockchain technology, and constructs the sample food storage and sampling process record data.

[0058] (3) Beneficial effects

[0059] The present invention provides a blockchain-based intelligent storage and access system and method for sample cabinets. It has the following beneficial effects:

[0060] 1. Accurately obtain the identity information of food sample storage administrators online through the sample cabinet control panel, providing real data support for intelligent and efficient management of food samples; independently supervise the sample storage authority of food sample storage administrators based on the identity information of food sample storage administrators combined with intelligent search algorithms and scientifically stored food sample registration administrator identity information, realize scientific supervision of the sample storage process of food sample operations, and improve the quality of food sample management; use the sample cabinet control panel to obtain the sample storage feature information of sampled food online and combine data processing to scientifically construct the identity feature information of sampled food objects, realize the efficient establishment of sampled food object information standards, and improve the scientific nature of food sample information management.

[0061] 2. By intelligently planning the storage plan for retained food samples based on the identity information of the sampled food objects in combination with intelligent recognition algorithms and standard storage plan information for retained food samples based on big data storage, it is possible to achieve refined and scientific planning of food storage plans based on the characteristic types of retained food samples, thereby improving the safety and accuracy of food samples; based on the planning information of the storage plan for retained food samples, combined with the control terminal of the sample cabinet, industrial robots and the sample cabinet, the storage operation of retained food samples is performed independently and reliably, and at the same time, the storage information of retained food samples is recorded safely and reliably in combination with blockchain technology, thereby achieving traceability of the storage information of retained food samples and improving the applicability of food sample management.

[0062] 3. Accurately obtain the identity information of the food sampling administrator through the sample cabinet control panel and dynamically supervise the sampling rights of the food sample administrator in combination with the identity information of the food sample registration administrator; accurately obtain the sample storage process record information of the sampled food and combine it with the sample cabinet control terminal, industrial robot and sample cabinet to quickly and accurately perform the sample food sampling operation, thereby improving the efficiency and safety of sampled food; dynamically and reliably record the sample storage and sampling information of the sampled food based on the sample storage process record information and the identity information of the food sampling administrator in combination with blockchain technology, thereby realizing intelligent and safe recording of the entire process information of food sample storage and sampling, thereby improving the applicability and safety of food sample management. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 A schematic diagram of the module of the blockchain-based sample cabinet intelligent access system provided by the present invention;

[0064] Figure 2 Flowchart of the blockchain-based intelligent storage and access method for sample cabinets provided by the present invention. DETAILED DESCRIPTION

[0065] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0066] The embodiments of the blockchain-based sample cabinet intelligent access system and method are as follows:

[0067] Example 1:

[0068] See also Figure 1 - Figure 2 , a blockchain-based intelligent storage and access method for sample cabinets, the method includes the following steps:

[0069] S1. Collect the identity data of the food sample storage manager;

[0070] S2. Determine the sample storage authority of the food sample storage administrator based on the identity characteristic data of the food sample storage administrator and the identity characteristic data of the food sample registration administrator, and generate sample storage authority determination data for the food sample storage administrator. If the food sample storage administrator does not have sample storage authority, it will be prompted that the food sample storage administrator does not have sample storage operation authority;

[0071] S3. When the sample storage authority is granted, collect the sample storage characteristic data of the retained food and perform identity information generation processing on the retained food. Generate the identity characteristic data of the retained food object and perform sample storage plan processing on the retained food in the sample cabinet with the retained food standard sample storage plan data. Generate the retained food sample storage plan data and perform the retained food sample storage operation.

[0072] S4. Processing information records during the food sample storage phase based on the identity data of the food sample storage administrator and the identity data of the sampled food object, to construct data on the food sample storage process record;

[0073] S5. Collect the identity characteristic data of the food sampling administrator and perform sampling authority determination processing on the food sampling administrator together with the identity characteristic data of the food sampling registration administrator to generate sampling authority determination data of the food sampling administrator. If the food sampling administrator does not have sampling authority, it is prompted that the food sampling administrator does not have sampling operation authority;

[0074] S6. When sampling authority is granted, obtain the sample storage process record data of the retained food and perform the sample collection operation;

[0075] S7. Process the information records of the food sample storage and sampling stage according to the sample storage process record data and the identity feature data of the food sampling administrator to construct the sample storage and sampling process record data.

[0076] For further information, see Figure 1 - Figure 2 The steps for obtaining the identity data of the food sample manager are as follows:

[0077] S11. Collect the identity characteristic information of the manager who stores the food samples in the sample cabinet during the food sampling operation online through the sample cabinet control panel, and generate food sample manager identity characteristic data I. The food sample manager identity characteristic data includes the name text information and facial image information of the food sample manager.

[0078] The sample storage authority of the food sample storage administrator is judged based on the identity feature data of the food sample storage administrator and the identity feature data of the food sample registration administrator, and the sample storage authority judgment data of the food sample storage administrator is generated. If there is no sample storage authority, the operation steps to prompt the food sample storage administrator that there is no sample storage operation authority are as follows:

[0079] S21. Establish the identity characteristic data matrix Y = (y1,…,y a ,…,y α ), a=1,2,3,…,α; where y arepresents the identity characteristic data of the food sample registration administrator corresponding to the a-th food sample administrator, α represents the maximum number of food sample administrators; the identity characteristic data of the food sample registration administrator represents the identity characteristic information of the food sample administrator registered in the sample cabinet control panel;

[0080] S22, using XGBoost search algorithm to compare the food sample storage manager identity feature data I with the food sample registration manager identity feature data matrix Y. a Perform identity feature information matching and generate food sample storage authority judgment data Y based on the identity feature information matching results cunyang ;

[0081] When I and y a If the identity feature information is matched successfully, it means that the manager who performs food sampling is a food sampling registration manager, then the food sampling manager's sample storage authority judgment data Y will be output. cunyang Have the permission to store samples;

[0082] When I and y a If the identity feature information is not matched successfully, it means that the manager who performs food sampling is not a registered food sampling manager, then the food sampling manager's storage authority judgment data Y is output. cunyang The user does not have the permission to store samples, and the sample cabinet control panel outputs a prompt that the food sample administrator does not have the permission to store samples.

[0083] Through the food sample storage administrator information collection unit, the sample cabinet control panel is used to accurately obtain the identity information of the food sample storage administrator online, providing real data support for the intelligent and efficient management of food samples; the food sample storage administrator sample storage authority judgment unit conducts autonomous supervision of the food sample storage authority based on the food sample storage administrator identity information combined with the intelligent search algorithm and the scientifically stored food sample registration administrator identity information, thereby realizing scientific supervision of the sample storage process of food sample operations and improving the quality of food sample management.

[0084] For further information, see Figure 1 - Figure 2 When there is sample storage authority, the sample characteristic data of the retained food is collected and the identity information of the retained food is generated and processed. The identity characteristic data of the retained food object is generated and the sample storage plan of the retained food in the sample cabinet is planned with the retained food standard sample storage plan data. The steps for generating the retained food sample storage plan data and executing the retained food sample storage operation are as follows:

[0085] S31, when the food sample administrator stores the sample authority judgment data Y cunyangWhen the user has the sample storage permission, the sample storage feature text information of the sampled food in the food sample storage operation is collected online through the sample storage cabinet control panel, and the sample storage feature data O of the sampled food is generated. The sample storage feature data of the sampled food includes the weight text information of the sampled food, the sample storage time text information, the dish text information and the meal number text information of the sampled food;

[0086] S32, using the sample retention date and the daily food sample retention operation sequence number to perform the sample food identity information combination identification processing on the sample food storage feature data O, and generate the sample food object identity feature data O. shenfen The identity characteristic data of the sampled food object includes the sample characteristic information and sample identification number of the sampled food;

[0087] S33, establish the data matrix Q = (q1, ..., q b ,…,q β ), b=1,2,3,…,β; where q b represents the standard storage plan data for retained food corresponding to the bth type of food retained sample feature combination type, β represents the maximum number of food retained sample feature combination types; the food retained sample feature combination type represents an index data type formed by combining the weight information of the retained food and the dish information, which is used to search for the standard storage plan information for the retained food; the standard storage plan data for retained food represents the optimal retained food storage plan information set for different types of retained food combination features, and the standard storage plan data for retained food includes the storage location information, storage temperature information, and storage humidity information of the retained food in the sample cabinet;

[0088] S34, the identity feature data of the sample food object O shenfen The data matrix Q of the standard sample storage plan for retained food is the data q of the standard sample storage plan for retained food b Perform keyword matching on food sample characteristics to search for identity feature data of sampled food objects. shenfen Corresponding food sample standard storage plan data q b , and generate sample food storage plan data q through data identification mubiao ; Execute and generate sample food storage plan data q mubiao The specific steps are as follows:

[0089] S341, initializing parameters and updating the maximum number of iterations T of the algorithm;

[0090] S342, initializing the sample storage plan to identify the position of the seagull population, and the sample storage plan to identify the position of the seagull population updated in the search space of the standard sample storage plan data matrix Q of the retained food sample;

[0091] S343, calculate all the food sample standard storage plan data q in the food sample standard storage plan data matrix Q according to the food sample characteristic keyword matching. b and the identity characteristic data of the sampled food object shenfen The fitness value is retained in the search space of the sample food standard storage plan data matrix Q and the sample food object identity feature data O shenfen The data of the standard sample storage plan of retained food with the largest fitness value q b The global optimal position of

[0092] S344, migration, global search: There are three main steps in the sample scheme to identify the migration behavior of seagulls. The first is to meet the conditions of avoiding collisions between seagulls identified by different sample schemes in the search space of the sample food standard sample scheme data matrix Q; the second is to match the key words of the food sample characteristics in the search space of the sample food standard sample scheme data matrix Q with the sample food object identity feature data O. shenfen Matching food sample standard storage plan data q b The best position direction; third according to the identity characteristic data of the sample food object O shenfen The best matching sample storage plan data q b Move to the new position in the direction of the best position;

[0093] S3441, calculating the new position R'(t) of the sample storage scheme identification seagull in the search space of the sample storage scheme data matrix Q without colliding with the adjacent sample storage scheme identification seagull; R'(t) = ω × R(t), Where R(t) represents the current position of the sample identification seagull in the search space of the sample storage plan data matrix Q of the sample storage plan of the sample food, t represents the current iteration number; ω represents the movement behavior of the sample identification seagull in the search space of the sample storage plan data matrix Q of the sample storage plan of the sample food; ξ represents the function that controls the frequency of change of ω, and T represents the maximum number of iterations;

[0094] S3442, calculate the matching of the key words of the food sample characteristics with the sample food object identity feature data O in the search space of the sample food standard sample storage plan data matrix Q. shenfen Matching food sample standard storage plan data q b The optimal position direction Φ(t); Φ(t)=Θ×(R best (t)-R(t)), Θ=2×ω 2 ×ψ, where R best (t) represents the search space of the sample food standard storage sample plan data matrix Q, and searches for the identity feature data O of the sample food object according to the food sample feature keyword matching. shenfenMatching food sample standard storage plan data q b The current best position of , Θ represents a random number that balances global and local search capabilities, and ψ represents a random number in the interval [0,1];

[0095] S3443, according to the identity characteristic data of the sample food object shenfen The best matching sample storage plan data q b The direction of the optimal position is moved to the new position Λ(t), Λ(t) = |R'(t) + Φ(t)|, that is, according to the direction of the optimal position, the food sample standard storage plan data matrix Q is searched for the identity feature data O of the sample food object according to the food sample feature keyword matching in the search space. shenfen Matching food sample standard storage plan data q b new location;

[0096] S345. Attacking prey, local search, and sample storage scheme identification. When attacking prey in the search space of the standard sample storage scheme data matrix Q of the retained food sample, the seagull performs a spiral motion in the air. The sample storage scheme identifies the new position Λ'(t) after the seagull attacks the prey, Λ'(t)=Λ(t)+R best (t), Sample storage scheme identification Seagull searches for the identity feature data O of the sample food object in the search space of the sample storage scheme data matrix Q according to the food sample feature keyword matching shenfen Matching food sample standard storage plan data q b of prey;

[0097] S346: Determine whether the maximum number of iterations is met, and then output the identity feature data of the sample food object. shenfen Matching food sample standard storage plan data q b ; If not satisfied, return to step S343;

[0098] S347, the identity feature data of the sample food object outputted in step S346 shenfen Matching food sample standard storage plan data q b And generate sample food storage plan data q through data identification mubiao ;

[0099] S35, the sample cabinet control terminal plans data q according to the sample storage plan mubiao The industrial robot is controlled in an orderly manner to place the retained food samples into the designated storage location in the sample cabinet, and the operating status of the sample cabinet is adjusted to perform the retained food sample storage operation.

[0100] The steps for recording and processing the information during the food sample storage phase based on the identity data of the food sample storage administrator and the identity data of the sampled food object to construct the data of the sample storage process record are as follows:

[0101] S41, the food sample manager identity feature data I, the sample food object identity feature data O shenfen The blockchain storage method is used to construct the sample storage process record data H through data combination identification. cunyang , where H cunyang =(I,O shenfen ).

[0102] Through the cooperation between the sample food storage information collection unit and the sample food object identity information generation unit, the sample cabinet control panel is used to obtain the sample food storage characteristic information online and combined with data processing to scientifically construct the sample food object identity characteristic information, so as to achieve the efficient establishment of the sample food object information standard and improve the scientific nature of food sample information management.

[0103] Through the sample storage plan planning unit, intelligent planning of the sample storage plan for retained food is carried out according to the identity information of the sample food object combined with the intelligent recognition algorithm and the standard sample storage plan information of the sample food based on big data storage, so as to realize the refined and scientific planning of the food storage plan based on the characteristic types of the sample food, thereby improving the safety and accuracy of food samples; the sample storage operation execution unit and the sample storage record information construction unit of the sample food cooperate with each other, and independently and reliably execute the sample storage operation of retained food according to the sample storage plan planning information combined with the sample cabinet control terminal, industrial robot and sample cabinet, and at the same time combine the blockchain technology to safely and reliably record the sample storage information of the sample food, thereby realizing the traceability of the storage information of the food samples and improving the applicability of food sample management.

[0104] For further information, see Figure 1 - Figure 2 , collect the identity feature data of the food sampling administrator and perform sampling authority judgment processing on the food sampling administrator together with the identity feature data of the food sampling registration administrator, generate sampling authority judgment data of the food sampling administrator, and when there is no sampling authority, prompt the food sampling administrator that there is no sampling operation authority as follows:

[0105] S51. Collecting identity feature information of a manager who takes food samples and places them into the sample cabinet during a food sampling operation online through the sample cabinet control panel, and generating food sampling manager identity feature data J. The food sampling manager identity feature data J includes the name text information and facial image information of the food sampling manager.

[0106] S52, using XGBoost search algorithm to compare the food sampling administrator identity feature data J with the food sample registration administrator identity feature data matrix Y. a Perform identity feature information matching and generate food sample administrator sampling authority judgment data P based on the identity feature information matching results. quyang ;

[0107] When J and y a If the identity feature information is matched successfully, it means that the manager who performs food sampling is a food sampling registration manager, then the food sampling manager sampling authority judgment data P is output. quyang To have sampling authority;

[0108] When J and y a If the identity feature information is not matched successfully, it means that the manager who performs food sampling is not a registered food sampling manager, then the food sampling manager sampling authority judgment data P is output. quyang The user has no sampling authority, and the sample cabinet control panel outputs a prompt that the food sample administrator has no sampling operation authority.

[0109] When you have sampling authority, the steps to obtain the sample storage process record data and perform the sample collection operation are as follows:

[0110] S61, when the food sample administrator's sampling authority determines the data P quyang When the sampling authority is granted, the food sample management personnel obtains the sample storage process record data H through the sample cabinet control panel cunyang ;

[0111] S62, the sample cabinet control terminal records the sample storage process data H obtained cunyang Control the industrial robot to take out the reserved food samples from the designated storage location in the sample cabinet and perform the reserved food sampling operation.

[0112] The steps for processing the information records of the food sample storage and sampling stage based on the sample storage process record data and the identity feature data of the food sampling administrator are as follows:

[0113] S71, obtain the sample storage process record data H cunyang , food sampling administrator identity characteristic data J;

[0114] S72, record the data of the sample storage process of the sampled food H cunyang , food sampling administrator identity feature data J is stored in blockchain mode and the sample storage and sampling process record data G is constructed through data combination identification. quyang , where G quyang=(J,H cunyang ).

[0115] Through the cooperation of the food sampling administrator information collection unit and the food sample retention administrator sampling authority judgment unit, the sample retention cabinet control panel is used to obtain accurate food sampling administrator identity information and dynamically supervise the sampling rights of the food sample retention administrator in combination with the food sample retention registration administrator identity information; the sample food storage record information acquisition unit and the sample food sampling operation execution unit cooperate with each other to accurately obtain the sample food storage process record information and combine the sample retention cabinet control terminal, industrial robot and sample retention cabinet to quickly and accurately perform the sample food sampling operation, thereby improving the efficiency and safety of sample food sampling; the sample food storage and sampling record information construction unit, based on the sample food storage process record information and the food sampling administrator identity information, combines blockchain technology to dynamically and reliably record the sample food storage and sampling information, thereby realizing intelligent and safe recording of the entire process information of food storage and sampling, thereby improving the applicability and safety of food sample management.

[0116] Example 2:

[0117] See also Figure 1 - Figure 2 , a blockchain-based sample cabinet intelligent storage and access system is used to implement a blockchain-based sample cabinet intelligent storage and access method. The system includes a sample food storage information processing module, a sample food storage management module, and a sample food sampling management module;

[0118] The sample food storage information processing module includes a food storage sample administrator information collection unit, a food sample registration administrator information storage unit, a food sample administrator storage authority judgment unit, a sample food storage information collection unit, and a sample food object identity information generation unit;

[0119] The food sample storage administrator information collection unit collects the identity characteristic data of the food sample storage administrator through the sample storage cabinet control panel; the food sample registration administrator information storage unit is used to store the identity characteristic data of the food sample registration administrator; the food sample storage authority judgment unit performs a sample storage authority judgment process on the food sample storage administrator based on the identity characteristic data of the food sample storage administrator and the identity characteristic data of the food sample registration administrator, and generates the sample storage authority judgment data of the food sample administrator; the sample storage information collection unit collects the sample storage characteristic data of the sampled food through the sample storage cabinet control panel; the sampled food object identity information generation unit performs a sample storage information generation process on the sampled food based on the sample storage characteristic data of the sampled food, and generates the identity characteristic data of the sampled food object;

[0120] The sample storage management module of retained food includes a sample storage plan storage unit for retained food standard, a sample storage plan planning unit for retained food, a sample storage operation execution unit for retained food, and a sample storage record information construction unit for retained food;

[0121] The standard storage plan storage unit for retained food samples is used to store the standard storage plan data for retained food samples; the storage plan planning unit for retained food samples performs storage plan processing for retained food samples in the sample cabinet based on the identity feature data of the retained food sample object and the standard storage plan data for retained food samples, and generates the storage plan planning data for retained food samples; the storage operation execution unit for retained food samples performs the storage operation for retained food samples based on the storage plan planning data for retained food samples in combination with the sample cabinet control terminal, industrial robot and sample cabinet; the storage record information construction unit for retained food samples performs information record processing at the storage stage of retained food samples based on the identity feature data of the food storage administrator and the identity feature data of the stored food sample object in combination with blockchain technology, and constructs the storage process record data for retained food samples;

[0122] The sample food sampling management module includes a food sampling administrator information collection unit, a food sample administrator sampling authority judgment unit, a sample food storage record information acquisition unit, a sample food sampling operation execution unit, and a sample food storage and sampling record information construction unit;

[0123] The food sampling administrator information collection unit collects the identity characteristic data of the food sampling administrator through the sample retention cabinet control panel; the food sample retention administrator sampling authority judgment unit performs sampling authority judgment processing on the food sample retention administrator based on the identity characteristic data of the food sampling administrator and the identity characteristic data of the food sample registration administrator, and generates sampling authority judgment data of the food sample retention administrator; the sample food storage record information acquisition unit is used to obtain the sample storage process record data of the sample food; the sample food sampling operation execution unit performs the sample food sampling operation based on the sample food storage process record data in combination with the sample cabinet control terminal, industrial robot and sample cabinet; the sample food storage and sampling record information construction unit performs information record processing on the sample food storage and sampling stage based on the sample food storage process record data, the identity characteristic data of the food sampling administrator and the blockchain technology, and constructs the sample food storage and sampling process record data.

[0124] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. The intelligent access method for sample cabinets based on blockchain is characterized by: The method comprises the following steps: S1. Collect the identity data of the food sample storage manager; S2. Perform sample storage authority determination processing on the food sample storage administrator, generate sample storage authority determination data for the food sample storage administrator, and if the food sample storage administrator does not have sample storage authority, prompt the food sample storage administrator that he or she does not have sample storage operation authority; S3. When the sample storage authority is granted, collect the sample storage characteristic data of the retained food and perform identity information generation processing on the retained food, generate identity characteristic data of the retained food object, perform sample storage plan processing on the retained food in the sample storage cabinet, generate sample storage plan data for the retained food, and execute the retained food sample storage operation; S4. Processing the information record of the sampled food during the storage phase to construct the data of the sampled food storage process record; S5. Collect the identity feature data of the food sampling administrator, perform sampling authority determination processing on the food sampling administrator, generate sampling authority determination data of the food sampling administrator, and if the sampling authority is not available, prompt the food sampling administrator that he or she does not have sampling operation authority; S6. When the sampling authority is granted, obtain the sample storage process record data of the reserved food and perform the reserved food sampling operation; S7. Process the information records of the food sample storage and sampling stages, and construct the record data of the food sample storage and sampling process.

2. The blockchain-based intelligent access method for sample cabinets according to claim 1 is characterized by: Said S1 comprises the following steps: S11. Collect the identity characteristic information of the manager who stores the food samples in the sample cabinet during the food sampling operation online through the sample cabinet control panel, and generate food sample manager identity characteristic data I.

3. The blockchain-based intelligent access method for sample cabinets according to claim 2 is characterized by: The S2 comprises the following steps: S21. Establish the identity characteristic data matrix Y = (y1,…,y a ,…,y α ), a=1,2,3,…,α; where y a represents the identity characteristic data of the food sample registration administrator corresponding to the a-th food sample administrator, and α represents the maximum number of food sample administrators; S22, using XGBoost search algorithm to compare the I with the y in the Y a Perform identity feature information matching and generate food sample storage authority judgment data Y based on the identity feature information matching results cunyang ; When I and y a If the identity feature information is matched successfully, the Y cunyang Have the permission to store samples; When I and y a If the identity feature information is not matched successfully, the Y cunyang The user does not have the permission to store samples, and the sample cabinet control panel outputs a prompt that the food sample administrator does not have the permission to store samples.

4. The blockchain-based intelligent access method for sample cabinets according to claim 3 is characterized by: The S3 includes the following steps: S31 , when the Y cunyang When the user has the sample storage authority, the user collects the sample characteristics text information of the sampled food in the food sample storage operation online through the sample storage cabinet control panel, and generates the sample characteristics data O of the sampled food; S32, using the sample retention date and the daily food sample retention operation sequence number to perform identity information combination identification processing on the sample food O, and generate the identity feature data of the sample food object O. shenfen The identity characteristic data of the sample food object includes the sample characteristic information and the sample identification number of the sample food; S33, establish the data matrix Q = (q1, ..., q b ,…,q β ), b=1,2,3,…,β; where q b represents the standard sample storage plan data of the retained food corresponding to the b-th food sample characteristic combination type, and β represents the maximum number of food sample characteristic combination types; S34, the O shenfen and the q in the Q b Perform food sample feature keyword matching to search for the O shenfen The corresponding q b , and generate sample food storage plan data q through data identification mubiao ; Execute and generate the sample food storage plan planning data q mubiao The specific steps are as follows: S341, initializing parameters and updating the maximum number of iterations T of the algorithm; S342, initializing a sample storage scheme to identify the location of the seagull population, and the sample storage scheme to identify the location of the seagull population update in the search space of Q; S343, calculate all the q in Q according to the food sample feature keyword matching b With the O shenfen The fitness value is retained in the search space of Q and O shenfen The q with the largest fitness value b The global optimal position of S344, migration, global search: There are three main steps in the sample solution to identify the migration behavior of seagulls. The first step is to meet the conditions of avoiding collisions between seagulls identified by different sample solutions in the search space of Q; the second step is to calculate the search space of Q and the search space of O according to the matching of food sample feature keywords. shenfen Match the q b The best position direction; the third is based on the O shenfen The best matching q b Move to the new position in the direction of the best position; S3441, calculating a new position R'(t) of the sample solution identified seagull in the search space of Q without colliding with an adjacent sample solution identified seagull; S3442, calculate the matching of the keywords of the food sample characteristics in the search space of Q with the O shenfen Match the q b The optimal position direction Φ(t); S3443, according to the O shenfen The best matching q b The direction of the optimal position moves to the new position Λ(t); S345, attacking prey, local search, the sample solution identifies that the seagull performs spiral motion in the air when attacking the prey in the search space of Q, and the sample solution identifies the new position Λ'(t) of the seagull after attacking the prey; S346, determine whether the maximum number of iterations is met, and then output the value of shenfen Match the q b ; If not satisfied, return to step S343; S347, the output of step S346 and the shenfen Match the q b And generate sample food storage plan data q through data identification mubiao ; S35, the sample cabinet control terminal according to the q mubiao The industrial robot is controlled in an orderly manner to place the retained food samples into the designated storage location in the sample cabinet, and the operating status of the sample cabinet is adjusted to perform the retained food sample storage operation.

5. The blockchain-based intelligent access method for sample cabinets according to claim 4 is characterized in that: The S4 comprises the following steps: S41, the I, the O shenfen The blockchain storage method is used to construct the sample storage process record data H through data combination identification. cunyang .

6. The blockchain-based intelligent access method for sample cabinets according to claim 5 is characterized by: The S5 comprises the following steps: S51, collecting identity characteristic information of the manager who takes samples of food and places them into the sample cabinet during the food sampling operation online through the sample cabinet control panel, and generating food sampling manager identity characteristic data J; S52, using XGBoost search algorithm to compare the J with the y in the Y a Perform identity feature information matching and generate food sample administrator sampling authority judgment data P based on the identity feature information matching results. quyang ; When J and y a If the identity feature information is matched successfully, the P quyang To have sampling authority; When J and y a If the identity feature information is not matched successfully, the P quyang The user has no sampling authority, and the sample cabinet control panel outputs a prompt that the food sample administrator has no sampling operation authority.

7. The blockchain-based intelligent access method for sample cabinets according to claim 6 is characterized by: The S6 comprises the following steps: S61, when the P quyang When the sampling authority is granted, the food sample management personnel obtains the sample storage process record data H of the sample storage cabinet control panel. cunyang ; S62, the sample cabinet control terminal obtains the H cunyang Control the industrial robot to take out the reserved food samples from the designated storage location in the sample cabinet and perform the reserved food sampling operation.

8. The blockchain-based intelligent access method for sample cabinets according to claim 7 is characterized in that: The S7 comprises the following steps: S71, obtain the H cunyang , said J; S72, the H cunyang , the J uses the blockchain storage method to construct the sample food storage and sampling process record data G through data combination identification quyang .

9. A blockchain-based intelligent storage and access system for sample cabinets, used to implement the blockchain-based intelligent storage and access method for sample cabinets described in any one of claims 1 to 8, characterized in that: The system includes a reserved food sample storage information processing module, a reserved food sample storage management module and a reserved food sample taking management module.

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