A food safety deep enhanced traceability system, method and computer readable medium

Abstract

The present invention discloses a food safety deep enhanced traceability system, method and computer readable medium. The traceability system includes a food safety deep enhanced traceability system, which includes a raw material supply monitoring system, a food production monitoring system, a food transportation monitoring system and a sales terminal monitoring system; the raw material supply monitoring system, the food production monitoring system, the food transportation monitoring system and the sales terminal monitoring system are all in wireless communication with a server built by a food safety traceability service platform; the method includes steps S1-S9. And a computer readable medium for executing the method is disclosed. The present invention builds a system for deep tracing of food safety, constructs a complete and detailed food safety traceability platform, monitors the quality assessment of the details in the process of planting, production, transportation and sales of food raw materials, and avoids the impact of errors in each link on food quality.

Description

Technical Field

[0001] The present invention relates to the field of food safety technology, and in particular to a food safety deep enhanced traceability system, method and computer-readable medium. Background Art

[0002] The food safety traceability system refers to the fact that food quality and safety and related information can be tracked forward (production source - consumer terminal) or reversely (consumer terminal - production source) in all aspects of food production, supply and marketing (including planting and breeding, production, circulation, sales and catering services, etc.), so that the entire production and operation activities of food are always under effective monitoring. The system can clarify responsibilities, clarify the respective responsibilities of the management subject and the managed subject, and effectively deal with food that does not meet safety standards, thereby ensuring food quality and safety. The existing food safety traceability system can only track food production or raw materials in the later stage, and cannot timely evaluate and screen the quality of food and raw materials through data, so that inferior products may still circulate in the market, bringing food safety risks to people. Summary of the invention

[0003] In view of the above-mentioned deficiencies in the prior art, the present invention provides a food safety deep enhanced traceability system, method and computer-readable medium that can track the raw material production, food production and transportation processes in real time.

[0004] In order to achieve the above-mentioned object of the invention, the technical solution adopted by the present invention is:

[0005] Provided is a food safety deep enhanced traceability system, which includes a raw material supply monitoring system, a food production monitoring system, a food transportation monitoring system and a sales terminal monitoring system; the raw material supply monitoring system, the food production monitoring system, the food transportation monitoring system and the sales terminal monitoring system all communicate wirelessly with a server built by a food safety traceability service platform;

[0006] The raw material supply monitoring system includes a water source monitoring system, a climate monitoring system, a soil quality monitoring system and an insect pest monitoring system; the water source monitoring system collects water quality parameters of the water source used for irrigation at the raw material supply base; the climate monitoring system collects climate parameters of the raw material supply base during the growth of the raw materials; the soil quality monitoring system collects soil quality parameters of the raw material supply base during the growth of the raw materials; the insect pest monitoring system collects disease and insect pest parameters of the raw material supply base during the growth of the raw materials;

[0007] The food production monitoring system includes a production process monitoring system and a warehouse monitoring system; the production process monitoring system is used to monitor the production parameters in the food production process and the packaging parameters in the packaging process; the warehouse monitoring system is used to monitor the storage condition parameters of the finished products when they are stored in the warehouse, and to detect the integrity of the packaging bags when they are shipped out of the warehouse;

[0008] The food transportation monitoring system includes a GPS positioning system and a transportation environment monitoring system; the GPS positioning system is used to monitor the transportation trajectory and coordinates during food transportation; the transportation environment monitoring system is used to monitor the transportation storage temperature and humidity during food transportation;

[0009] The sales terminal monitoring system includes an independent sales terminal monitoring system and a physical store sales monitoring system; the independent sales terminal monitoring system and the physical store sales monitoring system are used to monitor the sales storage temperature and humidity during the food sales process, and collect consumer information after the consumer purchases;

[0010] The server sets up raw material supply database, food production database, food transportation database and sales terminal database, and establishes a GIS map of the raw material planting base; the raw material supply database is used to store data collected by the raw material supply monitoring system; the food production database is used to store data collected by the food production monitoring system; the food transportation database is used to store data collected by the food transportation monitoring system; the sales terminal database is used to store data collected by the sales terminal monitoring system; the processor in the server is used to analyze and process the data in the raw material supply database, food production database, food transportation database and sales terminal database.

[0011] Furthermore, the water source monitoring system includes a pH sensor, a fluoride sensor and a heavy metal sensor. The pH sensor is used to detect the pH value in the irrigation water source, the fluoride sensor is used to detect the fluoride content in the irrigation water source, and the heavy metal sensor is used to detect the heavy metal content in the irrigation water source.

[0012] Furthermore, the soil quality monitoring system includes a soil pH sensor, a soil moisture sensor and a soil nitrogen, phosphorus and potassium sensor. The soil pH sensor is used to detect the pH of the soil in the raw material supply base, the soil moisture sensor is used to detect the moisture of the soil, and the soil nitrogen, phosphorus and potassium sensor is used to detect the nitrogen, phosphorus and potassium content of the soil.

[0013] Furthermore, production parameters include the heating temperature of the food given by the production equipment, the ratio of raw materials, cooking time and the amount of preservatives added, and packaging parameters include the packaging bag material and packaging type.

[0014] A control method for the above-mentioned food safety deep enhanced traceability system is provided, which comprises the following steps:

[0015] S1: The raw material supply monitoring system collects water quality parameters, climate parameters, soil parameters and pest and disease parameters at set intervals;

[0016] S2: When the raw materials are harvested, the processor uses the collected water quality parameters, climate parameters, soil parameters and pest and disease parameters to classify the harvested raw materials and select high-quality raw materials;

[0017] S3: Pack the high-quality raw materials and mark them with the raw material traceability code, which contains the water quality parameters, climate parameters, soil parameters, pest and disease parameters and GPS positioning information of the planting base when the raw materials were planted, and transport them to the production enterprises for food production;

[0018] S4: During the food processing, the heating temperature, raw material ratio, cooking time and preservative addition amount are uploaded to the food production database. The processor evaluates the processing quality of the food according to the heating temperature, raw material ratio, cooking time and preservative addition amount, selects high-quality food that meets the requirements, and eliminates inferior food;

[0019] S5: High-quality food is packaged through the packaging process and marked with a production traceability code on the packaging. The production traceability code contains the heating temperature, raw material ratio, cooking time, preservative addition amount and manufacturer information, and then put into the warehouse for storage;

[0020] S6: The packaged food in the warehouse is transported to the self-service sales terminal or the physical store sales terminal by transportation vehicles;

[0021] S7: During the transportation process, the GPS positioning module collects the trajectory and coordinates of the transportation process and uploads them to the food transportation database;

[0022] S8: The processor determines whether the transportation is normal according to the trajectory and coordinates of the transportation process. If not, an alarm text message is sent to the staff of the self-service sales terminal or the physical store sales terminal; if so, the self-service sales terminal or the physical store sales terminal is normally entered for sales;

[0023] S9: Consumers purchase food through the sales platform built by the sales terminal monitoring system. The sales platform enters the consumer's contact information, displays the food's raw material traceability code and production traceability code on the sales platform, and generates a food traceability file based on the raw material traceability code, production traceability code and consumer's contact information, and uploads it to the sales terminal database.

[0024] Further, step S2 includes:

[0025] S21: Traverse the water quality parameters, climate parameters, soil parameters and pest and disease parameters collected during the raw material planting process to form n groups of planting parameter data sets {(S1, Q1, T1, B1), (S2, Q2, T2, B2), ···, (S n , Q n , T n , Bn )}, where S n is the water quality parameter, Q n is the climate parameter, T n is the soil parameter, B n is the pest and disease parameter, and n is the number of times the raw material supply monitoring system collects the planting parameters during the raw material planting process;

[0026] S22: Establishing planting parameter threshold data sets for water quality parameters, climate parameters, soil parameters, and pest and disease parameters (S y , Q y , T y , B y );

[0027] S23: The implantation parameter data set (S n , Q n , T n , B n ) and the implantation parameter threshold data set (S y , Q y , T y , B y ) to compare the difference and obtain the planting parameter error data set (ΔS, ΔQ, ΔT, ΔB) = (S n , Q n , T n , B n )-(S y , Q y , T y , B y ), and ΔS, ΔQ, ΔT, ΔB are all positive numbers;

[0028] S24: Establishing a planting parameter error threshold data set (δ S , δ Q , δ T , δ B ), and compare each parameter in the planting parameter error data set (ΔS, ΔQ, ΔT, ΔB) with the error threshold data set (δ S , δ Q , δ T , δ B ) are compared with the corresponding parameters in each column;

[0029] S25: If there is a parameter in the implantation parameter error data set (ΔS, ΔQ, ΔT, ΔB) that is greater than the implantation parameter error threshold data set (δ S , δ Q , δ T , δ B ), the planting parameter data set collected this time is marked as exceeding the standard once; otherwise, it is not marked as exceeding the standard;

[0030] S26: traverse the n sets of planting parameter data collected during the raw material planting process, repeat steps S23-S25, count the number of times H of exceeding the standard in the n sets of planting parameter data; compare the number of times H of exceeding the standard with the threshold value h of the number of times exceeding the standard;

[0031] S27: If H ≥ h, the batch of raw materials is determined to be inferior raw materials, the processor collects the GPS positioning information of the planting base of the batch of raw materials, marks it on the GIS map, generates an inferior raw material alarm signal, and sends the inferior raw material alarm signal and GPS positioning information to the manufacturer;

[0032] S28: If H<h, the batch of raw materials is determined to be high-quality raw materials.

[0033] Further, step S4 includes:

[0034] S41: During the food processing, the heating temperature, raw material ratio, cooking time and preservative addition amount are uploaded to the food production database to generate a processing data set (R, L, P, F) of the food processing;

[0035] S42: Establishing a processing parameter threshold data set for processed food (R y , L y , P y , F y ), the parameters in the processing data set (R, L, P, F) are respectively compared with the processing parameter threshold data set (R y , L y , P y , F y ) to obtain the processing parameter error data set (ΔR, ΔL, ΔP, ΔF) = (R, L, P, F) - (R y , L y , P y , F y ), ΔR, ΔL, ΔP, ΔF are all positive numbers;

[0036] S43: Establishing a processing parameter error threshold data set (δ R , δ L , δ P , δ F ), the parameters in the processing parameter error data set (ΔR, ΔL, ΔP, ΔF) are compared with the processing parameter error threshold data set (δ R , δ L , δ P , δ F ) are compared with the corresponding parameters in each column;

[0037] S44: If there is a parameter in the processing parameter error data set (ΔR, ΔL, ΔP, ΔF) that is greater than the processing parameter error threshold data set (δ R , δ L , δ P , δ F ), the food produced in this batch is judged to be inferior food; otherwise, it is high-quality food.

[0038] Further, step S8 includes:

[0039] S81: During the transportation process, the GPS positioning module collects positioning coordinates every set time t;

[0040] S82: Calculate the time T* of the transport vehicle's travel at this time based on the number of times u that the location coordinates W have been collected: T* = u × t

[0041] S82: Using the time T* and the road speed limit V, calculate the ideal transportation distance of the transport vehicle at this time: M = V × T*. According to the ideal transportation distance M, mark the ideal coordinate Z at a distance M from the starting point of the warehouse on the planned route;

[0042] S83: Calculate the positioning error between the ideal coordinate Z and the actually collected positioning coordinate W;

[0043] S84: When the positioning error is compared with the positioning error threshold, if the positioning error is greater than the positioning error threshold, it is determined that the transport vehicle is abnormal, and an alarm text message is sent to the staff of the self-service sales terminal or the physical store sales terminal; otherwise, the transport vehicle is transporting normally.

[0044] A computer-readable medium is provided, which stores a control program of a food safety deep enhanced traceability system. When the control program of the food safety deep enhanced traceability system is executed by at least one processor, the at least one processor implements the control method of the food safety deep enhanced traceability system when executing.

[0045] The beneficial effects of the present invention are as follows: the present invention builds a system for in-depth traceability of food safety, constructs a complete and detailed food safety traceability platform, monitors quality assessment from the details of the planting, production, transportation and sales of food raw materials, and avoids the impact of errors in each link on food quality. At the same time, quality assessment of raw materials, finished products, transportation processes, and sales processes will be carried out at each link to screen out inferior raw materials and finished foods, greatly reducing the possibility of inferior food entering the market and achieving comprehensive monitoring of multiple links. The monitored data is classified and saved to facilitate the retrieval and analysis of data at a later stage. In order to achieve good safety, strong stability in quality monitoring, reduce the difficulty of food safety traceability, easy operation, and have the advantages of high work efficiency and openness. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 This is the principle block diagram of the deep enhanced traceability system for food safety. DETAILED DESCRIPTION

[0047] The specific implementation modes of the present invention are described below so that those skilled in the art can understand the present invention. However, it should be clear that the present invention is not limited to the scope of the specific implementation modes. For those of ordinary skill in the art, as long as various changes are within the spirit and scope of the present invention as defined and determined by the attached claims, these changes are obvious, and all inventions and creations utilizing the concept of the present invention are protected.

[0048] like Figure 1 As shown, the food safety deep enhanced traceability system of this solution includes raw material supply monitoring system, food production monitoring system, food transportation monitoring system and sales terminal monitoring system; the raw material supply monitoring system, food production monitoring system, food transportation monitoring system and sales terminal monitoring system all communicate wirelessly with the server built by the food safety traceability service platform.

[0049] The raw material supply monitoring system includes a water source monitoring system, a climate monitoring system, a soil quality monitoring system and a pest monitoring system; the water source monitoring system collects water quality parameters of the water source used for irrigation at the raw material supply base; the climate monitoring system collects climate parameters of the raw material supply base during the growth of the raw materials; the soil quality monitoring system collects soil parameters of the raw material supply base during the growth of the raw materials; the pest monitoring system collects disease and insect pest parameters of the raw material supply base during the growth of the raw materials.

[0050] The food production monitoring system includes a production process monitoring system and a warehouse monitoring system; the production process monitoring system is used to monitor the production parameters in the food production process and the packaging parameters in the packaging process; the warehouse monitoring system is used to monitor the storage condition parameters of the finished products when they are stored in the warehouse, and to detect the integrity of the packaging bags when they are shipped out of the warehouse.

[0051] The food transportation monitoring system includes a GPS positioning system and a transportation environment monitoring system; the GPS positioning system is used to monitor the transportation trajectory and coordinates during food transportation; the transportation environment monitoring system is used to monitor the transportation and storage temperature and humidity during food transportation.

[0052] The sales terminal monitoring system includes an independent sales terminal monitoring system and a physical store sales monitoring system; the independent sales terminal monitoring system and the physical store sales monitoring system are used to monitor the sales, storage, temperature and humidity during the food sales process, and collect consumer information after the consumer purchases.

[0053] The server sets up raw material supply database, food production database, food transportation database and sales terminal database, and establishes a GIS map of the raw material planting base; the raw material supply database is used to store data collected by the raw material supply monitoring system; the food production database is used to store data collected by the food production monitoring system; the food transportation database is used to store data collected by the food transportation monitoring system; the sales terminal database is used to store data collected by the sales terminal monitoring system; the processor in the server is used to analyze and process the data in the raw material supply database, food production database, food transportation database and sales terminal database.

[0054] The water source monitoring system includes a pH sensor, a fluoride sensor and a heavy metal sensor. The pH sensor is used to detect the pH value in the irrigation water source, the fluoride sensor is used to detect the fluoride content in the irrigation water source, and the heavy metal sensor is used to detect the heavy metal content in the irrigation water source.

[0055] The soil quality monitoring system includes soil pH sensor, soil moisture sensor and soil nitrogen, phosphorus and potassium sensor. The soil pH sensor is used to detect the pH of the soil in the raw material supply base, the soil moisture sensor is used to detect the moisture of the soil, and the soil nitrogen, phosphorus and potassium sensor is used to detect the nitrogen, phosphorus and potassium content of the soil.

[0056] Production parameters include the heating temperature of the food given by the production equipment, the ratio of raw materials, cooking time and the amount of preservatives added; packaging parameters include the material of the packaging bag and the type of packaging.

[0057] The control method of the above-mentioned food safety deep enhanced traceability system in this scheme includes the following steps:

[0058] S1: The raw material supply monitoring system collects water quality parameters, climate parameters, soil parameters and pest and disease parameters at set intervals;

[0059] S2: When the raw materials are harvested, the processor classifies the harvested raw materials using the collected water quality parameters, climate parameters, soil parameters and pest and disease parameters to select high-quality raw materials; step S2 includes:

[0060] S21: Traverse the water quality parameters, climate parameters, soil parameters and pest and disease parameters collected during the raw material planting process to form n groups of planting parameter data sets {(S1, Q1, T1, B1), (S2, Q2, T2, B2), ···, (S n , Q n , T n , B n )}, where S n is the water quality parameter, Q n is the climate parameter, T n is the soil parameter, B nis the pest and disease parameter, and n is the number of times the raw material supply monitoring system collects the planting parameters during the raw material planting process;

[0061] S22: Establishing planting parameter threshold data sets for water quality parameters, climate parameters, soil parameters, and pest and disease parameters (S y , Q y , T y , B y );

[0062] S23: The implantation parameter data set (S n , Q n , T n , B n ) and the implantation parameter threshold data set (S y , Q y , T y , B y ) to compare the difference and obtain the planting parameter error data set (ΔS, ΔQ, ΔT, ΔB) = (S n , Q n , T n , B n )-(S y , Q y , T y , B y ), and ΔS, ΔQ, ΔT, ΔB are all positive numbers;

[0063] S24: Establishing a planting parameter error threshold data set (δ S , δ Q , δ T , δ B ), and compare each parameter in the planting parameter error data set (ΔS, ΔQ, ΔT, ΔB) with the error threshold data set (δ S , δ Q , δ T , δ B ) are compared with the corresponding parameters in each column;

[0064] S25: If there is a parameter in the implantation parameter error data set (ΔS, ΔQ, ΔT, ΔB) that is greater than the implantation parameter error threshold data set (δ S , δ Q , δ T , δ B ), the planting parameter data set collected this time is marked as exceeding the standard once; otherwise, it is not marked as exceeding the standard;

[0065] S26: traverse the n sets of planting parameter data collected during the raw material planting process, repeat steps S23-S25, count the number of times H of exceeding the standard in the n sets of planting parameter data; compare the number of times H of exceeding the standard with the threshold value h of the number of times exceeding the standard;

[0066] S27: If H≥h, the batch of raw materials is determined to be inferior raw materials. The processor collects the GPS positioning information of the planting base of the batch of raw materials and marks it on the GIS map, generates an inferior raw material alarm signal, and sends the inferior raw material alarm signal and GPS positioning information to the manufacturer; the raw material production base is marked to facilitate the improvement and maintenance of the planting conditions of the raw material production base.

[0067] S28: If H<h, the batch of raw materials is determined to be high-quality raw materials.

[0068] During the planting process of raw materials, water quality parameters, climate parameters, soil parameters and pest and disease parameters need to meet certain conditions. When the above parameters exceed the standard for a long time, it will inevitably affect the quality of the raw materials, and consumers will cause long-term harm to their bodies after consumption.

[0069] S3: Pack the high-quality raw materials and mark them with the raw material traceability code, which contains the water quality parameters, climate parameters, soil parameters, pest and disease parameters and GPS positioning information of the planting base when the raw materials were planted, and transport them to the production enterprises for food production;

[0070] S4: During the food processing, the heating temperature, raw material ratio, cooking time and preservative addition amount are uploaded to the food production database. The processor evaluates the processing quality of the food according to the heating temperature, raw material ratio, cooking time and preservative addition amount, selects high-quality food that meets the requirements, and eliminates inferior food. Step S4 includes:

[0071] S41: During the food processing, the heating temperature, raw material ratio, cooking time and preservative addition amount are uploaded to the food production database to generate a processing data set (R, L, P, F) of the food processing;

[0072] S42: Establishing a processing parameter threshold data set for processed food (R y , L y , P y , F y ), the parameters in the processing data set (R, L, P, F) are respectively compared with the processing parameter threshold data set (R y , L y , P y , F y ) to obtain the processing parameter error data set (ΔR, ΔL, ΔP, ΔF) = (R, L, P, F) - (R y , L y , P y , F y ), ΔR, ΔL, ΔP, ΔF are all positive numbers;

[0073] S43: Establishing a processing parameter error threshold data set (δ R , δ L , δ P , δ F ), the parameters in the processing parameter error data set (ΔR, ΔL, ΔP, ΔF) are compared with the processing parameter error threshold data set (δ R , δ L , δ P , δ F ) are compared with the corresponding parameters in each column;

[0074] S44: If there is a parameter in the processing parameter error data set (ΔR, ΔL, ΔP, ΔF) that is greater than the processing parameter error threshold data set (δ R , δ L , δ P , δ F ), the food produced in this batch is judged to be inferior food; otherwise, it is high-quality food.

[0075] S5: High-quality food is packaged through the packaging process and marked with a production traceability code on the packaging. The production traceability code contains the heating temperature, raw material ratio, cooking time, preservative addition amount and manufacturer information, and then put into the warehouse for storage;

[0076] S6: The packaged food in the warehouse is transported to the self-service sales terminal or the physical store sales terminal by transportation vehicles;

[0077] S7: During the transportation process, the GPS positioning module collects the trajectory and coordinates of the transportation process and uploads them to the food transportation database;

[0078] S8: The processor determines whether the transportation is normal according to the trajectory and coordinates of the transportation process. If not, an alarm text message is sent to the staff of the self-service sales terminal or the physical store sales terminal; if so, the self-service sales terminal or the physical store sales terminal is normally entered for sales; step S8 includes:

[0079] S81: During the transportation process, the GPS positioning module collects positioning coordinates every set time t;

[0080] S82: Calculate the time T* of the transport vehicle's travel at this time based on the number of times u that the location coordinates W have been collected: T* = u × t

[0081] S82: Using the time T* and the road speed limit V, calculate the ideal transportation distance of the transport vehicle at this time: M = V × T*. According to the ideal transportation distance M, mark the ideal coordinate Z at a distance M from the starting point of the warehouse on the planned route;

[0082] S83: Calculate the positioning error between the ideal coordinate Z and the actually collected positioning coordinate W;

[0083] S84: When the positioning error is compared with the positioning error threshold, if the positioning error is greater than the positioning error threshold, it is determined that the transport vehicle is abnormal, and an alarm text message is sent to the staff of the self-service sales terminal or the physical store sales terminal; otherwise, the transport vehicle is transporting normally.

[0084] S9: Consumers purchase food through the sales platform built by the sales terminal monitoring system. The sales platform enters the consumer's contact information and displays the food's raw material traceability code and production traceability code on the sales platform. The raw material traceability code, production traceability code and consumer's contact information generate a food traceability file and upload it to the sales terminal database.

[0085] The present solution provides a computer-readable medium, which stores a control program of a food safety deep enhanced traceability system. When the control program of the food safety deep enhanced traceability system is executed by at least one processor, the at least one processor implements the control method of the food safety deep enhanced traceability system of any one of claims 5-8 when executing.

[0086] The present invention builds a system for in-depth traceability of food safety, constructs a complete and detailed food safety traceability platform, monitors quality assessment from the details of the planting, production, transportation and sales of food raw materials, and avoids the impact of errors in each link on food quality. At the same time, quality assessment of raw materials, finished products, transportation processes, and sales processes will be carried out at each link, and inferior raw materials and finished foods will be screened out, greatly reducing the possibility of inferior food entering the market, and realizing multi-link comprehensive monitoring. The monitored data is classified and saved, which is convenient for later data retrieval and analysis. In order to achieve good safety, strong stability of quality monitoring, reduce the difficulty of food safety traceability, easy operation, and have the advantages of high work efficiency and openness.

Claims

1. A control method for a food safety deep enhanced traceability system, the food safety deep enhanced traceability system comprising a raw material supply monitoring system, a food production monitoring system, a food transportation monitoring system and a sales terminal monitoring system; the raw material supply monitoring system, the food production monitoring system, the food transportation monitoring system and the sales terminal monitoring system all communicate wirelessly with a server built by a food safety traceability service platform; The raw material supply monitoring system includes a water source monitoring system, a climate monitoring system, a soil quality monitoring system and an insect pest monitoring system; the water source monitoring system collects water quality parameters of the water source used for irrigation at the raw material supply base; the climate monitoring system collects climate parameters of the raw material supply base during the growth of the raw materials; the soil quality monitoring system collects soil quality parameters of the raw material supply base during the growth of the raw materials; the insect pest monitoring system collects disease and insect pest parameters of the raw material supply base during the growth of the raw materials; The food production monitoring system includes a production process monitoring system and a warehouse monitoring system; the production process monitoring system is used to monitor the production parameters in the food production process and the packaging parameters in the packaging process; the warehouse monitoring system is used to monitor the storage condition parameters of the finished products when they are stored in the warehouse, and to detect the integrity of the packaging bags when they are shipped out of the warehouse; The food transportation monitoring system includes a GPS positioning system and a transportation environment monitoring system; the GPS positioning system is used to monitor the transportation track and coordinates during the food transportation process; the transportation environment monitoring system is used to monitor the transportation storage temperature and humidity during the food transportation process; The sales terminal monitoring system includes an independent sales terminal monitoring system and a physical store sales monitoring system; the independent sales terminal monitoring system and the physical store sales monitoring system are used to monitor the sales storage temperature and humidity during the food sales process, and collect consumer information after the consumer purchases; The server builds a raw material supply database, a food production database, a food transportation database and a sales terminal database, and establishes a GIS map of the raw material planting base; the raw material supply database is used to store data collected by the raw material supply monitoring system; the food production database is used to store data collected by the food production monitoring system; the food transportation database is used to store data collected by the food transportation monitoring system; the sales terminal database is used to store data collected by the sales terminal monitoring system; the processor in the server is used to analyze and process the data in the raw material supply database, the food production database, the food transportation database and the sales terminal database; The water source monitoring system includes a pH sensor, a fluoride sensor and a heavy metal sensor, wherein the pH sensor is used to detect the pH value in the irrigation water source, the fluoride sensor is used to detect the fluoride content in the irrigation water source, and the heavy metal sensor is used to detect the heavy metal content in the irrigation water source; The soil quality monitoring system includes a soil pH sensor, a soil moisture sensor and a soil nitrogen, phosphorus and potassium sensor. The soil pH sensor is used to detect the pH of the soil in the raw material supply base, the soil moisture sensor is used to detect the moisture of the soil, and the soil nitrogen, phosphorus and potassium sensor is used to detect the nitrogen, phosphorus and potassium content of the soil; The production parameters include the heating temperature of the food by the production equipment, the ratio of raw materials, the cooking time and the amount of preservatives added, and the packaging parameters include the packaging bag material and packaging type; It is characterized in that The following steps are involved: S1: The raw material supply monitoring system collects water quality parameters, climate parameters, soil parameters and pest and disease parameters at set intervals; S2: When the raw materials are harvested, the processor uses the collected water quality parameters, climate parameters, soil parameters and pest and disease parameters to classify the harvested raw materials and select high-quality raw materials; S3: Pack the high-quality raw materials and mark them with the raw material traceability code, which contains the water quality parameters, climate parameters, soil parameters, pest and disease parameters and GPS positioning information of the planting base when the raw materials were planted, and transport them to the production enterprises for food production; S4: During the food processing, the heating temperature, raw material ratio, cooking time and preservative addition amount are uploaded to the food production database. The processor evaluates the processing quality of the food according to the heating temperature, raw material ratio, cooking time and preservative addition amount, selects high-quality food that meets the requirements, and eliminates inferior food; S5: High-quality food is packaged through the packaging process and marked with a production traceability code on the packaging. The production traceability code contains the heating temperature, raw material ratio, cooking time, preservative addition amount and manufacturer information, and then put into the warehouse for storage; S6: The packaged food in the warehouse is transported to the self-service sales terminal or the physical store sales terminal by transportation vehicles; S7: During the transportation process, the GPS positioning module collects the trajectory and coordinates of the transportation process and uploads them to the food transportation database; S8: The processor determines whether the transportation is normal according to the trajectory and coordinates of the transportation process. If not, an alarm text message is sent to the staff of the self-service sales terminal or the physical store sales terminal; if so, the self-service sales terminal or the physical store sales terminal is normally entered for sales; S9: Consumers purchase food through the sales platform built by the sales terminal monitoring system. The sales platform enters the consumer's contact information, and displays the food's raw material traceability code and production traceability code on the sales platform. The raw material traceability code, production traceability code and consumer's contact information generate a food traceability file, which is uploaded to the sales terminal database; The step S2 comprises: S21: Traverse the water quality parameters, climate parameters, soil parameters and pest and disease parameters collected during the raw material planting process to form n groups of planting parameter data sets {(S1, Q1, T1, B1), (S2, Q2, T2, B2), ···, (S n , Q n , T n , B n )}, where S n is the water quality parameter, Q n is the climate parameter, T n is the soil parameter, B n is the pest and disease parameter, and n is the number of times the raw material supply monitoring system collects the planting parameters during the raw material planting process; S22: Establishing planting parameter threshold data sets for water quality parameters, climate parameters, soil parameters, and pest and disease parameters (S y , Q y , T y , B y ); S23: The implantation parameter data set (S n , Q n , T n , B n ) and the implantation parameter threshold data set (S y , Q y , T y , B y ) to compare the difference and obtain the planting parameter error data set (ΔS, ΔQ, ΔT, ΔB) = (S n , Q n , T n , B n )-(S y , Q y , T y , B y ), and ΔS, ΔQ, ΔT, ΔB are all positive numbers; S24: Establishing a planting parameter error threshold data set (δ S , δ Q , δ T , δ B ), and compare each parameter in the planting parameter error data set (ΔS, ΔQ, ΔT, ΔB) with the error threshold data set (δ S , δ Q , δ T , δ B ) are compared with the corresponding parameters in each column; S25: If there is a parameter in the implantation parameter error data set (ΔS, ΔQ, ΔT, ΔB) that is greater than the implantation parameter error threshold data set (δ S , δ Q , δ T , δ B ), the planting parameter data set collected this time is marked as exceeding the standard once; otherwise, it is not marked as exceeding the standard; S26: traverse the n sets of planting parameter data collected during the raw material planting process, repeat steps S23-S25, count the number of times H of exceeding the standard in the n sets of planting parameter data; compare the number of times H of exceeding the standard with the threshold value h of the number of times exceeding the standard; S27: If H ≥ h, the batch of raw materials is determined to be inferior raw materials, the processor collects the GPS positioning information of the planting base of the batch of raw materials, marks it on the GIS map, generates an inferior raw material alarm signal, and sends the inferior raw material alarm signal and GPS positioning information to the manufacturer; S28: If H < h, the batch of raw materials is determined to be high-quality raw materials; The step S8 comprises: S81: During the transportation process, the GPS positioning module collects positioning coordinates every set time t; S82: Calculate the time T* of the vehicle's travel at this time according to the number of times u collected when collecting the positioning coordinates W: T*=u×t; S82: Using the time T* and the road speed limit V, calculate the ideal transportation distance of the transport vehicle at this time: M = V × T*. According to the ideal transportation distance M, mark the ideal coordinate Z at a distance M from the starting point of the warehouse on the planned route; S83: Calculate the positioning error between the ideal coordinate Z and the actually collected positioning coordinate W; S84: When the positioning error is compared with the positioning error threshold, if the positioning error is greater than the positioning error threshold, it is determined that the transport vehicle is abnormal, and an alarm text message is sent to the staff of the self-service sales terminal or the physical store sales terminal; otherwise, the transport vehicle is transporting normally.

2. The control method of the food safety deep enhanced traceability system according to claim 1 is characterized in that: The step S4 comprises: S41: During the food processing, the heating temperature, raw material ratio, cooking time and preservative addition amount are uploaded to the food production database to generate a processing data group (R, L, P, F) of the food processing; S42: Establishing a processing parameter threshold data set for processed food (R y , L y , P y , F y ), the parameters in the processing data set (R, L, P, F) are respectively compared with the processing parameter threshold data set (R y , L y , P y , F y ) to obtain the processing parameter error data set (ΔR, ΔL, ΔP, ΔF) = (R, L, P, F) - (R y , L y , P y , F y ), ΔR, ΔL, ΔP, ΔF are all positive numbers; S43: Establishing a processing parameter error threshold data set (δ R , δ L , δ P , δ F ), the parameters in the processing parameter error data set (ΔR, ΔL, ΔP, ΔF) are compared with the processing parameter error threshold data set (δ R , δ L , δ P , δ F ) are compared with the corresponding parameters in each column; S44: If there is a parameter in the processing parameter error data set (ΔR, ΔL, ΔP, ΔF) that is greater than the processing parameter error threshold data set (δ R , δ L , δ P , δ F ), the food produced in this batch is judged to be inferior food; otherwise, it is high-quality food.

3. A computer-readable medium, which stores a control program of a food safety deep enhanced traceability system. When the control program of the food safety deep enhanced traceability system is executed by at least one processor, the at least one processor implements the control method of the food safety deep enhanced traceability system according to any one of claims 1-2.

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