Wireless detection method and system applied to stacking type fermentation smoke box

Abstract

The invention relates to a wireless detection method and system applied to a stacking type fermentation smoke box. The method comprises the following steps: acquiring binding information of a detection device and the stacking type fermentation smoke box; according to the distribution condition of the stacking type fermentation smoke boxes and the binding information, detecting devices needing to be awakened in each time period in the period are determined, and an awakening strategy is generated; issuing an awakening instruction to the detection device through the gateway according to the awakening strategy; receiving temperature and humidity detection data and gas concentration detection data in the stacking type fermentation smoke box, which are acquired and uploaded by the detection device after the detection device is awakened; according to the temperature and humidity detection data and the gas concentration detection data, whether abnormity occurs in the stacking type fermentation smoke box or not is judged; if abnormity occurs, abnormity warning is carried out; wherein the detection devices and the stacking type fermentation smoke boxes are bound in a one-to-one manner; the gateway and the detection device are configured to be a one-to-many wireless ad hoc network.

Description

Technical Field

[0001] The present application relates to the field of intelligent detection technology, and in particular, to a wireless detection method and system applied to a stack-type fermenting tobacco box. Background Art

[0002] In the prior art, there are few related technologies in the fields of tobacco mildew and insect detection for stack-type fermenting tobacco boxes, and it cannot be widely applied due to detection methods, on-site implementation difficulties, and cost issues.

[0003] As disclosed in Patent CN119470690A, a model for evaluating the mildew degree of stored tobacco leaves based on characteristic atmosphere and its application. The internal standard method is used to qualitatively and quantitatively analyze the volatile gases before and after the mildew of stored tobacco leaves. Then, the volatile gases in storage are classified according to the change amount, a change amount threshold is set, and characteristic atmospheres are screened. Then, under standard conditions, continuous mildew tests are carried out on the stored tobacco leaves to obtain the number of molds and the content of characteristic atmospheres, and a correlation relationship model between the number of molds and the content of characteristic atmospheres is established. Then, the identity and universality of the obtained model under different environmental factors are tested according to the same model data set. This solution can detect the occurrence of mildew, but this detection method cannot detect in real time whether mildew occurs, and requires expensive experimental equipment and complex test methods, and cannot be widely applied industrially.

[0004] As disclosed in Patent CN116380156A, NB-IoT wireless communication technology is used for data communication and transmission. In actual applications, a SIM card is required, and there are related problems such as real-name authentication in large-scale applications. In addition, in actual applications, the number of stacked tobacco boxes is large, and thousands of sensors detect and communicate in a closed space, there are problems such as channel interference, transmission distance, signal integrity, and power consumption, and the actual problems cannot be solved. Summary of the Invention

[0005] To at least overcome to some extent the problems of high cost, poor real-time performance, and difficulty in large-scale application in detecting stack-type fermenting tobacco boxes in the related art, the present application provides a wireless detection method and system applied to stack-type fermenting tobacco boxes.

[0006] The solution of the present application is as follows:

[0007] According to the first aspect of the embodiments of the present application, a wireless detection method applied to a stack-type fermenting tobacco box is provided, including:

[0008] Obtaining the binding information between the detection device and the stack-type fermenting tobacco box;

[0009] Determining the detection devices that need to be awakened in each time period within a cycle according to the distribution of the stack-type fermenting tobacco boxes and the binding information, and generating a wake-up strategy;

[0010] According to the wake-up strategy, a wake-up instruction is sent to the detection device through the gateway;

[0011] The receiving detection device collects and uploads the temperature and humidity detection data and gas concentration detection data in the stacking type fermentation smoke box after being awakened;

[0012] Determine whether there is any abnormality in the stacked fermentation smoke box according to the temperature and humidity detection data and the gas concentration detection data;

[0013] If an abnormality occurs, an abnormal alarm will be issued;

[0014] Wherein, the detection device is bound one-to-one with the stacking type fermentation tobacco box;

[0015] The gateway and the detection device are configured as a one-to-many wireless ad hoc network.

[0016] Preferably, the method further comprises:

[0017] According to the wake-up strategy, the scheduled wake-up time of each detection device is set through the gateway, so that the detection device automatically wakes up when the scheduled wake-up time is reached.

[0018] Preferably, the method further comprises:

[0019] Receiving a network connection request sent by the detection device through a gateway;

[0020] A communication connection is established between the detection device and the gateway, and configuration information of the communication connection is saved.

[0021] Preferably, the method further comprises:

[0022] The gateway with the best connection signal with the detection device is used as the normal connection gateway of the detection device, and other connectable gateways except the normal connection gateway are used as candidate connection gateways of the detection device.

[0023] Preferably, after receiving the temperature and humidity detection data and the gas concentration detection data, the method further includes:

[0024] The temperature and humidity detection data and the gas concentration detection data are screened, and duplicate or missing data therein are removed.

[0025] Preferably, when an abnormality occurs, the method further comprises:

[0026] Abnormal temperature and humidity detection data, and / or gas concentration detection data are saved.

[0027] Preferably, the method further comprises:

[0028] Locate the abnormal stack fermentation tobacco box according to the binding information.

[0029] Preferably, when an abnormality occurs, it is judged whether an abnormality occurs in the stack fermentation tobacco box according to the temperature and humidity detection data and the gas concentration detection data, including:

[0030] Obtain historical temperature and humidity data and historical gas concentration data;

[0031] Determine the normal temperature threshold, normal humidity threshold and normal gas concentration threshold according to the historical temperature and humidity data and the historical gas concentration data;

[0032] Judge whether the temperature and humidity detection data exceeds the normal temperature threshold;

[0033] If it exceeds, it is determined that there is a temperature abnormality in the stack fermentation tobacco box;

[0034] Judge whether the temperature and humidity detection data exceeds the normal humidity threshold;

[0035] If it exceeds, it is determined that there is a humidity abnormality in the stack fermentation tobacco box;

[0036] Judge whether the gas concentration detection data exceeds the normal gas concentration threshold;

[0037] If it exceeds, it is determined that there is a gas concentration abnormality in the stack fermentation tobacco box.

[0038] According to the second aspect of the embodiments of the present application, a wireless detection system applied to a stack fermentation tobacco box is provided, including:

[0039] Detection devices, gateways and cloud platforms;

[0040] Both the gateway and the detection device are multiple;

[0041] The cloud platform is in wired communication connection with each gateway;

[0042] Each gateway is in wireless communication connection with multiple detection devices;

[0043] The detection device is only in wireless communication connection with one gateway at the same time;

[0044] The cloud platform is used to execute the wireless detection method applied to the stack fermentation tobacco box as described in any one of the above.

[0045] The technical solution provided by the present application may include the following beneficial effects:

[0046] In this technical solution, the detection device is bound to the stack fermentation tobacco box one by one, avoiding data confusion that may occur in many-to-one or one-to-many bindings, and simplifying data location and subsequent alarm responsibility division.

[0047] There are a large number of stacked tobacco boxes, generally thousands or thousands of boxes of tobacco in a warehouse. Data communication for thousands of fermentation boxes is a difficult problem, and existing solutions are difficult to solve the communication and transmission problems of massive data. In this technical solution, the spatial distribution of stacked fermentation tobacco boxes in the warehouse and the historical data upload rules of each node are considered, and the wake-up timing is dynamically planned to balance the wake-up frequency of each detection device and the data demand. Avoiding channel congestion and peak energy consumption caused by simultaneous wake-up of all detection devices, and realizing load balancing and power consumption control at the network level.

[0048] Adopting a centralized gateway scheduling to uniformly manage the wake-up times of each detection device can improve the network coordination ability and reduce the signal competition between detection devices. The gateway forms an ad-hoc network with multiple detection devices, and each node can automatically select the best gateway to access, expanding the network coverage and improving the path redundancy. The ad-hoc network structure reduces the dependence on a single-point infrastructure and enhances the anti-interference and self-recovery capabilities of the system in a complex warehouse environment.

[0049] After the detection device is awakened, it immediately measures the environmental parameters and forwards them to the cloud platform through the gateway, shortening the delay from data collection to processing and realizing near "real-time" monitoring. The automatic judgment and warning mechanism based on thresholds enables managers to know abnormalities such as mildew or pests in the tobacco box in the first time, effectively reducing the loss of tobacco leaves.

[0050] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit this application. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] The drawings here are incorporated into the specification and form a part of this specification, showing embodiments consistent with this application, and are used together with the specification to explain the principles of this application.

[0052] Figure 1 It is a schematic flowchart of a wireless detection method applied to stacked fermentation tobacco boxes provided by an embodiment of this application;

[0053] Figure 2 It is a schematic flowchart of a wake-up strategy in a wireless detection method applied to stacked fermentation tobacco boxes provided by an embodiment of this application;

[0054] Figure 3 It is a schematic structural diagram of a wireless detection system applied to stacked fermentation tobacco boxes provided by an embodiment of this application;

[0055] Figure 4 It is a schematic structural diagram of a detection device provided by an embodiment of this application.

[0056] Reference numerals: Detection device - 101; Gateway - 201; Cloud platform - 301. Detailed implementation manners

[0057] Here, exemplary embodiments will be described in detail, and examples thereof are shown in the accompanying drawings. When the following description refers to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementation manners described in the following exemplary embodiments do not represent all implementation manners consistent with the present application. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0058] Embodiment 1

[0059] Figure 1 is a flowchart of a wireless detection method applied to a stacked fermentation tobacco box according to an embodiment of the present application. Referring to Figure 1 , a wireless detection method applied to a stacked fermentation tobacco box includes:

[0060] S11: Obtain the binding information between the detection device and the stacked fermentation tobacco box;

[0061] S12: Determine the detection devices that need to be awakened in each time period within a cycle according to the distribution of the stacked fermentation tobacco boxes and the binding information, and generate a wake-up strategy;

[0062] S13: Send a wake-up instruction to the detection device through the gateway according to the wake-up strategy;

[0063] S14: Receive the temperature and humidity detection data and gas concentration detection data inside the stacked fermentation tobacco box collected and uploaded after the detection device is awakened;

[0064] S15: Determine whether an abnormality occurs inside the stacked fermentation tobacco box according to the temperature and humidity detection data and the gas concentration detection data;

[0065] S16: If an abnormality occurs, perform an abnormality alarm;

[0066] Among them, the detection device and the stacked fermentation tobacco box are bound one-to-one;

[0067] The gateway and the detection device are configured as a one-to-many wireless ad hoc network.

[0068] It should be noted that the detection device can be placed in the stacked fermentation tobacco box for long-term use.

[0069] In the technical solution of the present application, the detection device and the stacked fermentation tobacco box are bound one-to-one, which avoids data confusion that may occur in many-to-one or one-to-many bindings, and simplifies data positioning and subsequent alarm responsibility division.

[0070] There are a large number of stacked tobacco boxes, generally thousands or thousands of boxes of tobacco in a warehouse. Data communication for thousands of fermentation boxes is a difficult problem, and existing solutions are difficult to solve the communication and transmission problems of massive data. In this technical solution, the spatial distribution of stacked fermentation tobacco boxes in the warehouse and the historical data upload rules of each node are considered, and the wake-up timing is dynamically planned to balance the wake-up frequency of each detection device and the data demand. Avoiding channel congestion and peak power consumption caused by simultaneous wake-up of all detection devices, and realizing load balancing and power consumption control at the network level.

[0071] Adopting centralized gateway scheduling to uniformly manage the wake-up moments of each detection device can improve the network coordination ability and reduce the signal competition between detection devices. The gateway forms an ad-hoc network with multiple detection devices, and each node can automatically select the best gateway to access, expanding the network coverage and improving the path redundancy. The ad-hoc network structure reduces the dependence on single-point infrastructure and enhances the anti-interference and self-recovery capabilities of the system in complex warehouse environments.

[0072] After the detection device is awakened, it immediately measures the environmental parameters and forwards them to the cloud platform through the gateway, shortening the delay from data acquisition to processing and realizing near "real-time" monitoring. The automatic judgment and alarm mechanism based on thresholds enables managers to know abnormalities such as mildew or pests in the tobacco box in the first time, effectively reducing the loss of tobacco leaves.

[0073] Embodiment 2

[0074] It should be noted that with reference to Figure 2 , the method further includes:

[0075] According to the wake-up strategy, the gateway sets the timed wake-up time of each detection device so that the detection device wakes up automatically when the timed wake-up time is reached.

[0076] The working process of the detection device is as follows: after the system is powered on, it is initialized. After the initialization is completed, it starts to bind the wireless gateway. If no wake-up instruction is received, the system wakes up regularly, collects sensor data, uploads the data to the server or cloud platform through wireless timing, and then enters the sleep state; if a wake-up instruction is received, the system wakes up, collects sensor data, and uploads the data to the server or cloud platform in real time through wireless communication.

[0077] In this embodiment, on the basis of the original "instantly issuing wake-up instructions", the wake-up plan is further decentralized to the local timer configuration of each node by the gateway.

[0078] The detection device independently executes the wake-up without having to wait for the gateway to remotely issue instructions each time, effectively sharing the instruction pressure of the gateway in high-concurrency scenarios.

[0079] The timed wake-up is triggered by a local timer, reducing the repeated handshakes and instruction transmissions between the gateway and the detection device; even if the gateway is temporarily unreachable, the detection device can still wake up and collect data according to the predetermined plan.

[0080] Embodiment III

[0081] It should be noted that the method further includes:

[0082] Receiving a networking request sent by the detection device through the gateway;

[0083] Establishing a communication connection between the detection device and the gateway, and saving the configuration information of the communication connection.

[0084] When the detection device is not connected to the gateway, make a device networking request, connect to the nearest network management device, and save the configuration information.

[0085] Introduce the "device actively requests to access the network" mechanism to replace the cumbersome way of pre-hardcoding or manual configuration. The gateway is responsible for completing the handshake, authentication, and saving the network parameters of the terminal (such as node ID, channel parameters, gateway priority, etc.).

[0086] After the detection device is powered on, it automatically accesses the network, greatly simplifying on-site installation and debugging. When adding or replacing a sensing device, there is no need to stop for maintenance, and it supports online rolling expansion.

[0087] Embodiment III

[0088] It should be noted that the method further includes:

[0089] Regarding the gateway with the best connection signal to the detection device as the normal connection gateway of the detection device, and regarding other connectable gateways except the normal connection gateway as the candidate connection gateways of the detection device.

[0090] When the number of stacked fermentation tobacco boxes in a single warehouse is large, multiple gateways can be configured. The multiple gateways can simultaneously perform self-organizing networking grouping on the tobacco boxes. When the detection device is simultaneously connected to 2 or more wireless gateways, select the wireless gateway with the strongest signal among them as the normal connection gateway, and regard other connectable gateways except the normal connection gateway as the candidate connection gateways of the detection device.

[0091] During the initial network access or operation process of the detection device, measure and evaluate the signal quality with each visible gateway, and dynamically select the best access point. Maintain a set of "primary / backup" gateway lists for quick switching.

[0092] The detection device always selects the gateway with the best signal to ensure the reliability of data upload and minimize the delay. When the primary gateway fails or is congested, it can quickly switch to the backup gateway to ensure that the monitoring is not interrupted, and through the management of the backup list, load balancing between multiple gateways can be achieved.

[0093] Taking 5,000 fermentation chambers as an example, 5,000 detection devices are configured on-site, and 5 gateways are configured. The number of monitoring terminals that a single gateway allows to access is not less than 2,048. When initially configuring the connection to the detection devices, multiple gateways can be linked. One of the gateways is linked according to the signal strength, and the connection configuration is saved subsequently. Wireless communication is carried out through this link. If the connection is interrupted, the link mechanism is restarted to link the gateway with the strongest signal strength.

[0094] Example 4

[0095] It should be noted that after receiving the temperature and humidity detection data and the gas concentration detection data, the method further includes:

[0096] Screen the temperature and humidity detection data and the gas concentration detection data, and eliminate the duplicate or missing data among them.

[0097] The data cleaning layer preprocesses the reported original sensing data, filtering out duplicate samples, error frames, and null records caused by communication packet loss.

[0098] In this way, the data quality can be improved: after eliminating redundant or incorrect data, the cloud data set is more accurate, and subsequent analysis / alarm is more reliable. It can also save storage and transmission resources: reduce the storage and forwarding of invalid data, and reduce the system bandwidth and storage costs. At the same time, it also reduces the false alarm rate: prevent misjudgment triggered by short-term duplicate or missing data, and improve the effectiveness of monitoring.

[0099] Example 5

[0100] It should be noted that when an abnormality occurs, the method further includes:

[0101] Save the temperature and humidity detection data and / or the gas concentration detection data where an abnormality occurs.

[0102] For the sensing records that have been determined to exceed the threshold, they are separately archived and classified for subsequent traceability and auditing. Subsequently, in-depth analysis can be carried out by combining multi-source information such as the environment and operation logs to locate the cause of the abnormality.

[0103] And the historical abnormal samples can be used to train more accurate thresholds or machine learning models.

[0104] Furthermore, the method further includes:

[0105] Locate the stack-type fermentation tobacco boxes where an abnormality occurs according to the binding information.

[0106] In this embodiment, the binding information between the detection devices registered in the system and the stack-type fermentation tobacco boxes is used to realize the mapping between the physical location and the sensing nodes.

[0107] Once an alarm is triggered, maintenance personnel can directly obtain the specific cigarette box number and storage area, eliminating the need for manual inspection of each box one by one, saving search time and improving operation efficiency and safety.

[0108] Embodiment Six

[0109] It should be noted that when an abnormality occurs, it is determined whether an abnormality occurs in the stack fermentation cigarette box based on the temperature and humidity detection data and the gas concentration detection data, including:

[0110] Obtain historical temperature and humidity data and historical gas concentration data;

[0111] Determine the normal temperature threshold, normal humidity threshold, and normal gas concentration threshold based on the historical temperature and humidity data and the historical gas concentration data;

[0112] Judge whether the temperature and humidity detection data exceeds the normal temperature threshold;

[0113] If it exceeds, it is determined that a temperature abnormality occurs in the stack fermentation cigarette box;

[0114] Judge whether the temperature and humidity detection data exceeds the normal humidity threshold;

[0115] If it exceeds, it is determined that a humidity abnormality occurs in the stack fermentation cigarette box;

[0116] Judge whether the gas concentration detection data exceeds the normal gas concentration threshold;

[0117] If it exceeds, it is determined that a gas concentration abnormality occurs in the stack fermentation cigarette box.

[0118] In this technical solution, independent threshold modeling and abnormality discrimination are carried out for three types of indicators: temperature, humidity, and gas, respectively identifying temperature, humidity, or gas concentration abnormalities, supporting differential disposal. With the accumulation of historical data, the threshold model can be continuously updated, and the monitoring effect can be continuously improved.

[0119] Embodiment Seven

[0120] A wireless detection system applied to a stack fermentation cigarette box, referring to Figure 3 , includes:

[0121] Detection device 101, gateway 102, and cloud platform 103;

[0122] Both the gateway 102 and the detection device 101 are multiple;

[0123] The cloud platform 103 is connected to each gateway 102 through wired communication;

[0124] Each gateway 102 is wirelessly connected to multiple detection devices 101;

[0125] The detection device 101 is only wirelessly communicatively connected to one gateway 102 at the same time;

[0126] The cloud platform 103 is used to execute the wireless detection method for the stacked fermentation tobacco boxes as described in any of the above embodiments.

[0127] It should be noted that, with reference to Figure 4 , the detection device 101 includes a wireless communication module (with antenna), a temperature and humidity detection module, a gas concentration detection module, a power supply module, an NFC module, a main controller, etc.

[0128] One detection device 101 is placed in each stacked fermentation tobacco box, and the detection device 101 can be bound to the fermentation box label (barcode, QR code) through the internal NFC module by a barcode scanner.

[0129] The detection device 101 is powered by the battery in the power supply module. Through low-power design, a single battery can be used for more than 3 years. The shell protection level of the detection device 101 meets the IP65 protection level, and the design standard refers to the mine safety and coal safety designs.

[0130] The gateway 102 includes a wireless communication module (with antenna), a wireless gateway 102, a 4G / 5G / ETH module, and a power supply module.

[0131] The cloud platform 103 can be a local server or a cloud server deployed. The cloud platform 103 performs comprehensive information collection, analysis, and warning information release for wireless detection of tobacco mildew and pests. Through historical data, the fermentation situation of tobacco can be analyzed, and based on the real-time data transmitted by the wireless detection device 101 for tobacco mildew and pests to the cloud platform 103 through the wireless gateway 102, analysis is carried out.

[0132] When the temperature data, humidity data, and gas concentration information exceed the threshold values, a warning is issued, providing a factual basis for on-site staff to perform relevant operations.

[0133] It can be understood that the same or similar parts in the above embodiments can be referred to each other, and the content not detailed in some embodiments can be referred to the same or similar content in other embodiments.

[0134] It should be noted that in the description of this application, the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. In addition, in the description of this application, unless otherwise stated, the meaning of "a plurality of" refers to at least two.

[0135] Any process or method description depicted in the flowchart or otherwise described 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 application includes additional implementations where functions may be executed in a substantially simultaneous manner or in the reverse order according to the involved functions, rather than in the order shown or discussed, which should be understood by those skilled in the technical field of the embodiments of the present application.

[0136] It should be understood that various parts of the present application can be implemented using hardware, software, firmware, or combinations thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application-specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0137] Those of ordinary skill in the technical field can understand that all or part of the steps carried out in implementing the above-described embodiment methods can be completed by instructing relevant hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiments.

[0138] In addition, in each of the embodiments of the present application, the functional units can be integrated into a processing module, or each unit can exist physically alone, or two or more units can be integrated into one module. The above-mentioned integrated modules can be implemented in the form of hardware or in the form of software functional modules. When the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0139] The above-mentioned storage medium can be a read-only memory, a magnetic disk, an optical disk, etc.

[0140] In the description of this specification, the descriptions referring to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples" 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 application. 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.

[0141] Although the embodiments of the present application 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 application. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

Claims

1. A wireless detection method applied to a stacked fermentation tobacco box, characterized in that Including: Obtain the binding information between the detection device and the stack fermentation tobacco box; According to the distribution of the stack fermentation tobacco boxes and the binding information, determine the detection devices that need to be woken up in each time period within a cycle, and generate a wake-up strategy; According to the wake-up strategy, send a wake-up instruction to the detection device through the gateway; Receive the temperature and humidity detection data and gas concentration detection data inside the stack fermentation tobacco box collected and uploaded after the detection device is woken up; Judge whether there is an abnormality inside the stack fermentation tobacco box according to the temperature and humidity detection data and the gas concentration detection data; If an abnormality occurs, an abnormality alarm is given; Among them, the detection device and the stack fermentation tobacco box are bound one-to-one; The gateway and the detection device are configured as a one-to-many wireless ad-hoc network.

2. The method according to claim 1, characterized in that, The method further includes: According to the wake-up strategy, set the scheduled wake-up time of each detection device through the gateway, so that the detection device wakes up automatically when the scheduled wake-up time is reached.

3. The method according to claim 1, wherein The method further includes: Receive the network connection request sent by the detection device through the gateway; Establish a communication connection between the detection device and the gateway, and save the configuration information of the communication connection.

4. The method according to claim 3, wherein The method further includes: Take the gateway with the best connection signal to the detection device as the normal connection gateway of the detection device, and take the other connectable gateways except the normal connection gateway as the candidate connection gateways of the detection device.

5. The method according to claim 1, wherein After receiving the temperature and humidity detection data and the gas concentration detection data, the method further includes: Screen the temperature and humidity detection data and the gas concentration detection data, and eliminate the duplicate or missing data among them.

6. The method according to claim 1, characterized in that When an abnormality occurs, the method further includes: Save the temperature and humidity detection data and / or gas concentration detection data where the abnormality occurs.

7. The method according to claim 6, characterized in that, The method further includes: Locate the stack fermentation tobacco box where the abnormality occurs according to the binding information.

8. The method according to claim 1, characterized in that When an abnormality occurs, judging whether there is an abnormality inside the stack fermentation tobacco box according to the temperature and humidity detection data and the gas concentration detection data includes: Obtain historical temperature and humidity data and historical gas concentration data; Determine the normal temperature threshold, normal humidity threshold and normal gas concentration threshold according to the historical temperature and humidity data and the historical gas concentration data; Judge whether the temperature and humidity detection data exceeds the normal temperature threshold; If it exceeds, it is determined that there is a temperature abnormality inside the stack fermentation tobacco box; Judge whether the temperature and humidity detection data exceeds the normal humidity threshold; If it exceeds, it is determined that there is a humidity abnormality inside the stack fermentation tobacco box; Judge whether the gas concentration detection data exceeds the normal gas concentration threshold; If it exceeds, it is determined that there is a gas concentration abnormality inside the stack fermentation tobacco box.

9. A wireless detection system applied to a stacked fermentation tobacco box, characterized in that, Including: Detection device, gateway and cloud platform; Both the gateway and the detection device are multiple; The cloud platform is connected to each gateway by wire communication; Each gateway is wirelessly connected to multiple detection devices; The detection device is only wirelessly connected to one gateway at the same time; The cloud platform is used to execute the wireless detection method for the stack fermentation tobacco box according to any one of claims 1-8.

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