Adaptive wireless communication intelligent gateway optimization method

Abstract

The invention relates to the technical field of Internet of Things communication, and discloses a self-adaptive wireless communication intelligent gateway optimization method, which comprises the following steps: collecting wireless communication environment information; analyzing the wireless communication environment; if the node meets the reporting condition, triggering an active reporting mechanism, and if the node does not meet the reporting condition, not triggering; performing corresponding optimization based on the reported data content in the active reporting mechanism; by arranging the step 2 and the step 3, back-and-forth control is facilitated by adopting a dynamic polling interval adjustment mechanism, node data is acquired in real time, communication power is adjusted according to the node distance to reduce energy consumption, and compared with a fixed polling mechanism, the node energy consumption is reduced; and meanwhile, an active reporting mechanism is adopted to timely discover a node communication problem and judge whether the node meets a reporting condition or not, and if so, the node is timely reported and the active reporting mechanism is triggered, so that node abnormity and data abnormity can be timely discovered, event reporting time delay is reduced, and corresponding optimization is timely performed to improve communication stability.

Description

Technical Field

[0001] The present invention relates to the technical field of Internet of Things communication, and more specifically to an optimization method for an adaptive wireless communication intelligent gateway. Background Art

[0002] With the rapid development of the agricultural Internet of Things, the application of wireless communication technology in the agricultural field is becoming more and more extensive. However, there are still some problems in the application of existing wireless communication technologies in the agricultural Internet of Things:

[0003] 1. The traditional gateway adopts a fixed polling interval, resulting in channel congestion under high load, such as a packet loss rate greater than 15%; energy waste under low load, such as the idle power consumption ratio reaching 40%; and response delay for sudden environmental events, such as a response time exceeding 30 seconds;

[0004] 2. There are conflicts in event reporting; protocols such as LoRa adopt the ALOHA random access mechanism. When multiple nodes report simultaneously, the probability of data collision increases exponentially with the number of nodes, and the number of retransmissions increases, resulting in increased energy consumption.

[0005] In view of this, the present invention proposes an optimization method for an adaptive wireless communication intelligent gateway. Summary of the Invention

[0006] In order to overcome the above-mentioned defects of the prior art, the present invention provides an optimization method for an adaptive wireless communication intelligent gateway, which uses a dynamic polling interval adjustment mechanism for round-trip control, obtains node data in real time, and adjusts the communication power according to the node distance to reduce energy consumption; at the same time, it adopts an active reporting mechanism to timely discover and optimize node communication problems to improve communication stability, thereby solving the problems existing in the above-mentioned background art.

[0007] The present invention provides the following technical solutions: An optimization method for an adaptive wireless communication intelligent gateway, comprising the following steps:

[0008] Step 1, collect wireless communication environment information: Real-time monitor the wireless communication environment through the gateway device and collect parameters;

[0009] Step 2, analyze the wireless communication environment: Use a dynamic polling interval adjustment mechanism to process node data and determine whether the node meets the reporting conditions;

[0010] Step 3, if the node meets the reporting conditions, trigger the active reporting mechanism, and if the node does not meet the reporting conditions, do not trigger;

[0011] Step 4, perform corresponding optimizations based on the data content reported in the active reporting mechanism.

[0012] Preferably, the use of the dynamic polling interval adjustment mechanism to process node data is specifically:

[0013] Step 21: Obtain the latest polling period as the current polling period. Based on the current polling period, the gateway sends a polling signal to all nodes, requesting the nodes to return data.

[0014] Step 22: After receiving the polling signal, the node determines whether the node is within the communication range of the gateway. If it is within the communication range of the gateway, the node returns data. If it is not within the communication range of the gateway, the node enters the sleep state.

[0015] Step 23: The gateway receives the data returned by the node, determines whether the node meets the reporting conditions, and simultaneously obtains the communication distance of the next node.

[0016] Step 24: According to the communication distance of the next node, the gateway dynamically adjusts the transmission power to increase the effective communication probability with the next node.

[0017] Step 25: Repeat Step 22 and Step 24 until all nodes complete the round-trip control, and simultaneously obtain a new polling period.

[0018] Preferably, the specific method for determining whether the node is within the communication range of the gateway is as follows:

[0019] Step 221: Obtain the communication effectiveness index of the node.

[0020] Step 222: Set a determination threshold to determine the communication effectiveness index.

[0021] Preferably, the specific method for obtaining the communication effectiveness index of the node is as follows:

[0022] Obtain the received signal strength indication and the received signal strength indication reference value of the node through measurement.

[0023] Obtain the bit error rate of the node through CRC check.

[0024] The gateway records the accurate timestamp to obtain the last packet round-trip time and the maximum allowed round-trip time of the node.

[0025] Obtain the communication effectiveness index of the node based on the above data.

[0026] Preferably, the specific method for setting a determination threshold to determine the communication effectiveness index is as follows:

[0027] Set determination thresholds YU1 and YU2. YU1 is the first determination threshold, and YU1 is the second determination threshold.

[0028] When YX a ≥YU1, it is determined that the node is within the communication range of the gateway and within the effective communication range of the gateway.

[0029] When YU2 ≤ YX a <When YU1, it is determined that the node is within the communication range of the gateway but in the edge communication area of the gateway, and the retransmission compensation mechanism can be started;

[0030] When YX a <When YU2, it is determined that the node is not within the communication range, that is, the node is out of the communication range.

[0031] Preferably, the specific method for determining whether the judgment node meets the reporting condition is:

[0032] Step 231: Determine whether there is a data anomaly trigger item for the node. If there is, it is determined that the node meets the reporting condition; if not, it does not meet the reporting condition.

[0033] Step 232: Determine whether there is a link quality anomaly trigger item for the node. If there is, it is determined that the node meets the reporting condition; if not, it is determined that the node does not meet the reporting condition.

[0034] Preferably, the specific process for determining whether there is a data anomaly trigger item for the node in step 231 is:

[0035] Obtain the data threshold corresponding to the node;

[0036] Use an adaptive algorithm to dynamically update the data threshold;

[0037] If the real-time data of the node meets the data anomaly condition, the node has a data anomaly trigger item; otherwise, it does not.

[0038] Preferably, the specific process for determining whether there is a link quality anomaly trigger item for the node in step 232 includes:

[0039] Determine whether the link quality of the node meets the set link quality threshold. If it does not meet, there is a link quality trigger item; if it meets, there is no link quality trigger item.

[0040] Preferably, the specific process for determining whether there is a link quality anomaly trigger item for the node in step 232 further includes:

[0041] When the larger the value of RSSI, the better the signal quality, then:

[0042] When RSSI a <RSSI line <, there is a link quality anomaly trigger item;

[0043] When RSSI a ≥ RSSI line <, there is no link quality anomaly trigger item;

[0044] The RSSI line represents the received signal strength indication threshold, at this time the RSSI line is the minimum allowable value for the signal reception strength indication;

[0045] When the smaller the value of RSSI, the better the signal quality, then:

[0046] When the RSSI a > RSSI line there is a link quality anomaly trigger item;

[0047] When the RSSI a ≤ RSSI line there is no link quality anomaly trigger item;

[0048] The RSSI line represents the received signal strength indication threshold, at this time the RSSI line is the maximum allowable value for the received signal strength indication.

[0049] Preferably, the obtaining of the new polling period is specifically:

[0050]

[0051] wherein, ZQ new represents the new polling period; ZQ base represents the base polling period; SL hy represents the number of current active nodes, that is, the number of nodes that have not entered the sleep state; SL ref represents the total number of all existing nodes; CQI ref represents the channel quality reference value; CQI ing represents the real-time channel quality index; α represents the adjustment coefficient.

[0052] The technical effects and advantages of the present invention:

[0053] By providing Step 2 and Step 3, the present invention is conducive to performing round-trip control through the adoption of a dynamic polling interval adjustment mechanism, obtaining node data in real time and adjusting the communication power according to the node distance to reduce energy consumption, reducing the node energy consumption compared with the fixed polling mechanism; at the same time, adopting an active reporting mechanism to timely discover node communication problems, judge whether the node meets the reporting conditions, and if so, report in time and trigger the active reporting mechanism, which can timely discover node anomalies and data anomalies, reduce the event reporting delay, and perform corresponding optimizations in time to improve communication stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 is a flowchart of the adaptive wireless communication intelligent gateway optimization method of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0055] Next, in combination with the accompanying drawings in the present invention, the technical solutions in the present invention will be clearly and completely described. In addition, the forms of the various structures described in the following embodiments are merely examples, and an adaptive wireless communication intelligent gateway optimization method according to the present invention is not limited to the various structures described in the following embodiments. All other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present invention.

[0056] Embodiment 1

[0057] As Figure 1 shown, the present invention provides an adaptive wireless communication intelligent gateway optimization method, including the following steps:

[0058] Step 1, collect wireless communication environment information: Real-time monitor the wireless communication environment through the gateway device, and collect parameters such as signal strength, channel quality, number of nodes, communication distance between the gateway and the nodes, and gateway communication radius;

[0059] Step 2, analyze the wireless communication environment: Use a dynamic polling interval adjustment mechanism to process the node data, and determine whether the node meets the reporting condition;

[0060] Step 3, if the node meets the reporting condition, trigger the active reporting mechanism, and if the node does not meet the reporting condition, do not trigger; the active reporting mechanism reports the triggered items that meet the reporting condition, and the reported data content includes the triggered items of the reporting condition and the data trigger value; the triggered items of the reporting condition include data anomaly trigger items and link quality anomaly trigger items, and the data trigger value is the data value when data anomaly and link quality anomaly are triggered;

[0061] Step 4, perform corresponding optimization based on the data content reported in the active reporting mechanism; for example, if the reported data content is link quality anomaly, take corresponding optimization operations such as improving signal quality and reducing bit error rate, etc., so as to improve the link quality.

[0062] In this embodiment, it should be specifically noted that the processing of the node data by using the dynamic polling interval adjustment mechanism is specifically as follows:

[0063] Step 21: Obtain the latest polling period as the current polling period, and based on the current polling period, the gateway sends a polling signal to all nodes, requesting the nodes to return data;

[0064] Step 22: After the node receives the polling signal, determine whether the node is within the communication range of the gateway. If it is within the communication range of the gateway, the node returns data. If it is not within the communication range of the gateway, the node enters the sleep state;

[0065] Step 23: The gateway receives the data returned by the node, determines whether the node meets the reporting condition, and meanwhile obtains the communication distance of the next node;

[0066] Step 24: According to the communication distance of the next node, the gateway dynamically adjusts the transmission power to increase the effective communication probability with the next node;

[0067] Step 25: Repeat Step 22 and Step 24 until all nodes complete the round-trip control, and meanwhile obtain a new polling period.

[0068] In this embodiment, it should be specifically noted that the specific method for determining whether the node is within the communication range of the gateway is as follows:

[0069] Step 221: Obtain the communication effectiveness index of the node;

[0070] Step 222: Set a determination threshold to determine the communication effectiveness index.

[0071] In this embodiment, it should be specifically noted that the specific method for obtaining the communication effectiveness index of the node is as follows:

[0072]

[0073] Among them, YX a represents the communication effectiveness index of the a-th node; RSSI a represents the received signal strength indication of the a-th node, with the unit of dBm, which can be obtained through measurement; RSSI_base represents the reference value of the received signal strength indication, with the unit of dBm, which can be determined through experiments and is obtained by measurement at a specific distance from the gateway, such as 100 meters, in a barrier-free laboratory environment. For example, when the LoRa module is 100 meters away from the gateway, RSSI_base = -82 dBm; BER a represents the bit error rate of the a-th node, which can be obtained through CRC check. BER a ranges from 0 to 1. When BER a = 0, it means that the bit error rate of the a-th node is 0, that is, there is no error. When BER a = 1, it means that the bit error rate of the a-th node is 100%, that is, all errors; k represents the bit error rate attenuation coefficient, which reflects the influence weight of the bit error on the communication quality. In this embodiment, k = 3.5 is selected; RTT max represents the maximum allowable round-trip time, with the unit of ms, which can be set by those skilled in the art according to the network protocol. For example, in the LoRaWAN Class A mode, RTT max = 2000 ms; RTT ing_aIndicates the round-trip time of the most recent data packet for the a-th node, in ms. The gateway can record precise timestamps to obtain the total time required to send data to the node and receive the data back from the node, that is, the round-trip time of the data packet; γ represents the delay weight coefficient, which is used to balance the contribution ratio of signal strength and delay. In this embodiment, γ = 0.4 is selected.

[0074] In this embodiment, it should be specifically noted that the specific method for determining the communication effectiveness index by setting the determination threshold is as follows:

[0075] Set determination thresholds YU1 and YU2. YU1 is the first determination threshold, and YU1 is the second determination threshold;

[0076] When YX a ≥ YU1, it is determined that the node is within the communication range of the gateway and is within the effective communication range of the gateway;

[0077] When YU2 ≤ YX a < YU1, it is determined that the node is within the communication range of the gateway but is within the edge communication area of the gateway, and the retransmission compensation mechanism can be activated;

[0078] When YX a < YU2, it is determined that the node is not within the communication range, that is, the node is out of the communication range;

[0079] The values of YU1 and YU2 can be set by those skilled in the art according to the actual situation. In this embodiment, YU1 = 1 and YU2 = 0.6 are selected.

[0080] In this embodiment, it should be specifically noted that the specific method for determining whether the node meets the reporting condition is as follows:

[0081] Step 231: Determine whether there is a data anomaly trigger item for the node. If there is, it is determined that the node meets the reporting condition; if not, it does not meet the reporting condition;

[0082] Step 232: Determine whether there is a link quality anomaly trigger item for the node. If there is, it is determined that the node meets the reporting condition; if not, it is determined that the node does not meet the reporting condition.

[0083] In this embodiment, it should be specifically noted that the specific process for determining whether there is a data anomaly trigger item for the node in step 231 is as follows:

[0084] Obtain the data threshold corresponding to the node; if the node is a temperature sensor, the corresponding data is temperature; if the node is a humidity sensor, the corresponding node is humidity;

[0085] Adopt an adaptive algorithm to dynamically update the data threshold:

[0086] Ua_threshold = u a_history + β·σ a_history ;

[0087] Wherein, U a_threshold represents the data threshold of the a-th node, u a_history represents the historical data mean of the a-th node, σ a_history represents the historical data standard deviation of the a-th node, and β represents the sensitivity coefficient, satisfying β ∈ [1.5, 3]. The specific value can be set by those skilled in the art according to the actual situation. In this embodiment, β = 3 is selected;

[0088] If the real-time data of the node meets the data anomaly condition, there is a data anomaly trigger item for the node, otherwise there is no data anomaly trigger item; the data anomaly condition can be exceeding the threshold or not reaching the threshold; Exemplarily, if the node is a humidity sensor, the data threshold is 40%, and the data anomaly condition is not reaching the threshold, then there is a data anomaly trigger item when the node data, i.e., the humidity, is less than 40%; if the node is a temperature sensor, the data threshold is 35°C, and the data anomaly condition is exceeding the threshold, then there is a data anomaly trigger item when the node data, i.e., the temperature, is greater than 35°C.

[0089] In this embodiment, it should be specifically noted that the specific process of determining whether there is a link quality anomaly trigger item for the node in step 232 is as follows:

[0090] Judgment method 1:

[0091] Judge whether the link quality of the node meets the set link quality threshold. If it does not meet, there is a link quality trigger item; if it meets, there is no link quality trigger item; the link quality threshold can be set by those skilled in the art according to the actual situation, and the link quality of the node can be obtained by performing LQI measurement on the physical layer;

[0092] Judgment method 2:

[0093] When the value of RSSI is such that the larger the value, the better the signal quality, then:

[0094] When RSSI a < RSSI line there is a link quality anomaly trigger item;

[0095] When RSSI a ≥ RSSI line there is no link quality anomaly trigger item;

[0096] The RSSI line represents the received signal strength indication threshold, and at this time, RSSI line is the minimum allowable value of the signal reception strength indication;

[0097] When the smaller the RSSI value, the better the signal quality, then:

[0098] When RSSI a > RSSI line there is an abnormal link quality trigger item;

[0099] When RSSI a ≤ RSSI line there is no abnormal link quality trigger item;

[0100] The RSSI line represents the received signal strength indication threshold, and at this time, RSSI line is the maximum allowed value of the received signal strength indication;

[0101] Since in practical applications, the RSSI value is affected by various factors, including transmission power, distance, obstacles, and interference, etc., the RSSI value is not necessarily the smaller or the larger the better. Therefore, the received signal strength indication threshold needs to be set according to the specific usage scenario and device characteristics to better evaluate the signal quality; the maximum allowed value and the minimum allowed value are the link quality abnormal boundary values set by those skilled in the art according to the specific usage scenario and device characteristics, and this embodiment does not specifically limit the specific numerical values; either of the judgment method 1 and the judgment method 2 can be selected for judgment.

[0102] In this embodiment, it should be specifically noted that the formula for obtaining the communication distance of the next node can be expressed as:

[0103] where d a represents the distance between the a-th node and the gateway, Tr a represents the time when the a-th node receives the polling signal, Tr a represents the time when the polling signal is sent to the a-th node, c represents the speed of light, c = 3×10 8 , and the unit is m / s;

[0104] According to the communication distance, the gateway dynamically adjusts the transmission power, which can be specifically manifested as: when the communication distance is 0 - 50m, the transmission power can be adjusted to 10 - 14dBm; when the communication distance is 50 - 200m, the transmission power can be adjusted to 14 - 20dBm; when the communication distance exceeds 200m, the transmission power can be adjusted to 20 - 27dBm.

[0105] In this embodiment, it should be specifically noted that the specific method for obtaining the new polling period is:

[0106]

[0107] Among them, ZQ new represents a new polling period; ZQ base represents the basic polling period. In this embodiment, ZQ base is selected to be 200 ms; SL hy represents the current number of active nodes, that is, the number of nodes that have not entered the sleep state; SL ref represents the total number of all existing nodes; CQI ref represents the channel quality reference value. For example, -85 dBm corresponds to the channel reference value CQI = 5; CQI ing represents the real-time channel quality index, which can be obtained by calculating RSSI and the recognition rate; α represents the adjustment coefficient. In this embodiment, α = 0.2 is selected.

[0108] In this embodiment, it should be specifically noted that the retransmission compensation mechanism is specifically as follows:

[0109] Adjust the transmission power by establishing a signal attenuation compensation model. The signal attenuation compensation model is expressed by the formula:

[0110] Among them, P tx represents the compensated transmission power, P base represents the current transmission power, θ a represents the compensation coefficient of the a-th node. The value range of the compensation coefficient is θ a ∈[0, 0.1]. The specific value can be specifically set by those skilled in the art according to the devices corresponding to different nodes. In this embodiment, the specific value is not specifically set; ΔBH a represents the data change amount corresponding to the a-th node. The data change amount is relative to the historical average data value.

[0111] Embodiment 2

[0112] Combined with a specific application implementation scenario, when this embodiment is applied to a greenhouse, it can be further embodied as:

[0113] The gateway node can be monitoring devices such as temperature sensors and humidity sensors. In this embodiment, temperature sensors and humidity sensors are taken as examples, and other devices will not be described in detail;

[0114] Collect the communication environment information of the humidity sensor and the temperature sensor, analyze the wireless communication environment, and adopt a dynamic polling interval adjustment mechanism to process the data of the humidity sensor and the temperature sensor. When a decrease in channel quality is detected, the polling period is automatically extended, reducing the energy consumption of the humidity sensor and the temperature sensor compared to the fixed polling mechanism; determine whether the humidity sensor and the temperature sensor meet the reporting conditions. If they do, report in a timely manner and trigger the active reporting mechanism, which can promptly detect abnormalities in the humidity sensor and the temperature sensor and data abnormalities, reduce the event reporting delay, and perform corresponding optimizations in a timely manner, effectively improving communication stability.

[0115] Finally: The above are only the preferred embodiments of the present invention and are not used to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included in the protection scope of the present invention.

[0116] The above is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed in the present application can easily think of changes or replacements, which should all be covered by the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. An adaptive wireless communication intelligent gateway optimization method, characterized in that: It includes the following steps: Step 1, collect wireless communication environment information: The gateway device monitors the wireless communication environment in real time and collects parameters; Step 2, analyze the wireless communication environment: Use the dynamic polling interval adjustment mechanism to process the node data and determine whether the node meets the reporting conditions; Step 3, if the node meets the reporting conditions, trigger the active reporting mechanism, and if the node does not meet the reporting conditions, do not trigger; Step 4, perform corresponding optimization based on the data content reported in the active reporting mechanism.

2. An optimization method for an adaptive wireless communication intelligent gateway according to claim 1, characterized in that: The specific process of using the dynamic polling interval adjustment mechanism to process the node data is as follows: Step 21: Obtain the latest polling period as the current polling period. Based on the current polling period, the gateway sends a polling signal to all nodes, requesting the nodes to return data; Step 22: After the node receives the polling signal, determine whether the node is within the communication range of the gateway. If it is within the communication range of the gateway, the node returns data. If it is not within the communication range of the gateway, the node enters the sleep state; Step 23: The gateway receives the data returned by the node, determines whether the node meets the reporting conditions, and at the same time obtains the communication distance of the next node; Step 24: According to the communication distance of the next node, the gateway dynamically adjusts the transmission power to increase the effective communication probability with the next node; Step 25: Repeat Step 22 and Step 24 until all nodes complete the round-trip control, and at the same time obtain a new polling period.

3. An optimization method for an adaptive wireless communication intelligent gateway according to claim 2, wherein: The specific method for determining whether the node is within the communication range of the gateway is as follows: Step 221: Obtain the communication effectiveness index of the node; Step 222: Set a determination threshold to determine the communication effectiveness index.

4. An adaptive wireless communication intelligent gateway optimization method according to claim 3, characterized in that: The specific method for obtaining the communication effectiveness index of the node is as follows: Obtain the received signal strength indication and the received signal strength indication reference value of the node through measurement; Obtain the bit error rate of the node through CRC check; The gateway records the precise timestamp to obtain the last packet round-trip time and the maximum allowed round-trip time of the node; Based on the above data, obtain the communication effectiveness index of the node.

5. An optimization method for an adaptive wireless communication intelligent gateway according to claim 4, characterized in that: The specific method for setting the determination threshold to determine the communication effectiveness index is as follows: Set determination thresholds YU1 and YU2, where YU1 is the first determination threshold and YU1 is the second determination threshold; When YX a ≥ YU1, it is determined that the node is within the communication range of the gateway and within the effective communication range of the gateway; When YU2 ≤ YX a <When YU1, it is determined that the node is within the communication range of the gateway but in the edge communication area of the gateway, and the retransmission compensation mechanism can be started; When YX a When YU2, it is determined that the node is not within the communication range, that is, the node has left the communication range.

6. An adaptive wireless communication intelligent gateway optimization method according to claim 5, characterized in that: The specific method for determining whether the node meets the reporting conditions is as follows: Step 231: Determine whether there is a data anomaly trigger item for the node. If there is, it is determined that the node meets the reporting conditions. If not, it does not meet the reporting conditions; Step 232: Determine whether there is a link quality anomaly trigger item for the node. If there is, it is determined that the node meets the reporting conditions. If not, it is determined that the node does not meet the reporting conditions.

7. An optimization method for an adaptive wireless communication intelligent gateway according to claim 6, characterized in that: The specific process of determining whether there is a data anomaly trigger item for the node in Step 231 is as follows: Obtain the data threshold corresponding to the node; Use an adaptive algorithm to dynamically update the data threshold; If the real-time data of the node meets the data anomaly conditions, the node has a data anomaly trigger item, otherwise it does not have a data anomaly trigger item.

8. An adaptive wireless communication intelligent gateway optimization method according to claim 7, characterized in that: The specific process of determining whether there is a link quality anomaly trigger item for the node in Step 232 includes: Determine whether the link quality of the node meets the set link quality threshold. If it does not meet, there is a link quality trigger item; if it meets, there is no link quality trigger item.

9. An adaptive wireless communication intelligent gateway optimization method according to claim 8, characterized in that: The specific process of determining whether there is a link quality anomaly trigger item for the node in step 232 further includes: When the larger the RSSI value, the better the signal quality, then: When RSSI a <RSSI line there is a link quality anomaly trigger item; When RSSI a ≥ RSSI line there is no link quality anomaly trigger item; The RSSI line represents a received signal strength indication threshold, where the RSSI line is the minimum allowable value for the signal reception strength indication; When the smaller the RSSI value, the better the signal quality, then: When RSSI a > RSSI line there is a link quality anomaly trigger item; When RSSI a ≤ RSSI line there is no link quality anomaly trigger item; The RSSI line represents a received signal strength indication threshold, at which the RSSI line is the maximum allowed value for the received signal strength indication.

10. An adaptive wireless communication intelligent gateway optimization method according to claim 9, characterized in that: The obtaining of the new polling period is specifically as follows: Among them, ZQ new represents the new polling period; ZQ base represents the basic polling period; SL hy represents the current number of active nodes, that is, the number of nodes that have not entered the sleep state; SL ref represents the total number of all existing nodes; CQI ref represents the channel quality reference value; CQI ing represents the real-time channel quality index; α represents the adjustment coefficient.

Images