Internet of Things temperature control management system based on temperature detection and device thereof

Abstract

The invention relates to an Internet of Things temperature control management system based on temperature detection, and the system comprises a wireless temperature label which is internally provided with a temperature detection module and is used for converting an obtained temperature value into a voltage signal, transmitting the voltage signal to a main controller, and obtaining a corresponding temperature detection value; the temperature detection module identifies an abnormal sequence with time continuity in the obtained temperature data according to a temperature abnormal sequence detection algorithm, so that false alarm caused by short-time fluctuation is avoided, and meanwhile, a potential danger trend is captured; and the traceability management system is internally provided with a two-dimensional code management unit, and the two-dimensional code management unit is in Bluetooth connection with the wireless temperature label and is used for generating a temperature detection report according to the obtained temperature record. By adopting the Internet of Things temperature control management system based on temperature detection, the loss of temperature-sensitive goods in the transportation and storage process can be obviously reduced, so that the logistics cost of the temperature-sensitive goods is reduced.

Description

Technical Field

[0001] The present invention relates to the field of intelligent logistics, especially the field of temperature detection, and specifically refers to an Internet of Things temperature control management system and device based on temperature detection. Background Art

[0002] Currently, many transported goods are extremely sensitive to temperature, such as fresh food, pharmaceuticals, biological products, etc. During transportation and storage, if the temperature exceeds the specified range, it may cause product deterioration, failure, or even the generation of harmful substances, posing a health threat to end-users and even terminal consumers. For example, in the cold chain transportation of biological products such as vaccines, improper temperature control will render the vaccines ineffective and affect the immunization effect. With the improvement of people's living standards, the consumption demand for high-quality and fresh products is increasing continuously. The fresh e-commerce, pharmaceutical and other industries are developing rapidly, and the demand for temperature-controlled logistics is also growing vigorously. For example, the rise of fresh e-commerce has led to a large number of fresh products needing to be transported to consumers through temperature-controlled logistics to ensure the freshness and quality of the products.

[0003] In recent years, the government has been increasingly strict in the supervision of industries such as food and pharmaceuticals, requiring enterprises to establish a perfect temperature-controlled logistics system to ensure the quality and safety of products during transportation and storage. For example, the drug regulatory department requires that the cold chain transportation of drugs must comply with the GSP (Good Supply Practice) standard to ensure that drugs are stored and transported within the specified temperature range.

[0004] Temperature-controlled logistics can achieve real-time monitoring and precise control of the temperature of goods through advanced technical equipment and management means, improving the efficiency of logistics operations. For example, an intelligent temperature control system can automatically adjust the temperature of cold storages and transport vehicles, reducing manual intervention and operational errors. At the same time, an efficient temperature-controlled logistics system can shorten the transportation time of goods, improve the delivery speed, and enhance the market competitiveness of enterprises. Through precise temperature control, product losses caused by temperature fluctuations can be effectively reduced. For example, in cold chain logistics, the application of temperature control technology can reduce the loss rate of fresh products to the lowest level. In addition, the optimization of temperature-controlled logistics can also reduce energy consumption and operating costs. For example, the adoption of energy-saving refrigeration equipment and optimized transportation routes can reduce energy waste and lower logistics costs.

[0005] The development of temperature-controlled logistics has also promoted the innovation and application of related technologies, such as the application of technologies such as the Internet of Things, big data, and artificial intelligence in temperature-controlled logistics, which has promoted the intelligent and digital transformation of the cold chain logistics industry. For example, through the Internet of Things technology, remote monitoring and management of temperature control equipment can be realized, and logistics distribution plans can be optimized using big data analysis. At the same time, the development of temperature-controlled logistics has also driven the coordinated development of upstream and downstream industries, such as the common progress of related industries such as refrigeration equipment manufacturing, packaging material production, and information technology services. Summary of the Invention

[0006] The object of the present invention is to overcome the above-mentioned drawbacks of the prior art and provide an Internet of Things temperature control management system and device based on temperature detection.

[0007] To achieve the above object, the Internet of Things temperature control management system and device based on temperature detection of the present invention are as follows:

[0008] The Internet of Things temperature control management system based on temperature detection is mainly characterized in that the system includes:

[0009] A wireless temperature tag, which is built with a temperature detection module for converting the acquired temperature value into a voltage signal and transmitting it to the main controller to obtain a corresponding temperature detection value; and the temperature detection module identifies an abnormal sequence with time continuity in the acquired temperature data according to the temperature abnormal sequence detection algorithm to avoid false alarms caused by short-term fluctuations and capture potential dangerous trends at the same time; and

[0010] A traceability management system, which is built with a two-dimensional code management unit. The two-dimensional code management unit is used to generate a temperature detection report according to the acquired temperature records by connecting with the wireless temperature tag via Bluetooth.

[0011] Preferably, the temperature abnormal sequence detection algorithm includes the following processing procedures:

[0012] Perform data preprocessing on the acquired temperature detection data. Among them, the data acquisition method is to collect the temperature value sequence output by the temperature sensor in real time according to the following formula:

[0013] T = {T(1), T(2), …, T(n)}

[0014] Wherein, T(i) is the temperature value at the i-th time point, and i ∈ [1, n];

[0015] Use weighted moving average to smooth the data and reduce noise interference:

[0016] T smooth (i) = αT(i) + (1 - α)T smooth (i - 1)

[0017] Wherein, α ∈ [0, 1] is a smoothing coefficient used to determine the weights of the current value and the historical value, and T smooth (0) = T(0).

[0018] Preferably, the temperature abnormal sequence detection algorithm further includes dynamic threshold calculation in the following manner:

[0019] (a) Sliding window statistics: Calculate the average value μ(i) and the standard deviation σ(i) within a sliding window of length W:

[0020]

[0021] (b) Dynamic anomaly range: Define the dynamic threshold range according to the statistical results of the sliding window:

[0022] T dyn_min (i) = μ(i) - k × σ(i)

[0023] T dyn_max (i) = μ(i) + k × σ(i)

[0024] Where k is a coefficient for adjusting the sensitivity, and its value range is 1.5 to 3.0.

[0025] Preferably, the temperature anomaly sequence detection algorithm further includes performing anomaly detection and annotation in the following manner:

[0026] (c) Single-point anomaly detection: If the temperature value T smooth (i) exceeds the dynamic range, then mark this point as an anomaly point:

[0027]

[0028] (d) Perform continuous anomaly sequence detection according to the following steps:

[0029] Set the minimum length N of continuous anomalies threshold ;

[0030] Check whether there are N ≥ N threshold consecutive points that are anomalies. If the condition is met, mark this sequence as an anomaly sequence:

[0031]

[0032] (e) Anomaly sequence merging:

[0033] For adjacent anomaly sequences, if the time interval is less than the preset threshold Δt merge , then merge them into one sequence.

[0034] Preferably, the temperature anomaly sequence detection algorithm further includes performing anomaly level classification and processing in the following manner:

[0035] Classify according to the duration and deviation degree of the anomaly sequence:

[0036] (f) Calculate the deviation degree:

[0037]

[0038] Where D seq is the average deviation degree of this anomaly sequence;

[0039] (g) Calculate the duration in the following manner:

[0040] T smoorh = t end - t start

[0041] (h) Classify the temperature anomaly level in the following manner:

[0042] Low risk: D seq < D low and T duration < T low

[0043] Medium risk: D seq ∈ [D low , D high or T duration ∈ [T low , T high

[0044] High risk: D seq > D low and T duration > T low

[0045] (i) If a high - risk anomaly sequence is detected, immediately trigger an alarm, and record the anomaly start and end times t start , t end , the number of anomaly points N, the average deviation degree D seq and the duration T duration into the system;

[0046] Finally, generate a visualization report of the abnormal temperature data, and mark the abnormal time period and the corresponding temperature values.

[0047] Preferably, the QR - code management unit specifically includes:

[0048] Identify the QR - code information content according to the identifier on the wireless temperature tag, and generate a corresponding QR - code based on the determined QR - code information. The QR - code is scanned and read by a handheld mobile device.

[0049] Preferably, the traceability management system includes:

[0050] A waybill information acquisition unit for acquiring the waybill information of the goods;

[0051] A goods information binding unit for binding the cold - chain goods with the waybill information of the goods;

[0052] ​A transportation trajectory tracking unit, which is used to record the location information of corresponding goods in real time through a positioning device during the logistics transportation process;

[0053] A central data unit, which is used to store, analyze and process the acquired information.

[0054] Preferably, the wireless temperature tag further includes a main controller, which is composed of a main control chip, a Bluetooth chip and a Bluetooth antenna. Among them,

[0055] The main control chip has a sampling port, a data interface and a communication interface. The sampling port is connected to the temperature detection module, the data interface is connected to an external memory, and the communication interface is connected to the Bluetooth chip;

[0056] The Bluetooth chip is electrically connected to the Bluetooth antenna and is used to communicate with a relay gateway device or a mobile terminal;

[0057] The Bluetooth antenna is used to receive / send Bluetooth signals.

[0058] The wireless temperature detection device is mainly characterized in that the device is used to implement the above-mentioned system and synchronize the temperature record data to a smart device.

[0059] By adopting the Internet of Things temperature control management system and device based on temperature detection of the present invention, through an effective cold chain logistics system, the loss of perishable foods during transportation and storage can be significantly reduced, the shelf life of foods can be extended, thereby reducing the cost of perishable foods, and having relatively prominent practical value. Brief Description of the Drawings

[0060] Figure 1 It is a schematic diagram of the overall structure of the Internet of Things temperature control management system based on temperature detection of the present invention.

[0061] Figure 2 It is a schematic diagram of the internal structure of the wireless temperature tag of the present invention. Detailed Embodiments

[0062] In order to be able to more clearly describe the technical content of the present invention, the following will be further described in conjunction with specific embodiments.

[0063] Before detailing the embodiments according to the present invention, it should be noted that, hereinafter, the terms "include", "comprise" or any other variant are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements but also includes other elements not expressly listed, or elements inherent to such process, method, article or device.

[0064] Please refer to Figure 1As shown, the Internet of Things temperature control management system based on temperature detection, wherein the system includes:

[0065] A wireless temperature tag, which is built with a temperature detection module, used to convert the acquired temperature value into a voltage signal and transmit it to the main controller, and obtain the corresponding temperature detection value; and the temperature detection module identifies the abnormal sequence with time continuity in the acquired temperature data according to the temperature abnormal sequence detection algorithm, avoids false alarms caused by short-term fluctuations, and captures potential dangerous trends at the same time; and

[0066] A traceability management system, which is built with a two-dimensional code management unit. The two-dimensional code management unit is used to generate a temperature detection report according to the acquired temperature record by connecting to the wireless temperature tag via Bluetooth.

[0067] As a preferred embodiment of the present invention, the temperature abnormal sequence detection algorithm includes the following processing procedures:

[0068] Perform data preprocessing on the acquired temperature detection data. Among them, the data acquisition method is to collect the temperature value sequence output by the temperature sensor in real time according to the following formula:

[0069] T = {T(1), T(2), …, T(n)}

[0070] Wherein, T(i) is the temperature value at the i-th time point, and i ∈ [1, n];

[0071] Use weighted moving average to smooth the data and reduce noise interference:

[0072] T smooth (i) = αT(i) + (1 - α)T smooth (i - 1)

[0073] Wherein, α ∈ [0, 1] is the smoothing coefficient, used to determine the weights of the current value and the historical value, and T smooth (0) = T(0).

[0074] As a preferred embodiment of the present invention, the temperature abnormal sequence detection algorithm also includes dynamic threshold calculation in the following manner:

[0075] (a) Sliding window statistics: Calculate the average value μ(i) and standard deviation σ(i) within a sliding window of length W:

[0076]

[0077] (b) Dynamic abnormal range: Define the dynamic threshold range according to the statistical results of the sliding window:

[0078] T dyn_min(i) = μ(i) - k × σ(i)

[0079] T dyn_max (i) = μ(i) + k × σ(i)

[0080] Where k is a coefficient for adjusting the sensitivity, and its value range is 1.5 to 3.0.

[0081] As a preferred embodiment of the present invention, the temperature anomaly sequence detection algorithm further includes performing anomaly detection and annotation in the following manner:

[0082] (c) Single-point anomaly detection: If the temperature value T smooth (i) exceeds the dynamic range, then mark this point as an anomaly point:

[0083]

[0084] (d) Perform continuous anomaly sequence detection according to the following steps:

[0085] Set the minimum length N threshold ;

[0086] Check whether there are consecutive N ≥ N threshold points that are anomalies. If the condition is met, then mark this sequence as an anomaly sequence:

[0087]

[0088] (e) Anomaly sequence merging:

[0089] For adjacent anomaly sequences, if the time interval is less than the preset threshold Δt merge , then merge them into one sequence.

[0090] As a preferred embodiment of the present invention, the temperature anomaly sequence detection algorithm further includes performing anomaly level classification and processing in the following manner:

[0091] Classify according to the duration and deviation degree of the anomaly sequence:

[0092] (f) Calculate the deviation degree:

[0093]

[0094] Where D seq is the average deviation degree of this anomaly sequence;

[0095] (g) Calculate the duration in the following manner:

[0096] T smooth = t end - t start

[0097] (h) The temperature anomaly level is classified as follows:

[0098] Low risk: D seq < D low and T duration < T low

[0099] Medium risk: D seq ∈ [D low , D high or T duration ∈ [T low , T high

[0100] High risk: D seq > D low and T duration > T low

[0101] (i) If a high-risk anomaly sequence is detected, an alarm is immediately triggered, and the start and end times t start , t end , the number of anomaly points N, the average deviation degree D seq and the duration T duration are all recorded in the system;

[0102] Finally, a visualization report of the abnormal temperature data is generated, and the abnormal time period and the corresponding temperature values are marked.

[0103] As a preferred embodiment of the present invention, the QR code management unit specifically includes:

[0104] According to the identifier on the wireless temperature tag, the QR code information content is identified, and the corresponding QR code is generated according to the determined QR code information. The QR code is scanned and read by a handheld mobile device.

[0105] As a preferred embodiment of the present invention, the traceability management system includes:

[0106] A waybill information acquisition unit for acquiring the waybill information of the goods;

[0107] A goods information binding unit for binding the cold chain goods with the waybill information of the goods;

[0108] A transportation track tracking unit for real-time recording of the location information of the corresponding goods through the positioning device during the logistics transportation process;

[0109] A central data unit for storing and analyzing the acquired information.

[0110] ​As a preferred embodiment of the present invention, the wireless temperature tag further includes a main controller, which is composed of a main control chip, a Bluetooth chip, and a Bluetooth antenna. Among them,

[0111] The main control chip has a sampling port, a data interface, and a communication interface. The sampling port is connected to the temperature detection module, the data interface is connected to an external memory, and the communication interface is connected to the Bluetooth chip;

[0112] The Bluetooth chip is electrically connected to the Bluetooth antenna and is used for communicating with a relay gateway device or a mobile terminal;

[0113] The Bluetooth antenna is used for receiving / sending Bluetooth signals.

[0114] This wireless temperature detection device, wherein the device is used to implement the above-mentioned system and synchronize temperature record data to a smart device.

[0115] The following further details the wireless temperature detection device, which is used for temperature monitoring and recording of items during cold chain logistics transportation and storage. At the same time, it has Bluetooth (Bluetooth 5.0) wireless communication function and can be connected to a handheld smart device (smartphone) with Bluetooth function to synchronize temperature record data to the smart device.

[0116] · Temperature range: -20.0°C to +60.0°C

[0117] · Temperature data storage

[0118] · Temperature storage interval: default 2 minutes (can be modified through Bluetooth settings)

[0119] · High and low temperature thresholds can be set,

[0120] ● Temperature tag activation method: Manual button start, and parameters can be set through the mobile phone App

[0121] ● Temperature tag stop method: Manual button shutdown, and it can be shut down and reset through the mobile phone App.

[0122] ● Bluetooth connection method: The mobile phone App obtains the unique device identifier by scanning the QR code and connects to the temperature tag without opening the box.

[0123] Traceability management system:

[0124] It is used to generate a temperature report based on temperature records and provide an audit basis for supervised products such as food, fresh produce, pharmaceuticals, vaccines, etc.

[0125] QR code management unit

[0126] Determine the QR code information content:

[0127] It may include, but is not limited to, the unique identifier of the wireless temperature tag, the unique identifier of the cold chain goods, the production batch, the production date, the expiration date, the manufacturer information, and the transportation route information, etc.

[0128] Generate a QR code:

[0129] Generate a QR code according to the determined information content, and directly paste the generated QR code outside the storage package of the cold chain goods.

[0130] Read the QR code:

[0131] A hand-held QR code scanning device is used to scan the QR code and read the information therein.

[0132] Traceability management unit

[0133] Waybill information acquisition unit:

[0134] Acquire the waybill information of the goods, such as flight, land transportation, sea transportation information, etc.

[0135] Goods information binding module:

[0136] Bind the cold chain goods with the waybill information of the goods.

[0137] Central data system:

[0138] Data storage.

[0139] Transportation track tracking module:

[0140] The location information is recorded in real time through the positioning module in the relay gateway device during the logistics transportation process.

[0141] Traceability management module:

[0142] Query, analysis and report generation functions.

[0143] The Internet of Things temperature control management system based on temperature detection specifically includes:

[0144] A temperature detection module is used to detect the ambient temperature and convert the temperature value into a voltage signal for output;

[0145] A memory is used to store temperature data records;

[0146] A main controller is used to collect the voltage signal output by the temperature detection device to obtain the corresponding temperature detection value, and save the temperature detection value in the memory;

[0147] The main controller is electrically connected to the temperature detection device and the memory respectively;

[0148] The main controller is also used to communicate with the relay gateway device or the mobile terminal, and adjust the signal acquisition frequency according to the setting value of the relay gateway device or the mobile terminal;

[0149] It is also used to adjust the set temperature threshold of the signal according to the set temperature value of the relay gateway device or the mobile terminal;

[0150] The main controller includes a Bluetooth antenna, a Bluetooth chip and a main control chip;

[0151] The Bluetooth antenna is used to receive / send Bluetooth signals;

[0152] The Bluetooth chip is electrically connected to the Bluetooth antenna, and the Bluetooth chip is used to communicate with the relay gateway device or the mobile terminal;

[0153] The main control chip has a sampling port connected to the temperature detection module, a data interface connected to the memory, and a communication interface connected to the Bluetooth chip;

[0154] The housing includes a button and two LED lights (one red, hereinafter referred to as LED-R; one green, hereinafter referred to as LED-G).

[0155] The button is divided into a long press for 2 seconds, a long press for 5 seconds, and a short press; long press for 2 seconds to turn on the machine when shutting down,

[0156] The LED lights are used to respond to button operations and indicate the device status.

[0157] Temperature measurement and storage function: Measure the temperature according to the set interval time, store it in the memory, and judge whether there is over-temperature according to the upper and lower temperature limits.

[0158] Two-dimensional code management unit: Determine the content of the two-dimensional code information, such as the unique identifier of the wireless temperature tag, the unique identifier of the cold chain goods, the production batch, the production date, the expiration date, the production manufacturer information, and the transportation route information, etc.

[0159] Generate two-dimensional code: Generate a two-dimensional code according to the determined information content, and directly paste the generated two-dimensional code outside the cold chain goods storage package.

[0160] Read two-dimensional code: Use a handheld terminal to read the two-dimensional code.

[0161] Obtain waybill information: Bind the waybill with the goods.

[0162] Transportation track tracking: Use positioning devices such as transportation vehicles, temperature tags or gateways to track the transportation track of the goods.

[0163] Temperature data monitoring: Record the temperature data during transportation and detect in real time whether it exceeds the standard.

[0164] Temperature Record Synchronization Function: Synchronize temperature records by connecting to a relay gateway device or a mobile terminal via Bluetooth.

[0165] Data Upload: Transmit temperature data and transportation track data to a central data system for recording and analysis.

[0166] Any process or method description shown in the flowchart or described otherwise herein can be understood to represent a module, segment, or portion of code including one or more executable instructions for implementing a specific logical function or process. The scope of the preferred embodiments of the present invention includes additional implementations where functions may be executed in a substantially simultaneous manner or in an order opposite to that shown or discussed, according to the functions involved, which should be understood by those skilled in the art to which the embodiments of the present invention pertain.

[0167] It should be understood that various parts of the present invention can be implemented by hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution device.

[0168] Those of ordinary skill in the art of this technology can understand that all or part of the steps carried by the method of the above embodiments can be completed by instructing relevant hardware through a program. The program can be stored in a computer-readable storage medium, and when the program is executed, it includes one or a combination of the steps of the method embodiments.

[0169] The above-mentioned storage medium can be a read-only memory, a magnetic disk, an optical disk, etc.

[0170] In the description of this specification, the descriptions referring to terms such as "one embodiment", "some embodiments", "example", "specific example", or "embodiment" etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples.

[0171] Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention.

[0172] The temperature control management system and device of the Internet of Things based on temperature detection according to the present invention can significantly reduce the loss of temperature-sensitive goods during transportation and storage through an effective temperature control cold chain logistics system, thereby reducing the logistics cost of temperature-sensitive goods and having relatively prominent practical value.

[0173] In this specification, the present invention has been described with reference to its specific embodiments. However, it is obvious that various modifications and variations can still be made without departing from the spirit and scope of the present invention. Therefore, the specification and the drawings should be regarded as illustrative rather than restrictive.

Claims

1. An Internet of Things temperature control management system based on temperature detection, characterized in that: The system comprises: A wireless temperature tag with a built-in temperature detection module for converting the acquired temperature value into a voltage signal and transmitting it to the main controller to obtain the corresponding temperature detection value; and the temperature detection module identifies the abnormal sequence with time continuity in the acquired temperature data according to the temperature abnormal sequence detection algorithm, avoiding false alarms caused by short-term fluctuations and capturing potential dangerous trends; and The traceability management system has a built-in QR code management unit, which is connected to the wireless temperature tag via Bluetooth to generate a temperature detection report based on the acquired temperature records.

2. The temperature control management system of the Internet of Things based on temperature detection according to claim 1 is characterized in that: The temperature anomaly sequence detection algorithm includes the following processing steps: The acquired temperature detection data is preprocessed, wherein the data acquisition method is to collect the temperature value sequence output by the temperature sensor in real time according to the following formula: T={T(1),T(2),…,T(n)} Where T(i) is the temperature value at the i-th time point, i∈[1,n]; Use a weighted moving average to smooth the data and reduce noise: T smooth (i)=αT(i)+(1-α)T smooth (i-1) Among them, α∈[0,1] is the smoothing coefficient, which is used to determine the weight of the current value and the historical value, T smooth (0) = T(0).

3. The temperature control management system of the Internet of Things based on temperature detection according to claim 2 is characterized in that: The temperature anomaly sequence detection algorithm also includes dynamic threshold calculation in the following manner: (a) Sliding window statistics: Calculate the mean μ(i) and standard deviation σ(i) in a sliding window of length W: (b) Dynamic anomaly range: Define the dynamic threshold range based on the statistical results of the sliding window: T dyn_min (i)=μ(i)-k×σ(i) T dyn_max (i)=μ(i)+k×σ(i) Wherein, k is the coefficient for adjusting sensitivity, and its value range is 1.5 to 3.

0.

4. The temperature control management system of the Internet of Things based on temperature detection according to claim 3 is characterized in that: The temperature anomaly sequence detection algorithm also includes anomaly detection and labeling in the following manner: (c) Single point anomaly detection: If the temperature value T smooth (i) If it exceeds the dynamic range, the point is marked as an outlier: (d) Perform continuous abnormal sequence detection according to the following steps: Set the minimum length N of consecutive exceptions threshold ; Check if there is a continuous N ≥ N threshold Points are abnormal. If the conditions are met, the sequence is marked as an abnormal sequence: (e) Abnormal sequence merging: For adjacent abnormal sequences, if the time interval is less than the preset threshold Δt merge , then merge them into one sequence.

5. The temperature control management system of the Internet of Things based on temperature detection according to claim 4 is characterized in that: The temperature anomaly sequence detection algorithm also includes anomaly level classification processing in the following manner: Classification based on the duration and degree of deviation of abnormal sequences: (f) Calculation of the degree of deviation: Among them, D seq is the average deviation degree of the abnormal sequence; (g) The duration is calculated as follows: T smooth =t end -t start (h) Temperature anomaly classification is carried out in the following manner: Low risk: D seq <D low And T duration <T low Medium risk: D seq ∈[D low ,D high ] or T duration ∈[T low ,T high ] High risk: D seq >D low And T duration >T low (i) If a high-risk abnormal sequence is detected, an alarm is triggered immediately and the abnormal start and end times t start , t end , number of abnormal points N, average deviation degree D seq and duration T duration All are recorded in the system; Finally, a visual report of abnormal temperature data is generated, with abnormal time periods and corresponding temperature values ​​marked.

6. The temperature control management system of the Internet of Things based on temperature detection according to claim 1 is characterized in that: The two-dimensional code management unit specifically includes: According to the identifier on the wireless temperature tag, the QR code information content is identified, and a corresponding QR code is generated according to the determined QR code information. The QR code is scanned and read by a handheld mobile device.

7. The temperature control management system of the Internet of Things based on temperature detection according to claim 1 is characterized in that: The traceability management system includes: A waybill information acquisition unit, used to acquire the waybill information of the goods; The cargo information binding unit is used to bind the cold chain cargo with the cargo waybill information; The transport track tracking unit is used to record the location information of the corresponding goods in real time through the relay gateway device or the positioning module in the mobile terminal during the logistics transportation process; The central data unit is used to store, analyze and process the acquired information.

8. The temperature control management system of the Internet of Things based on temperature detection according to claim 1 is characterized in that: The wireless temperature tag also includes a main controller, which is composed of a main control chip, a Bluetooth chip and a Bluetooth antenna. The main control chip has a sampling port, a data interface and a communication interface, the sampling port is connected to the temperature detection module, the data interface is connected to the external memory, and the communication interface is connected to the Bluetooth chip; The Bluetooth chip is electrically connected to the Bluetooth antenna and is used to communicate with the relay gateway device or the mobile terminal; The Bluetooth antenna is used to receive / send Bluetooth signals.

9. A wireless temperature detection device, characterized in that: The device is used to implement the system described in any one of claims 1 to 8, and synchronize the temperature recording data to the smart device.

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