Agricultural product traceability system based on Internet of Things and block chain

Abstract

The invention discloses an agricultural product traceability system based on the Internet of Things and a block chain, and relates to the technical field of agricultural product traceability, the agricultural product traceability system comprises a traceability management analysis module, a comprehensive traceability processing module and a traceability management information output module, and solves the technical problems that computing resources are difficult to efficiently allocate, and server overload and response delay are easy to occur. Idle computing resources of server nodes are intelligently distributed through a comprehensive traceability processing module according to the number of traceability request signals, and the server node with the largest idle computing resource is selected for processing for a single request; for a plurality of requests, the requests and the server nodes are reasonably matched according to the relation between the number of the requests and the number of the server nodes and the processing delay of the server nodes, parallel processing is achieved, the processing capacity of the system for the multi-node requests is improved, traceability query of consumers is quickly responded, and the user experience is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of agricultural product traceability, and specifically provides an agricultural product traceability system based on the Internet of Things and blockchain. Background Art

[0002] In order to enhance consumers' experience of agricultural product safety, agricultural product manufacturers attach two-dimensional codes containing manufacturer information and agricultural product source information to the packages of the produced agricultural products. After purchasing agricultural products, consumers can obtain the manufacturer information of the produced agricultural products and the agricultural product source information by scanning the codes.

[0003] According to the patent application with the publication number CN111091398B, an agricultural product traceability system is disclosed, including: a management server, an agricultural product server, a first middleman server, and a second middleman server. The management server generates digital certificates for the agricultural product server, the first middleman server, and the second middleman server; the agricultural product server generates an agricultural product two-dimensional code based on agricultural product characteristic information, the electronic signature of the agricultural product service provider, the agricultural product information digest, and the first sub-node pointer. The first middleman server scans the agricultural product two-dimensional code and generates the first circulation information of the agricultural product containing a pointer to the parent node, the information digest of the parent node, the supplementary information of the first middleman, the electronic signature of the first middleman, the first circulation information digest of the agricultural product, and the second sub-node pointer based on the supplementary information of the first middleman. The second middleman server creates a second middleman two-dimensional code based on the second circulation information and price information of the agricultural product.

[0004] However, during the process of collecting agricultural product information, due to reasons such as manual entry errors or sensor failures, the collected data may be inaccurate or incomplete, affecting the reliability of traceability. When a large number of users initiate traceability requests simultaneously, the traditional system is difficult to efficiently allocate computing resources, and problems such as server overload and response delay are likely to occur, unable to meet users' needs for quickly obtaining traceability information. Summary of the Invention

[0005] Aiming at the deficiencies of the prior art, the present invention provides an agricultural product traceability system based on the Internet of Things and blockchain, which solves the problems of difficult efficient allocation of computing resources and easy occurrence of server overload and response delay.

[0006] To achieve the above objectives, the present invention is realized through the following technical solutions: An agricultural product traceability system based on the Internet of Things and blockchain, including:

[0007] An agricultural product data acquisition module, used to transmit the acquired agricultural product information to the agricultural product data verification and analysis module, and the agricultural product information includes geographical information, seed and seedling information, fertilization and pesticide application information, harvesting information, processing information, packaging information, and logistics information;

[0008] An agricultural product data verification and analysis module is used to segment the agricultural product information transmitted by the agricultural product data acquisition module according to the time series to obtain time period information, compare it with the pre-stored information to screen out abnormal time period information, modify it to generate modified information at the same time, generate traceability information by integrating the time period information, and transmit it to the traceability management and analysis module;

[0009] A traceability management and analysis module is used to classify the traceability information according to the data type to obtain information of the same type, perform data compression and redundancy processing on the information of the same type. For the data compression process, the DEFLATE algorithm and Delta coding are respectively used for text data and time series data to compress the data to obtain compressed data. For the redundancy processing, based on the redundant data, the impact on its corresponding associated data is backed up and deleted to obtain processed data, and the processed data is transmitted to the comprehensive traceability processing module;

[0010] A comprehensive traceability processing module is used to analyze the processed data in combination with the traceability request signal, and allocate and process the server nodes according to different numbers of traceability request signals. For a single request signal, it is matched according to the idle computing resources of the server nodes in descending order to obtain traceability processing information. For multiple request signals, an initial match is made according to the size of the idle resources, and at the same time, the request time of the request signal and the processing delay of the server node are combined for matching to generate traceability processing information, and it is transmitted to the traceability management information output module.

[0011] A traceability management information output module is used to display the obtained traceability processing information to the corresponding traceability personnel.

[0012] As a further solution of the present invention, the specific method for the agricultural product data verification and analysis module to screen out abnormal time period information is:

[0013] The agricultural product information is segmented according to the time series to obtain different time period information, which is labeled as i, and i = 1, 2,..., j, where j represents the number of time period information. The obtained time period information i is compared with the pre-stored information of the system. If the time period information i is different from the pre-stored information, it is recorded as abnormal time period information. On the contrary, if the time period information i is the same as the pre-stored information, it is not processed.

[0014] As a further solution of the present invention, the specific method for the agricultural product data verification and analysis module to generate traceability information is:

[0015] For the obtained abnormal time period information, it is modified with the pre-stored information as the standard to generate modified information. At the same time, the obtained modified information and time period information are recorded as traceability information, and then it is transmitted to the traceability management and analysis module.

[0016] As a further solution of the present invention, the specific manner in which the traceability management analysis module obtains information of the same type is as follows:

[0017] Transmit the traceability information to the blockchain ledger and the database, and classify the traceability information according to the corresponding data types according to the types of agricultural products to obtain information of the same type.

[0018] As a further solution of the present invention, the specific manner in which the traceability management analysis module performs data compression on information of the same type to obtain compressed data is as follows:

[0019] Obtain any set of information of the same type and denote it as the analysis object. Then, classify the data corresponding to the analysis object to obtain text data and time series data. Perform data compression on the obtained text data using the DEFLATE algorithm to obtain a compressed analysis object. Perform data compression on the classified time series data using Delta encoding to obtain a compressed analysis object;

[0020] And so on, perform compression processing on all information of the same type to obtain compressed data.

[0021] As a further solution of the present invention, the specific manner in which the traceability management analysis module performs redundancy processing on information of the same type to obtain processed data is as follows:

[0022] Obtain the redundant data in the information of the same type. Then, analyze the associated data where the redundant data exists, and judge the impact of deleting the redundant data on its associated data. If there is an impact, update and back up the corresponding associated data, and then delete the redundant data. If there is no impact, directly delete the redundant data;

[0023] After performing data compression and redundancy processing on the traceability information to obtain processed data, at the same time, transmit the obtained processed data to the comprehensive traceability processing module.

[0024] As a further solution of the present invention, the specific manner in which the traceability comprehensive processing module analyzes a single request signal to generate traceability processing information is as follows:

[0025] Obtain the server nodes corresponding to the blockchain ledger and label them as a, and a = 1, 2,..., b, where b represents the number of server nodes. At the same time, obtain the corresponding traceability request signals and judge the number of traceability request signals. If the number of traceability request signals is one, generate a single request signal. Conversely, if the number of traceability request signals is multiple, generate multiple request signals, and then analyze the two respectively;

[0026] Analyze a single request signal, obtain the idle computing resources corresponding to server node a, sort them in descending order of idle computing resources, and select the server node corresponding to the largest idle computing resource as the standard processing server to generate traceability processing information, and then transmit it to the traceability management information output module.

[0027] As a further solution of the present invention, the specific way for the traceability comprehensive processing module to analyze multiple request signals is as follows:

[0028] Obtain all server nodes a, and at the same time obtain the idle computing resources corresponding to server node a, sort server node a in descending order of idle computing resources, then obtain the number of request signals, and compare the number of requests with the number of server nodes a;

[0029] If the number of requests is less than the number of server nodes a, select the corresponding server nodes in descending order of idle resources for matching and generate traceability processing information;

[0030] If the number of requests is greater than the number of server nodes a, first obtain all server nodes a and match the corresponding request signals, then obtain the remaining request signals, and at the same time obtain the corresponding request times, and match them with server node a in the order of the request times to generate traceability processing information, and the specific matching method is as follows:

[0031] Obtain the remaining request signals, and at the same time obtain all server nodes a, then obtain the processing delays corresponding to server node a, sort server node a in ascending order of processing delays, and then match the sorted server node a with the request signals in the order of the request times corresponding to the request signals from front to back to generate traceability processing information.

[0032] Then transmit the generated traceability processing information to the traceability management information output module.

[0033] The present invention provides an agricultural product traceability system based on the Internet of Things and blockchain. Compared with the prior art, it has the following beneficial effects:

[0034] Through the agricultural product data verification and analysis module of the present invention, the collected agricultural product information is processed in segments according to the time series and compared with the pre-stored information, which can timely discover and correct abnormal information, ensure the accuracy and integrity of the traceability data, use the DEFLATE algorithm to compress the text data and the Delta coding to compress the time series data, and adopt the data fingerprint technology to identify and process redundant data, effectively reducing the data storage space, improving the data storage and transmission efficiency, and reducing the data storage cost.

[0035] The comprehensive traceability processing module intelligently allocates the idle computing resources of server nodes according to the number of traceability request signals. For a single request, it selects the server node with the largest idle computing resources for processing; for multiple requests, according to the relationship between the number of requests and the number of server nodes, as well as the processing latency of the server nodes, it reasonably matches the requests with the server nodes to achieve parallel processing, improving the system's processing ability for multi-node requests, quickly responding to consumers' traceability queries, and enhancing the user experience. Brief Description of the Drawings

[0036] Figure 1 It is a block diagram of the system principle of the present invention. Detailed Embodiments

[0037] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0038] Embodiment 1, please refer to Figure 1 , this application provides an agricultural product traceability system based on the Internet of Things and blockchain, including an agricultural product data acquisition module, an agricultural product data verification and analysis module, a traceability management analysis module, a comprehensive traceability processing module, and a traceability management information output module, and in combination with the attached Figure 1 It can be known that all the above functional modules are connected in a one-way electrical manner.

[0039] The agricultural product data acquisition module is used to acquire agricultural product information and simultaneously transmit the acquired agricultural product information to the agricultural product data verification and analysis module. The acquired agricultural product information includes origin information, seed and seedling information, fertilization and pesticide application information, harvesting information, processing information, packaging information, logistics information, etc.

[0040] The agricultural product data verification and analysis module is used to analyze the acquired agricultural product information and simultaneously perform segmented processing on the agricultural product information according to the time series. Here, the time series represents different processes corresponding to different periods of agricultural products, such as the processing process, transportation process, and sales process, etc., to obtain different period information, and label it as i, and i = 1, 2,..., j, where j represents the number of period information. At the same time, the obtained period information i is compared with the pre-stored information in the system. Here, the pre-stored information represents the original information of agricultural products. If the period information i is different from the pre-stored information, the corresponding period information is marked and recorded as abnormal period information. Conversely, if the period information i is the same as the pre-stored information, it is not processed;

[0041] For the obtained abnormal period information, it is modified based on the pre-stored information to generate modified information. At the same time, the obtained modified information and period information are recorded as traceability information, and the period information here represents information without abnormalities. Then it is transmitted to the traceability management analysis module.

[0042] Traceability management analysis module, which is used to analyze the obtained traceability information, transmit the traceability information to the blockchain ledger and database at the same time, classify the traceability information according to the corresponding data types to obtain information of the same type, and the data types here represent classification according to the types of agricultural products. Then, data optimization processing is performed on the obtained information of the same type, and data optimization specifically includes data compression and redundancy processing;

[0043] The specific method for data compression of information of the same type is as follows: Any group of information of the same type is obtained and recorded as the analysis object. Then, the data corresponding to the analysis object is classified to obtain text data and time series data. Here, the text data includes text and numbers, and the time series data represents data such as temperature, humidity, light intensity, and soil nutrient content during the growth process of crops. The obtained text data is compressed using the DEFLATE algorithm to obtain a compressed analysis object, and the classified time series data is compressed using Delta encoding to obtain a compressed analysis object;

[0044] And so on, all information of the same type is compressed to obtain compressed data. Specifically, before applying the DEFLATE algorithm, the text data is first simply preprocessed, and then the preprocessed text data is encoded using the LZ77 algorithm. The LZ77 algorithm works based on the sliding window mechanism. It regards the text data as a data stream, searches for repeated strings within a fixed-size sliding window, and then performs Huffman encoding after LZ77 encoding to obtain the corresponding compressed data. Huffman encoding is an entropy encoding method based on character frequencies. It first counts the frequencies of each character (including the triples generated by LZ77) in the data after LZ77 encoding, and then constructs a Huffman tree based on the frequencies. When encoding, shorter binary codes are used to represent high-frequency characters, and longer binary codes are used to represent low-frequency characters, thereby achieving further compression of the data;

[0045] For Delta encoding, first read the first data point of the time series, use it as the reference value, and store it directly. Starting from the second data point, calculate the difference between each data point and the previous data point in turn, and store the calculated difference. Since the difference is usually smaller than the original data, a more compact encoding method can be used during storage to further reduce the storage space. For example, for the temperature monitoring data 20, 21, 22, and 23 in an agricultural product warehouse, first store the first value 20, and calculate the differences 21 - 20 = 1, 22 - 21 = 1, 23 - 22 = 1. An appropriate integer type can be selected for storage according to the range of the differences. For smaller differences, byte type (8 bits) or even half-byte type (4 bits) can be used for storage.

[0046] The specific method for redundant processing of the same type of information is as follows: Obtain the redundant data in the same type of information, and here the acquisition of redundant data uses the data fingerprint technology to generate a unique data fingerprint for each piece of data. The data fingerprint is a fixed-length encoding calculated by a specific algorithm for the data content. Use the hash algorithm to generate the data fingerprint. If the fingerprints of two pieces of data are the same, it means that their data contents are exactly the same, and one of them is likely to be redundant data. Then analyze the associated data where the redundant data exists, and judge the impact of deleting the redundant data on its associated data. Here, the judgment of the data impact is specifically judged through the integrity of the associated data. If there is an impact, update and back up the corresponding associated data, and then delete the redundant data. If there is no impact, directly delete the redundant data;

[0047] After data compression and redundant processing of the traceability information, the processed data is obtained, and at the same time, the obtained processed data is transmitted to the comprehensive traceability processing module.

[0048] Comprehensive traceability processing module. This module is used to analyze the obtained processed data. Obtain the server nodes corresponding to the blockchain ledger and label them as a, where a = 1, 2,..., b, and b represents the number of server nodes. At the same time, obtain the corresponding traceability request signals and judge the number of traceability request signals. If the number of traceability request signals is one, generate a single request signal. Conversely, if the number of traceability request signals is multiple, generate multiple request signals. Then analyze the two respectively;

[0049] Analyze the single request signal, obtain the idle computing resources corresponding to the server node a, and here the idle computing resources represent the ability to perform other task processing, and sort them from largest to smallest according to the idle computing resources. At the same time, select the server node corresponding to the largest idle computing resources as the standard processing server, generate traceability processing information, and then transmit it to the traceability management information output module.

[0050] Traceability management information output module, which is used to display the obtained traceability processing information to the corresponding personnel.

[0051] Embodiment 2, this embodiment is implemented on the basis of Embodiment 1, and the differences from Embodiment 1 are as follows:

[0052] The comprehensive traceability processing module analyzes the obtained multiple request signals, and the specific analysis method is as follows:

[0053] Obtain all server nodes a, and at the same time obtain the corresponding idle computing resources of server nodes a, sort server nodes a in descending order according to the idle computing resources, then obtain the number of request signals, and compare the number of requests with the number of server nodes a;

[0054] If the number of requests is less than the number of server nodes a, then select the corresponding server nodes for matching in descending order according to the idle resources, and generate traceability processing information, and this is parallel processing here; for example, when processing the scanning code query requests of a large number of consumers, a multi-core processor can process multiple query tasks simultaneously and quickly return traceability information.

[0055] If the number of requests is greater than the number of server nodes a, first obtain all server nodes a, and match the corresponding request signals. Here, the corresponding request signals are sorted according to the generation time of the request signals, and specifically in the order from the earliest appearance time to the latest. Then obtain the remaining request signals, at the same time obtain the corresponding request times, and match them with server nodes a in sequence according to the order of the request times, and generate traceability processing information. The specific matching method is as follows:

[0056] Obtain the remaining request signals, at the same time obtain all server nodes a, then obtain the processing delay corresponding to server nodes a. Here, the processing delay represents the time duration from when the server node obtains the request signal to when it returns the traceability information, and the specific duration is calculated according to past historical data. Sort server nodes a in ascending order according to the processing delay, and then match them with the sorted server nodes a in sequence from the front to the back according to the request time corresponding to the request signal, and generate traceability processing information.

[0057] Then transmit the generated traceability processing information to the traceability management information output module.

[0058] Embodiment 3, as Embodiment 3 of the present invention, focuses on combining the implementation processes of Embodiment 1 and Embodiment 2.

[0059] For some data in the above formula, only their numerical values are taken for calculation, and the parameter units are not substituted for calculation. At the same time, the content not described in detail in this specification belongs to the prior art well-known to those skilled in the art.

[0060] The above embodiments are only used to illustrate the technical method of the present invention and not to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical method of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical method of the present invention.

Claims

1. An agricultural product traceability system based on the Internet of Things and blockchain, characterized in that: include: The agricultural product data verification and analysis module is used to process the agricultural product information transmitted by the agricultural product data acquisition module in sections according to the time series to obtain time period information, and compare and screen the abnormal time period information with the pre-stored information, and modify it to generate modification information, and generate traceability information based on the time period information, and transmit it to the traceability management and analysis module; The traceability management and analysis module is used to classify the traceability information according to the data type to obtain the same type of information, and to perform data compression and redundancy processing on the same type of information. For data compression processing, the DEFLATE algorithm and Delta encoding are used for data compression of text data and time series data to obtain compressed data. For redundancy processing, the corresponding associated data is backed up and deleted based on the impact of redundant data to obtain processed data, and the processed data is transmitted to the comprehensive traceability processing module; The comprehensive traceability processing module is used to analyze the processing data in combination with the traceability request signal, and allocate processing to the server nodes according to different numbers of traceability request signals. For a single request signal, the server nodes are sorted and matched from large to small according to their idle computing resources to obtain traceability processing information. For multiple request signals, an initial match is performed according to the size of idle resources. At the same time, the request time of the request signal and the processing delay of the server node are matched to generate traceability processing information, which is then transmitted to the traceability management information output module.

2. According to claim 1, the agricultural product traceability system based on the Internet of Things and blockchain is characterized in that: It also includes agricultural product data acquisition module and traceability management information output module; The agricultural product data acquisition module is used to transmit the acquired agricultural product information to the agricultural product data verification and analysis module, and the agricultural product information includes land information, seed and seedling information, fertilizer and drug information, harvesting information, processing information, packaging information, and logistics information; The traceability management information output module is used to display the acquired traceability processing information to the corresponding traceability personnel.

3. The agricultural product traceability system based on the Internet of Things and blockchain according to claim 1 is characterized in that: The specific method for the agricultural product data verification and analysis module to screen and obtain abnormal period information is as follows: The agricultural product information is processed in segments according to the time series to obtain different time period information, which is labeled as i, and i=1, 2, ..., j, where j represents the number of time period information. The obtained time period information i is compared with the pre-stored information of the system. If the time period information i is different from the pre-stored information, it is recorded as abnormal time period information. Otherwise, if the time period information i is the same as the pre-stored information, it is not processed.

4. According to claim 1, the agricultural product traceability system based on the Internet of Things and blockchain is characterized in that: The specific method for the agricultural product data verification and analysis module to generate traceability information is as follows: For the abnormal time period information obtained, it is modified based on the pre-stored information and the modification information is generated. At the same time, the modification information and time period information obtained are recorded as traceability information, which is then transmitted to the traceability management analysis module.

5. The agricultural product traceability system based on the Internet of Things and blockchain according to claim 1 is characterized in that: The specific method for the traceability management and analysis module to obtain the same type of information is as follows: The traceability information is transmitted to the blockchain ledger and database, and the traceability information is classified according to the corresponding data type and the type of agricultural product to obtain the same type of information.

6. The agricultural product traceability system based on the Internet of Things and blockchain according to claim 1 is characterized in that: The specific method of the traceability management and analysis module to compress the same type of information to obtain compressed data is: Obtain any group of information of the same type as the analysis object, then classify the data corresponding to the analysis object to obtain text data and time series data, use the DEFLATE algorithm to compress the obtained text data to obtain a compressed analysis object, and use Delta coding to compress the classified time series data to obtain a compressed analysis object; In this way, all information of the same type is compressed to obtain compressed data.

7. The agricultural product traceability system based on the Internet of Things and blockchain according to claim 1 is characterized in that: The specific method in which the traceability management and analysis module performs redundant processing on the same type of information to obtain processed data is as follows: Obtain redundant data from the same type of information, then analyze the associated data where the redundant data exists, and determine the impact of deleting the redundant data on its associated data. If there is an impact, update and back up the corresponding associated data, and then delete the redundant data. If there is no impact, directly delete the redundant data. The traceability information is compressed and redundantly processed to obtain processed data, and the processed data is transmitted to the comprehensive traceability processing module.

8. The agricultural product traceability system based on the Internet of Things and blockchain according to claim 1 is characterized in that: The specific method in which the traceability comprehensive processing module analyzes a single request signal to generate traceability processing information is as follows: The server node corresponding to the blockchain account book is obtained and labeled as a, and a=1, 2, ..., b, where b represents the number of server nodes. The corresponding traceability request signal is obtained at the same time, and the number of traceability request signals is judged. If the number of traceability request signals is one, a single request signal is generated. Conversely, if the number of traceability request signals is multiple, multiple request signals are generated, and then the two are analyzed respectively; Analyze the single request signal, obtain the idle computing resources corresponding to the server node a, and sort them from large to small according to the idle computing resources. At the same time, select the server node corresponding to the largest idle computing resources as the standard processing server, generate traceability processing information, and then transmit it to the traceability management information output module.

9. The agricultural product traceability system based on the Internet of Things and blockchain according to claim 8 is characterized in that: The specific way in which the traceability comprehensive processing module analyzes multiple request signals is as follows: Obtain all server nodes a, obtain the idle computing resources corresponding to server nodes a, and sort the server nodes a from large to small according to the idle computing resources, then obtain the number of request signals, and compare the number of requests with the number of server nodes a; If the number of requests is less than the number of server nodes a, the corresponding server nodes are selected in order from large to small according to the idle resources, and the traceability processing information is generated; If the number of requests is greater than the number of server nodes a, first obtain all server nodes a and match the corresponding request signals, then obtain the remaining request signals and the corresponding request times, and match them with server nodes a in the order of request times to generate traceability processing information. The specific matching method is as follows: Obtain the remaining request signals and all server nodes a at the same time, then obtain the processing delay corresponding to server node a, and sort the server nodes a from small to large according to the processing delay, then match the request time corresponding to the request signal with the sorted server nodes a in order from front to back, and generate traceability processing information; Then the generated traceability processing information is transmitted to the traceability management information output module.

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