A method and system for whole journey monitoring and traceability of a sample under submission

Abstract

The application discloses a kind of whole process monitoring and tracing method and system of sample for submission, wherein the method comprises: obtaining the first basic information of the sample for submission, storing the first basic information in the RFID of the sample for submission;Set transport route, set multiple information collection points on the transport route, and set RFID reader at each information collection point;When the sample for submission passes each information collection point, the first dynamic monitoring code of the sample for submission is calculated based on the timestamp of information collection and information collection point number;The sample for submission is verified based on the first dynamic monitoring code.The application can realize real-time environmental monitoring and feedback through comprehensive data analysis, and ensure the integrity and non-tamperability of data, distributed data processing and system robustness, and reduce operating costs.

Description

Technical Field

[0001] This invention belongs to the field of computer systems engineering, and in particular relates to a method and system for full-process monitoring and traceability of submitted samples. Background Technology

[0002] In modern logistics and supply chain management, ensuring the safety, quality, and integrity of products during transportation is crucial. This is especially true in industries such as pharmaceuticals, food, and high-value goods, where monitoring product temperature, humidity, and other environmental variables is paramount. In these industries, any change in the external environment can lead to a decline in product quality, resulting in economic losses and legal liabilities. Therefore, effectively monitoring and controlling the environmental conditions of products during transportation has become an urgent technological need.

[0003] With the development of technology, more and more enterprises are adopting monitoring systems based on Internet of Things (IoT) technology. These systems can collect environmental data in real time by embedding sensors in products or shipping containers and upload it to servers. This data typically includes indicators such as temperature, humidity, air pressure, and vibration, and is analyzed and monitored through a centralized management system. However, existing monitoring systems still face challenges in handling large volumes of data, real-time performance, and accuracy.

[0004] Currently, most environmental monitoring systems on the market rely on single sensor outputs, and their data processing and computation are often insufficient to fully reflect the complex changes during transportation. Furthermore, many existing systems are typically designed for centralized monitoring and data processing, which not only increases the risk of single points of failure but may also cause delays in responding to real-time data. Summary of the Invention

[0005] To address the shortcomings of the existing technology, this invention provides a method for full-process monitoring and traceability of submitted samples, comprising the following steps: Step S101: Obtain the first basic information of the submitted sample and store the first basic information in the RFID of the submitted sample; Step S103: Set up a transportation route, set up multiple information collection points on the transportation route, and set up an RFID reader / writer at each information collection point; Step S105: When the submitted sample passes through each information collection point, calculate the first dynamic monitoring code of the submitted sample based on the information collection timestamp and information collection point number, wherein the first dynamic monitoring code M(t) is calculated using the following formula: Where ΔM represents the state change at each sampling point, and n represents the sequence number of the information collection point. This represents a function related to timestamps, where t represents the time when the sampling point information was collected. Step S107: Verify the submitted sample based on the first dynamic monitoring code.

[0006] The first basic information includes the sample category, production date, supplier information, and production batch of the submitted sample.

[0007] Step S105 includes: The first dynamic monitoring code of the submitted sample is calculated locally based on the timestamp of information collection and the information collection point number. At the same time, the timestamp information, information collection point number, and status change information of the current information collection point are sent to the server; The server synchronously calculates the second dynamic monitoring code.

[0008] Step S105 further includes: in the event of a network interruption, using a local storage mechanism and an encryption algorithm, the timestamp information, information collection point number, and status change information of the current information collection point are locally saved, and automatically uploaded to the server after the network is restored.

[0009] The use of a distributed ledger ensures the immutability of all data uploaded by each information collection point and provides transparency and traceability for data queries.

[0010] Step S107 includes verifying, after the sample arrives at the testing unit, whether the first dynamic monitoring code stored in the RFID tag after each dynamic modification is consistent with the second dynamic monitoring code calculated from the data obtained from the server each time.

[0011] The method also includes setting up an electronic fence, which automatically triggers an alarm and records abnormal information when the submitted sample exceeds the designated area.

[0012] Each information collection point is equipped with an environmental sensor to monitor the temperature, humidity and other environmental parameters of the submitted sample during transportation in real time, and upload this data to the server in real time.

[0013] The electronic fence is set up with multiple geographic coordinate points and uses BeiDou positioning system technology to monitor the location of the submitted samples in real time.

[0014] This invention also proposes a system for full-process monitoring and traceability of submitted samples, which includes: The basic information acquisition module is used to acquire the first basic information of the submitted sample. RFID, which is used to be set on the outer packaging of the submitted sample and to store the first basic information; RFID readers are installed at information collection points along the transportation route. The first dynamic monitoring code calculation module is used to calculate the first dynamic monitoring code of the submitted sample based on the timestamp of information collection and the information collection point number when the submitted sample passes through each information collection point. The first dynamic monitoring code M(t) is calculated using the following formula: Where ΔM represents the state change at each sampling point, and n represents the sequence number of the information collection point. This represents a function related to timestamps, where t represents the time when the sampling point information was collected. A verification module is used to verify the submitted sample based on the first dynamic monitoring code.

[0015] Compared with the prior art, the present invention has the following beneficial effects: Traditional monitoring systems typically rely on single sensor data collection and often lack real-time dynamic analysis. In contrast, systems based on dynamic monitoring codes can collect multiple environmental parameters such as temperature and humidity in real time and perform real-time analysis through comprehensive algorithms. This capability allows companies to obtain accurate environmental data in real time, quickly respond to any anomalies during transportation, such as temperature fluctuations or humidity changes, and take timely measures to ensure sample quality.

[0016] The generation process of dynamic monitoring codes is based on multiple environmental factors and the current state of the product, meaning each monitoring code is unique and unpredictable. This approach ensures data integrity during transportation and prevents data tampering. Therefore, businesses can rely more confidently on monitoring data for decision-making, reducing potential economic losses and legal risks caused by data tampering.

[0017] By utilizing mathematical models (such as integrals and weighting factors in formulas), the dynamic monitoring code system can comprehensively consider various influencing factors (e.g., temperature, humidity, time) for data analysis. This enables the system not only to monitor environmental parameters but also to predict and alert on the current state of the product through calculations. For example, the system can predict which environmental factors will affect product quality and provide targeted optimization suggestions.

[0018] Compared to centralized monitoring systems, dynamic monitoring code systems can employ a distributed architecture, allowing multiple data collection points to independently collect data, reducing the risk of single points of failure. Even if individual nodes malfunction, the overall system can still operate normally. This design improves the system's robustness and reliability, ensuring continuous and effective monitoring functionality.

[0019] The system based on dynamic monitoring codes can dynamically adjust its parameters and functions according to industry needs. Whether in the pharmaceutical, food, or high-value goods transportation industries, the system can flexibly adapt to different monitoring requirements and provide customized solutions. This flexibility enables companies to better meet industry regulations and customer requirements, achieving full compliance.

[0020] By providing transparent monitoring data and traceability, businesses can show customers the status of samples during transportation. This transparency not only enhances customer trust but also provides a competitive advantage. Customers can view temperature and humidity monitoring records on product labels or traceability systems, thus increasing their confidence in the products they purchase.

[0021] Real-time monitoring and dynamic adjustments enable rapid response to anomalies, effectively reducing product losses and return costs caused by environmental changes. Simultaneously, data-driven intelligent decision-making systems can help businesses optimize resource allocation, reduce unnecessary labor and storage costs, and thus improve overall operational efficiency.

[0022] In practice, by utilizing dynamic monitoring code technology, businesses can not only improve the transparency of the transportation process but also enhance consumer trust. Based on real-time feedback from product monitoring data, businesses can promptly address any anomalies that occur during transportation, minimizing losses. Furthermore, through big data analytics, businesses can gain deeper market insights and optimize supply chain management. Attached Figure Description

[0023] The above and other objects, features, and advantages of exemplary embodiments of the present disclosure will become readily apparent upon reading the following detailed description with reference to the accompanying drawings. In the drawings, several embodiments of the present disclosure are illustrated by way of example and not limitation, and like or corresponding reference numerals denote like or corresponding parts, wherein: Figure 1 This is a flowchart illustrating a method for full-process monitoring and traceability of submitted samples according to an embodiment of the present invention. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this invention, and not all of them. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0025] The terminology used in the embodiments of this invention is for the purpose of describing particular embodiments only and is not intended to limit the invention. The singular forms “a,” “the,” and “the” as used in the embodiments of this invention and the appended claims are also intended to include the plural forms, and “multiple” generally includes at least two unless the context clearly indicates otherwise.

[0026] It should be understood that although the terms first, second, third, etc., may be used to describe... in the embodiments of the present invention, these... should not be limited to these terms. These terms are only used to distinguish... For example, first... may also be referred to as second... without departing from the scope of the embodiments of the present invention, and similarly, second... may also be referred to as first...

[0027] It should be understood that the term "and / or" used in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0028] Depending on the context, the words “if” or “suppose” as used here can be interpreted as “when” or “in response to determination” or “in response to detection.” Similarly, depending on the context, the phrases “if determination” or “if detection (of the stated condition or event)” can be interpreted as “when determination” or “in response to determination” or “when detection (of the stated condition or event)” or “in response to detection (of the stated condition or event).”

[0029] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that an article or device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such an article or device. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the article or device that includes said element.

[0030] The optional embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0031] Example 1 like Figure 1 As shown, this invention discloses a method for full-process monitoring and traceability of submitted samples, including the following steps: Step S101: Obtain the first basic information of the submitted sample and store the first basic information in the RFID of the submitted sample; Step S103: Set up a transportation route, set up multiple information collection points on the transportation route, and set up an RFID reader / writer at each information collection point; Step S105: When the submitted sample passes through each information collection point, calculate the first dynamic monitoring code of the submitted sample based on the information collection timestamp and information collection point number, wherein the first dynamic monitoring code M(t) is calculated using the following formula: Where ΔM represents the state change at each sampling point, and n represents the sequence number of the information collection point. This represents a function related to timestamps, where t represents the time when the sampling point information was collected. Step S107: Verify the submitted sample based on the first dynamic monitoring code.

[0032] Example 2 The present invention proposes a method for full-process monitoring and traceability of submitted samples, comprising the following steps: Step S101: Obtain the first basic information of the submitted sample and store the first basic information in the RFID of the submitted sample; Step S103: Set up a transportation route, set up multiple information collection points on the transportation route, and set up an RFID reader / writer at each information collection point; Step S105: When the submitted sample passes through each information collection point, calculate the first dynamic monitoring code of the submitted sample based on the information collection timestamp and information collection point number, wherein the first dynamic monitoring code M(t) is calculated using the following formula: Where ΔM represents the state change at each sampling point, and n represents the sequence number of the information collection point. This represents a function related to timestamps, where t represents the time when the sampling point information was collected. Step S107: Verify the submitted sample based on the first dynamic monitoring code.

[0033] The first dynamic monitoring code is specifically represented by the following formula: ,in, , which is a timestamp function, controls the degree to which the sample state decays over time, representing the amount that gradually decreases over time, affecting the calculation of the monitoring code; λ represents the decay rate constant, which determines how fast T(t) decays. A larger λ value means faster decay, and vice versa. In practical applications, λ can be correlated with the characteristics of the sample, environmental factors, or other influencing factors to quantify the impact of time on the sample state; A(n), B(n), and C(n) represent the state information at the current sampling point n. A(n) represents the physical state parameters of the sample, such as color, odor, appearance, viscosity, etc.; B(n) represents environmental condition parameters, such as temperature, humidity, light intensity, etc., which may affect the quality and stability of the sample; C(n) represents the chemical composition parameters of the sample, such as the concentration of major components and trace elements, such as nutrients, chemical additives, etc.; t0 represents the start time of recording; t n This represents the timestamp corresponding to the current sampling point n; Represents random perturbation, where N represents a normal distribution, σ is the standard deviation; α1, β1 represent the weighting coefficients associated with parameters A and B; γ i This can represent the time delay of the i-th sampling point, used to adjust the time factor considered in the calculation of the monitoring code. When calculating the sample state, it considers the response time of different samples or the influence of environmental factors. For simplicity, it can be defined as a constant related to the i-th sampling point, representing the time delay between the change in sample state and information acquisition, applicable to a fixed delay for all sampling points; C i It is a random perturbation or measurement value associated with the i-th sampling point.

[0034] Generate C using a deterministic random number generator (Pseudo-Random Number Generator, PRNG). i This ensures that the same seed is used in every calculation. This guarantees a consistent sequence of random numbers, whether generated on the server or locally: the random number seed is recorded at each sampling point; the same algorithm and seed are used to generate random perturbations on both the server and local machine. Using this consistent perturbation model ensures that all systems participating in the calculation use the same algorithm and parameters.

[0035] The specific processing procedure is as follows: Step a: Select a seed.

[0036] Before starting the calculation, choose a fixed random number seed s. For example, set s=12345.

[0037] Step b: Initialize PRNG.

[0038] Initialize the PRNG using the selected seed to ensure that the generated random number sequence is consistent each time it runs.

[0039] Step c: Generate random values.

[0040] For each sampling point i (from 1 to n), a random number r is generated using PRNG. i r i =PRNG(s,i), which will generate a deterministic random number for each i.

[0041] Step d: Calculate C i .

[0042] Based on the generated random number r i C can be calculated i C i =BaseValue+k⋅r i Where BaseValue is the baseline value and k is the magnitude of the random disturbance.

[0043] Step e: Update the formula.

[0044] The generated C i Substitute the values ​​into the original formula and perform subsequent calculations.

[0045] The first basic information includes the sample category, production date, supplier information, and production batch of the submitted sample.

[0046] Step S105 includes: The first dynamic monitoring code of the submitted sample is calculated locally based on the timestamp of information collection and the information collection point number. At the same time, the timestamp information, information collection point number, and status change information of the current information collection point are sent to the server; The server synchronously calculates the second dynamic monitoring code.

[0047] To ensure that the monitoring codes on the local client and the server are consistent, the following verification steps can be implemented: After the monitoring code is calculated on the local client and server, the two results can be compared for verification.

[0048] When sending monitoring codes, hash them and perform the same process on the server side to ensure consistent results.

[0049] Step S105 further includes: in the event of a network interruption, using a local storage mechanism and an encryption algorithm, the timestamp information, information collection point number, and status change information of the current information collection point are locally saved, and automatically uploaded to the server after the network is restored.

[0050] In one embodiment, the following steps are specifically adopted: Step S1051: Define a data structure to store the information to be uploaded. JSON format can be used for saving, for example: { "timestamp": "2023-10-18T12:34:56Z", "point_id": n, "status_change": { "A": value_A, "B": value_B, "C": value_C } } Step S1052: Select a suitable encryption algorithm (e.g., AES or RSA) to encrypt the data. Ensure that secure key management measures are used.

[0051] Step S1053: In the event of a network interruption, record the current information, encrypt it, and save it to a local file or database.

[0052] The implementation steps are as follows: import json from Crypto.Cipher import AES from Crypto.Util.Padding import pad import os def save_data_locally(data, key): # Encrypted data cipher = AES.new(key, AES.MODE_CBC) ciphertext = cipher.encrypt(pad(json.dumps(data).encode(), AES.block_size)) # Save the local file, including the initialization vector (iv). with open('local_storage.json', 'a') as f: f.write(json.dumps({ 'iv': cipher.iv.hex(), 'ciphertext': ciphertext.hex(), }) + "\n") Step S1054: After the network is restored, read the locally saved data, decrypt it, and upload it to the server.

[0053] The specific implementation is as follows: import requests from Crypto.Cipher import AES from Crypto.Util.Padding import unpad def upload_data(key): with open('local_storage.json', 'r') as f: for line in f: entry = json.loads(line) iv = bytes.fromhex(entry['iv']) ciphertext = bytes.fromhex(entry['ciphertext']) # Decrypting the data cipher = AES.new(key, AES.MODE_CBC, iv) decrypted_data = unpad(cipher.decrypt(ciphertext), AES.block_size) # Convert to dictionary data = json.loads(decrypted_data.decode()) # Upload data response = requests.post('https: / / example.com / api / upload', json=data) if response.status_code == 200: print("Data uploaded successfully!") else: print("Failed to upload data.") Step S1055: Implement network status monitoring in the application to detect when the connection can be restored.

[0054] The specific implementation is as follows: import requests import time def check_network(): while True: try: response = requests.get('https: / / example.com / api / health') if response.status_code == 200: upload_data('your_secure_key') break except requests.ConnectionError: time.sleep(5) # Check the network again after 5 seconds This scheme ensures that even in the event of a network outage, data from data collection points can be securely stored and automatically uploaded once the network is restored. Encryption is used to protect data security, ensuring the reliability and security of the entire process. This mechanism effectively improves the system's robustness and user experience.

[0055] The use of a distributed ledger ensures the immutability of all data uploaded by each information collection point and provides transparency and traceability for data queries.

[0056] In one embodiment, the system utilizes multiple nodes across the entire testing network, including data collection points, servers, and even other participants (such as testing institutions). Each node can verify data and share a ledger.

[0057] Information is collected locally at data collection points, sensors, or devices, such as timestamps, data collection point numbers, and status change information.

[0058] Before uploading data to the distributed ledger, the data is encrypted and hashed to ensure its integrity and security.

[0059] The implementation is as follows: import hashlib import json def prepare_data(timestamp, point_id, status_change): data = { "timestamp": timestamp, "point_id": point_id, "status_change": status_change } # Generate data hash value hash_value = hashlib.sha256(json.dumps(data).encode()).hexdigest() return data, hash_value Upload the data and its hash value to the distributed ledger. This can be achieved using smart contracts. The specific implementation is as follows: def upload_to_blockchain(data, hash_value): # Assuming you're using a blockchain library or API to interact with smart contracts blockchain_client.send_transaction({ "data": data, "hash": hash_value }) In a distributed ledger, users can access and verify data through query interfaces. These interfaces provide APIs for users to query data, for example: @app.route(' / api / query', methods=['GET']) def query_data(): transaction_id = request.args.get('id') data = blockchain_client.get_transaction(transaction_id) return jsonify(data), 200 Users can verify data integrity by comparing the hash value in the query results with the hash value of the original data.

[0060] The system monitors operations and records all data uploads and queries for auditing and compliance checks.

[0061] Step S107 includes verifying, after the sample arrives at the testing unit, whether the first dynamic monitoring code stored in the RFID tag after each dynamic modification is consistent with the second dynamic monitoring code calculated from the data obtained from the server each time.

[0062] In one embodiment, each dynamic monitoring code (first dynamic monitoring code) stored in the RFID tag is ensured to be unique and can be associated with each collection timestamp and related information of the sample. The RFID tag can securely store these monitoring codes to prevent tampering.

[0063] The specific implementation is as follows: { "sample_id": "123456", "dynamic_monitor_code": "hash_value_from_local_calculation", "timestamp": "2023-10-18T12:34:56Z", "previous_codes": [ "previous_hash_value_1", "previous_hash_value_2" ] } When the sample arrives at the testing unit, the following steps are performed to verify the consistency between the monitoring code in the RFID tag and the monitoring code calculated by the server: Step S1071: First, read the data from the RFID tag to obtain the sample ID and the stored dynamic monitoring code.

[0064] The specific implementation is as follows: def read_rfid_tag(tag_reader): rfid_data = tag_reader.read() return rfid_data# Returns a data dictionary containing sample IDs and monitoring codes. Step S1072: Use the sample ID to obtain the dynamic monitoring code (second dynamic monitoring code) associated with the sample from the server.

[0065] The specific implementation is as follows: def fetch_dynamic_monitor_code(sample_id): response = requests.get(f'https: / / example.com / api / get_monitor_code / {sample_id}') if response.status_code == 200: return response.json()["dynamic_monitor_code"] else: raise Exception("Failed to fetch dynamic monitor code from server.") Step S1073: Compare the first dynamic monitoring code obtained from the RFID tag with the second dynamic monitoring code obtained from the server to verify their consistency.

[0066] The specific implementation is as follows: def verify_monitor_codes(local_code, server_code): return local_code == server_code If the monitoring codes are inconsistent, error handling measures should be implemented, for example: Record error logs and save relevant information for auditing purposes; Send an alarm to relevant personnel (such as the quality control department); The sample has been temporarily isolated pending further investigation.

[0067] The method also includes setting up an electronic fence, which automatically triggers an alarm and records abnormal information when the submitted sample exceeds the designated area.

[0068] Use latitude and longitude coordinates to define the acceptable area for sample submission. You can define a polygonal or circular area to represent the geographical location where samples are allowed to be stored.

[0069] The location information of the sample is obtained periodically through the positioning module.

[0070] To determine whether a sample's current location is within a defined geofence, a function can be used, typically employing algorithms that identify points within polygons. For example, the ray casting method can be used to determine if a point is inside a polygon. def is_point_in_polygon(point, polygon): x, y = point inside = False for i in range(len(polygon)): x1, y1 = polygon[i] x2, y2 = polygon[(i + 1) % len(polygon)] if y > min(y1, y2): if y <= max(y1, y2): if x <= max(x1, x2): if y1 != y2: xinters = (y - y1) * (x2 - x1) / (y2 - y1) + x1 if x1 == x2 or x <= xinters: inside = not inside return inside When a sample is detected to have exceeded the electronic fence, an alarm is automatically triggered and abnormal information is recorded. Scheduled tasks periodically check the sample's location to ensure real-time monitoring.

[0071] Each information collection point is equipped with an environmental sensor to monitor the temperature, humidity and other environmental parameters of the submitted sample during transportation in real time, and upload this data to the server in real time.

[0072] Here is an example of sensor data reading: import Adafruit_DHT # Assuming a DHT22 sensor is used DHT_SENSOR = Adafruit_DHT.DHT22 DHT_PIN = 4# GPIO pin number def read_environment_data(): humidity, temperature = Adafruit_DHT.read_retry(DHT_SENSOR, DHT_PIN) if humidity is not None and temperature is not None: return { "temperature": temperature, "humidity": humidity } else: raise Exception("Failed to read from DHT sensor.") The read data is uploaded to the server in real time. This can be done using an HTTP POST request.

[0073] import requests def upload_data_to_server(sample_id, data): url = 'https: / / example.com / api / upload_environment_data' payload = { "sample_id": sample_id, "data": data } response = requests.post(url, json=payload) if response.status_code == 200: print("Data uploaded successfully!") else: print("Data upload failed!", response.status_code) To achieve continuous environmental monitoring, a loop can be set up to periodically read and upload sensor data: import time def monitor_environment(sample_id): while True: try: env_data = read_environment_data() upload_data_to_server(sample_id, env_data) except Exception as e: print(f"An error occurred: {e}") time.sleep(60) # Reads data every 60 seconds. Ensure the server can receive, store, and process uploaded environment data. Data can be stored in a relational database (such as MySQL) or a non-relational database (such as MongoDB). For example, API endpoint implementation: from flask import Flask, request, jsonify app = Flask(__name__) @app.route(' / api / upload_environment_data', methods=['POST']) def upload_environment_data(): data = request.json sample_id = data['sample_id'] env_data = data['data'] # Storing data to the database (details omitted) return jsonify({"status": "success"}), 200 if __name__ == '__main__': app.run(debug=True) On the server side, the received data can be monitored and analyzed in real time: An alarm mechanism is in place to automatically trigger an alarm and record any abnormalities if the temperature or humidity exceeds a preset range. Data visualization uses charts to display monitoring data, making it easier to analyze environmental changes of samples during transportation.

[0074] The electronic fence is set up with multiple geographic coordinate points and uses BeiDou positioning system technology to monitor the location of the submitted samples in real time.

[0075] Example 3 This invention also proposes a system for full-process monitoring and traceability of submitted samples, which includes: The basic information acquisition module is used to acquire the first basic information of the submitted sample. RFID, which is used to be set on the outer packaging of the submitted sample and to store the first basic information; RFID readers are installed at information collection points along the transportation route. The first dynamic monitoring code calculation module is used to calculate the first dynamic monitoring code of the submitted sample based on the timestamp of information collection and the information collection point number when the submitted sample passes through each information collection point. The first dynamic monitoring code M(t) is calculated using the following formula: Where ΔM represents the state change at each sampling point, and n represents the total number of information collection points. This represents a function related to timestamps, where t represents the marker of the current information collection point, and t is a positive integer. A verification module is used to verify the submitted sample based on the first dynamic monitoring code.

[0076] Example 4 This disclosure provides a non-volatile computer storage medium storing computer-executable instructions that can perform the steps described in the above embodiments.

[0077] It should be noted that the computer-readable medium described in this disclosure can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this disclosure, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this disclosure, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0078] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device.

[0079] Computer program code for performing the operations of this disclosure can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (AN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0080] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0081] The units described in the embodiments of this disclosure can be implemented in software or hardware. The names of the units are not, in some cases, intended to limit the specific unit.

[0082] The preferred embodiments of the present invention have been described above to make the spirit of the present invention clearer and easier to understand, and are not intended to limit the present invention. All modifications, substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope summarized by the appended claims.

Claims

1. A method for full-process monitoring and traceability of submitted samples, comprising the following steps: Step S101: Obtain the first basic information of the submitted sample and store the first basic information in the RFID of the submitted sample; Step S103: Set up a transportation route, set up multiple information collection points on the transportation route, and set up an RFID reader / writer at each information collection point; Step S105: When the submitted sample passes through each information collection point, the first dynamic monitoring code of the submitted sample is calculated based on the information collection timestamp and the information collection point number, wherein the first dynamic monitoring code M(t) is calculated using the following formula: Where ΔM represents the state change at each sampling point, and n represents the sequence number of the information collection point. This represents a function related to timestamps, where t represents the time when the sampling point information was collected. Step S107: Verify the submitted sample based on the first dynamic monitoring code.

2. The method of claim 1, wherein the first basic information includes the sample category, production date, supplier information, and production batch of the submitted sample.

3. The method of claim 2, wherein step S105 comprises: The first dynamic monitoring code of the submitted sample is calculated locally based on the timestamp of information collection and the information collection point number. At the same time, the timestamp information, information collection point number, and status change information of the current information collection point are sent to the server; The server synchronously calculates the second dynamic monitoring code.

4. The method of claim 2, wherein step S105 further comprises: In the event of a network outage, a local storage mechanism is adopted, using an encryption algorithm to locally save the timestamp information, information collection point number, and status change information of the current information collection point, and automatically uploads them to the server after the network is restored.

5. The method as described in claim 4, wherein a distributed ledger is used to ensure the immutability of all data uploaded by each information collection point and to provide transparency and traceability for data queries.

6. The method of claim 1, wherein step S107 includes verifying, after the sample arrives at the testing unit, whether the first dynamic monitoring code stored in the RFID tag after each dynamic modification is consistent with the second dynamic monitoring code calculated from the data obtained in the server each time.

7. The method as described in claim 1 further includes setting an electronic fence, which automatically triggers an alarm and records abnormal information when the submitted sample exceeds the designated area.

8. The method as described in claim 1, wherein each information collection point is equipped with an environmental sensor for real-time monitoring of the temperature, humidity and other environmental parameters of the submitted sample during transportation, and uploading this data to the server in real time.

9. The method of claim 8, wherein the electronic fence is set up with multiple geographic coordinate points and the location of the submitted sample is monitored in real time using BeiDou positioning system technology.

10. A system for full-process monitoring and traceability of submitted samples, comprising: The basic information acquisition module is used to acquire the first basic information of the submitted sample. RFID, which is used to be set on the outer packaging of the submitted sample and to store the first basic information; RFID readers are installed at information collection points along the transportation route. The first dynamic monitoring code calculation module is used to calculate the first dynamic monitoring code of the submitted sample based on the timestamp of information collection and the information collection point number when the submitted sample passes through each information collection point. The first dynamic monitoring code M(t) is calculated using the following formula: Where ΔM represents the state change at each sampling point, and n represents the sequence number of the information collection point. This represents a function related to timestamps, where t represents the time when the sampling point information was collected. A verification module is used to verify the submitted sample based on the first dynamic monitoring code.

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