An intelligent operation management system and method applied to wireless devices

Abstract

The present invention discloses an intelligent operation management system and method applied to wireless devices, which relates to the field of artificial intelligence technology. By dividing the irrigation area of the intelligent water valve into multiple sub-areas and analyzing in combination with historical offline data, the present invention accurately monitors the device status and predicts the offline duration, ensuring the stability of the irrigation system among different areas, avoiding uneven irrigation caused by local device offline, and improving the operation efficiency. By constructing a water valve offline monitoring set and using a prediction model, the accuracy of offline duration prediction is improved to ensure the normal operation of the device; by combining historical irrigation data and a neural network model, the duration, amount and timestamp of the next irrigation are accurately calculated, and through the water valve control cache mechanism, even when the device is offline, the irrigation task can be independently executed, ensuring the stability and autonomy of the system, reducing the dependence on network connection, and ensuring the continuity and reliability of the irrigation process.

Description

Technical Field

[0001] The present invention relates to the technical field of artificial intelligence, and specifically to an intelligent operation management system and method applied to wireless devices. Background Technique

[0002] Wireless devices play a crucial role in modern society and are widely used in fields such as communication, medical, transportation, and smart home. They transmit data through wireless signals, breaking the limitations of traditional wired devices and improving flexibility and operational convenience. Among them, intelligent water valves achieve automatic adjustment and remote monitoring of water flow through wireless technology, optimizing water use management. Wireless device technology not only enhances the interconnection and interoperability between devices but also promotes the digital transformation of industry, commerce, and daily life.

[0003] In today's intelligent irrigation systems, offline problems often occur due to abnormal factors, resulting in the inability of local areas to operate normally during irrigation. When such an offline situation occurs during irrigation, it will lead to incomplete irrigation in a specific area or being out of sync with other areas, thus affecting the water resource allocation efficiency of the entire irrigation system. Due to uneven water volume distribution, some areas may experience excessive or insufficient water, further affecting the health and growth of plants. Summary of the Invention

[0004] The purpose of the present invention is to provide an intelligent operation management system and method applied to wireless devices to solve the problems raised in the prior art.

[0005] To achieve the above purpose, the present invention provides the following technical solution: An intelligent operation management method applied to wireless devices, the supply chain platform data management method includes the following steps:

[0006] Step S1: Divide the irrigation area of the intelligent water valve into multiple sub-areas, record the intelligent water valves in the sub-areas as basic intelligent water valves, and analyze and extract the historical offline data of the basic intelligent water valves in the sub-areas. The offline data represents the offline time period during which the basic intelligent water valve fails to connect to the network normally due to abnormal factor interference, and cannot upload data or receive control instructions through the network according to a predetermined period.

[0007] Step S1-1: Divide the irrigation area of the intelligent water valve. According to one intelligent water valve as one sub-area, divide the irrigation area of the intelligent water valve into multiple sub-areas, and record the intelligent water valves in the sub-areas as basic intelligent water valves;

[0008] Step S1-2: Analyze and extract the historical offline data of the basic intelligent water valves in the sub-areas. The offline data represents the offline time period during which the basic intelligent water valves fail to be normally connected to the network due to abnormal factor interference, and thus cannot upload data or receive control instructions through the network at a predetermined period. Calculate the offline duration based on the timestamp when the basic intelligent water valve starts to go offline and the timestamp when it resumes connection.

[0009] Dividing the irrigation area of the intelligent water valve into multiple sub-areas helps to achieve more refined management and control. By analyzing the historical offline data of the basic intelligent water valves, the offline time period of the devices can be identified, ensuring an accurate understanding of the system operation status. Based on the calculation of the offline duration, the offline prediction and control strategies can be optimized to improve the stability and efficiency of the system.

[0010] Step S2: Construct a water valve offline monitoring set, store the historical offline data of the basic intelligent water valves analyzed and extracted, and predict the offline duration of the basic intelligent water valves after optimizing the data in the water valve offline monitoring set, denoted as the predicted offline duration.

[0011] Step S2-1: Construct a water valve offline monitoring set and store the historical data of the basic intelligent water valves analyzed and extracted into the water valve offline monitoring set. The water valve offline monitoring set is used to store the timestamps and offline durations of the historical offline of the basic intelligent water valves.

[0012] Step S2-2: Predict the next offline duration of the basic intelligent water valves based on the offline durations in the water valve offline monitoring set, and denote the predicted offline duration as the predicted offline duration. The prediction of the offline duration uses the following formula:

[0013] ;

[0014] In the formula, H t represents the offline duration of the basic intelligent water valve when it is offline at time t; a represents the baseline value for prediction calculation; Y i represents the influence of the offline duration corresponding to the i-th timestamp in the water valve offline monitoring set on the current predicted offline duration; H t-i represents the observed value of the actual offline duration corresponding to the (t - i)-th timestamp in the water valve offline monitoring set; n represents the number of timestamps in the water valve offline monitoring set; R j represents the moving average coefficient; F t-j represents the error term at time t - j; m represents the number of error terms in the water valve offline monitoring set; b t represents the current error term at time t.

[0015] By constructing a water valve offline monitoring set and storing historical offline data, it helps to track the offline mode and frequency of the device, providing basic data support for system optimization. Through the optimized processing of historical offline data, the future offline duration of the basic intelligent water valve can be accurately predicted, thus preventing potential system problems in advance. This prediction model combines historical data of multiple timestamps, which helps to improve the accuracy of prediction and provides real-time data basis for water valve control, enhancing the reliability and stability of the system.

[0016] Step S3: Calculate the irrigation duration, irrigation volume, and irrigation timestamp for the next irrigation based on the irrigation duration and irrigation volume of each basic intelligent water valve's historical normal irrigation, construct a water valve control cache set, store the calculated irrigation duration, irrigation volume, and irrigation timestamp for the next irrigation into the water valve control cache set, and store the data of the water valve control cache set in each basic intelligent water valve controller in a cached manner;

[0017] Step S3-1: Obtain the historical normal irrigation data of each basic intelligent water valve. The historical normal irrigation data is represented as each irrigation operation record during the normal operation of the basic intelligent water valve in the past period of time, including the irrigation duration, irrigation volume, and irrigation timestamp;

[0018] Step S3-2: Based on the obtained historical normal irrigation data of each basic intelligent water valve, calculate the irrigation duration, irrigation volume, and irrigation timestamp for the next irrigation of the basic intelligent water valve in combination with the neural network model;

[0019] Step S3-3: Construct a water valve control cache set, traverse and read the calculated irrigation duration, irrigation volume, and irrigation time for the next irrigation of the basic intelligent water valve, store them into the water valve control cache set in sequence, and correspondingly read the data of each basic intelligent water valve in the water valve control cache set, and store it in each basic intelligent water valve controller in a cached manner. The basic intelligent water valve controller is used to independently control a single basic intelligent water valve, store real-time data using the cache mechanism, and adjust the switch state operation parameters of the basic intelligent water valve according to the control instruction. It can independently execute the switch control and flow regulation of the basic intelligent water valve according to the preset parameters in the offline state.

[0020] By combining historical irrigation data and the neural network model, the duration, volume, and timestamp of the next irrigation can be accurately calculated, improving the accuracy and efficiency of irrigation scheduling. Constructing a water valve control cache set and storing the data in the controller ensures that each basic intelligent water valve can operate independently and execute irrigation tasks according to the preset parameters even in the offline state. This method not only optimizes water valve management but also enhances the autonomy and stability of the system, reducing the risks brought by relying on network connections.

[0021] Step S4: Set the irrigation timestamp threshold, monitor the irrigation of the basic intelligent water valve. When it is detected that the basic intelligent water valve is offline during irrigation, construct a temporary irrigation data set, and combine the irrigation timestamp threshold and the water valve control cache set to predict the offline duration and control the basic intelligent water valve for irrigation.

[0022] Step S4-1: Set the irrigation timestamp threshold G max , and conduct real-time irrigation monitoring of the basic intelligent water valve through a flow sensor, and monitor the offline situation through the logs and event monitoring of the basic intelligent water valve;

[0023] Step S4-2: When the flow sensor monitors that the basic intelligent water valve starts irrigation, analyze and judge the logs and event monitoring of the basic intelligent water valve;

[0024] Step S4-3: When the analysis and judgment result based on the logs and event monitoring of the basic intelligent water valve is normal online, construct a temporary irrigation data set, and the temporary irrigation data set is used to store the irrigation duration, irrigation volume, and irrigation timestamp of the basic intelligent water valve;

[0025] Step S4-4: Obtain the irrigation duration data in the basic intelligent water valve controller, and combine the predicted offline duration to control the basic intelligent water valve for irrigation:

[0026] Step S4-4-1: When the predicted offline duration Ht is less than the irrigation duration, initialize the temporary irrigation data set before the basic intelligent water valve starts irrigation, and monitor and store the irrigation duration, irrigation volume, and irrigation timestamp after irrigation starts;

[0027] Step S4-4-1-1: When the basic intelligent water valve goes offline during irrigation, read the irrigation duration and irrigation volume in the basic intelligent water valve controller, subtract the irrigation duration and irrigation volume in the temporary irrigation data set as completed data from the basic intelligent water valve controller, and continue to control the basic intelligent water valve for irrigation through the remaining irrigation duration and irrigation volume;

[0028] Step S4-4-1-2: When the basic intelligent water valve does not go offline during irrigation, normally control the basic intelligent water valve for irrigation;

[0029] Step S4-4-2: When the predicted offline duration Ht is greater than or equal to the irrigation duration, update the data in the basic intelligent water valve controller, update the irrigation control data to the basic intelligent water valve controller, and the irrigation control data is expressed as the irrigation duration and irrigation volume, and use the updated data by the basic intelligent water valve controller to control the basic intelligent water valve for irrigation;

[0030] Step S4-5: When the analysis and judgment result based on the log of the basic intelligent water valve and event monitoring is offline, read the irrigation timestamp data cached in the basic intelligent water valve controller. When the cached irrigation timestamp is greater than or equal to the irrigation timestamp threshold G max control the basic intelligent water valve to perform irrigation through the cached irrigation duration and irrigation volume in the basic intelligent water valve controller.

[0031] By setting the irrigation timestamp threshold and combining with real-time monitoring of the flow sensor, the offline situation of the basic intelligent water valve can be effectively detected and processed, thus ensuring the continuity and accuracy of the irrigation task. Even in the offline state, the system can use the temporary irrigation data set and predict the offline duration to flexibly adjust the irrigation duration, volume and timestamp, ensuring that the basic intelligent water valve can independently execute the irrigation task after going offline. This mechanism optimizes irrigation management, improves system stability and autonomy, and reduces the dependence on network connection.

[0032] Furthermore, an intelligent operation management system applied to wireless devices, the intelligent operation management system includes a regional data analysis module, an offline duration prediction module, an irrigation data caching module and an irrigation control module;

[0033] The regional data analysis module is used to divide the irrigation area and analyze the historical offline data of the basic intelligent water valve; the offline duration prediction module is used to store the historical offline data and predict the future offline duration of the basic intelligent water valve; the irrigation data caching module is used to calculate the duration, volume and timestamp of the next irrigation, and cache the data into the water valve controller; the irrigation control module is used to monitor and control the irrigation operation of the basic intelligent water valve, ensuring that even when the device is offline, irrigation can be carried out according to the cached data;

[0034] The output end of the regional data analysis module is electrically connected to the input end of the offline duration prediction module; the output end of the offline duration prediction module is electrically connected to the input end of the irrigation data caching module; the output end of the irrigation data caching module is electrically connected to the input end of the irrigation control module.

[0035] The regional data analysis module includes a regional division unit and an offline data extraction unit; the regional division unit is used to divide the irrigation area into multiple sub-areas, and each sub-area manages a basic intelligent water valve; the offline data extraction unit is used to extract the historical offline data of the basic intelligent water valve;

[0036] The offline duration prediction module includes a data storage unit and an offline duration prediction calculation unit; the data storage unit is used to store the offline timestamp and offline duration data of the basic intelligent water valve; the offline duration prediction calculation unit is used to predict the next offline duration based on the stored data;

[0037] The irrigation data caching module includes an irrigation data calculation unit and a cache storage unit; the irrigation data calculation unit is used to calculate the duration, quantity, and timestamp of the next irrigation according to historical irrigation data in combination with a neural network model; the cache storage unit is used to store the calculated irrigation data in the water valve controller to control the basic intelligent water valve for irrigation in an offline state;

[0038] The irrigation control module includes an offline monitoring unit, a data fusion processing unit, an offline operation control unit, and a temporary data processing unit; the offline monitoring unit is used to monitor the offline state of the water valve in real time and determine whether control needs to be performed through cached data; the data fusion processing unit is used to fuse irrigation control data by combining the irrigation timestamp and the predicted offline duration; the offline operation control unit is used to control whether the water valve executes the irrigation task according to the predicted offline duration; the temporary data processing unit is used to temporarily adjust the irrigation operation by analyzing the cached irrigation data in an offline state.

[0039] Compared with the prior art, the beneficial effects of the present invention are:

[0040] 1. By dividing the irrigation area of the intelligent water valve into multiple sub-areas and analyzing in combination with historical offline data, the present invention can achieve precise monitoring of the device state. This method effectively identifies the offline periods of the device, thereby providing reliable data support for subsequent optimized control strategies, ensuring the coordination and stability between different regions of the irrigation system. By accurately calculating the offline duration, the efficiency of irrigation management is improved, uneven irrigation caused by offline is avoided, and the allocation of water resources is optimized.

[0041] 2. By constructing a water valve offline monitoring set and storing the historical offline data of the device, the present invention provides a precise data basis for predicting the offline duration of the intelligent water valve. Combining historical data with multiple timestamps and using a moving average coefficient and error term adjustment can effectively improve the prediction accuracy and anticipate the offline situation of the device in advance. The implementation of the prediction model can help the system quickly take countermeasures when offline occurs, ensure that the intelligent water valve can maintain normal operation during the next run, and further improve the stability and reliability of the system.

[0042] 3. By combining historical normal irrigation data and a neural network model, the present invention can accurately calculate the duration, quantity, and timestamp of the next irrigation, optimizing the accuracy and efficiency of irrigation scheduling. By storing these data in the water valve control cache set and implementing a cache mechanism in the controller, even in an offline state, the basic intelligent water valve can independently execute irrigation tasks according to preset parameters, avoiding dependence on real-time network connections. It improves the autonomy and stability of the intelligent water valve, reduces the system operation risk, and ensures the continuity of the irrigation process. Description of the Drawings

[0043] Figure 1 It is a schematic flowchart of an intelligent operation management method for a wireless device according to the present invention;

[0044] Figure 2 It is a schematic structural diagram of an intelligent operation management system for a wireless device according to the present invention. Specific embodiments

[0045] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0046] Embodiment 1: As Figure 1 shown, the present invention provides a technical solution, an intelligent operation management method for a wireless device. The intelligent operation management method includes the following steps:

[0047] Step S1: Divide the irrigation area of the intelligent water valve into multiple sub-areas, record the intelligent water valves in the sub-areas as basic intelligent water valves, and analyze and extract the historical offline data of the basic intelligent water valves in the sub-areas. The offline data represents the offline time period during which the basic intelligent water valve fails to be normally connected to the network due to abnormal factor interference, and cannot upload data or receive control instructions through the network at a predetermined period.

[0048] Step S1-1: Divide the irrigation area of the intelligent water valve. According to one intelligent water valve as one sub-area, divide the irrigation area of the intelligent water valve into multiple sub-areas, and record the intelligent water valves in the sub-areas as basic intelligent water valves;

[0049] Step S1-2: Analyze and extract the historical offline data of the basic intelligent water valves in the sub-areas. The offline data represents the offline time period during which the basic intelligent water valve fails to be normally connected to the network due to abnormal factor interference, and cannot upload data or receive control instructions through the network at a predetermined period. Calculate the offline duration according to the timestamp when the basic intelligent water valve starts to go offline and the timestamp when it resumes connection.

[0050] In specific implementation, taking the application of the intelligent water valve in the agricultural irrigation system as an example, first, the irrigation area is divided into multiple sub-areas according to the number and distribution of water valves. Each sub-area contains an intelligent water valve, which is called the basic intelligent water valve. Then, the system analyzes the historical data of the basic intelligent water valve and extracts the offline time period during which the device is disconnected from the network due to abnormal interference. The timestamps at the start and recovery of the offline time period are used to calculate the offline duration. In this way, the system can accurately identify the offline duration of each water valve.

[0051] Step S2: Construct a water valve offline monitoring set, store the historical offline data of the basic intelligent water valve analyzed and extracted, and optimize the data in the water valve offline monitoring set to predict the offline duration of the basic intelligent water valve, denoted as the predicted offline duration;

[0052] Step S2-1: Construct a water valve offline monitoring set and store the historical data of the basic intelligent water valve analyzed and extracted into the water valve offline monitoring set; the water valve offline monitoring set is used to store the timestamps and offline durations of the historical offline of the basic intelligent water valve;

[0053] Step S2-2: Predict the next offline duration of the basic intelligent water valve according to the offline duration in the water valve offline monitoring set, and denote the predicted offline duration as the predicted offline duration. The prediction of the offline duration uses the following formula:

[0054] ;

[0055] In the formula, H t represents the offline duration of the basic intelligent water valve at time t; a represents the baseline value for prediction calculation; Y i represents the influence of the offline duration corresponding to the i-th timestamp in the water valve offline monitoring set on the current predicted offline duration; H t-i represents the observed value of the actual offline duration corresponding to the t-i-th timestamp in the water valve offline monitoring set; n represents the number of timestamps in the water valve offline monitoring set; R j represents the moving average coefficient; F t-j represents the error term at time t-j; m represents the number of error terms in the water valve offline monitoring set; b t represents the current error term at time t.

[0056] For example, the historical offline data of the basic intelligent water valve in sub-region A is known as follows:

[0057] Time t-1: The offline duration is 0.2 hours (H t -1 = 0.2);

[0058] Time t-2: The offline duration is 0.1 hour (Ht -2 = 0.1);

[0059] The baseline value a = 0.1 hour; the moving average coefficient R j = 0.5; the error term F t-1 = 0.05; the error term F t-2 = 0.03; According to the off - line duration prediction calculation formula, it can be obtained that:

[0060] H t = 0.1+(1 * 0.2 + 1 * 0.1)+(0.5 * 0.005 + 0.5 * 0.03)

[0061] = 0.1 + 0.3 + 0.04

[0062] = 0.44 hour;

[0063] According to the calculation, the next off - line duration of the basic intelligent water valve in sub - region A is 0.44 hours, approximately 26 minutes.

[0064] Step S3: Calculate the irrigation duration, irrigation volume, and irrigation timestamp for the next irrigation based on the irrigation duration and irrigation volume of each basic intelligent water valve's historical normal irrigation, and construct a water valve control cache set. Store the calculated irrigation duration, irrigation volume, and irrigation timestamp for the next irrigation into the water valve control cache set, and store the data of the water valve control cache set in the form of cache into each basic intelligent water valve controller;

[0065] Step S3 - 1: Obtain the historical normal irrigation data of each basic intelligent water valve. The historical normal irrigation data represents each irrigation operation record during the normal operation of the basic intelligent water valve in the past period of time, including the irrigation duration, irrigation volume, and irrigation timestamp;

[0066] Step S3 - 2: Based on the obtained historical normal irrigation data of each basic intelligent water valve, calculate the irrigation duration, irrigation volume, and irrigation timestamp for the next irrigation of the basic intelligent water valve in combination with the neural network model;

[0067] Step S3 - 3: Construct a water valve control cache set. Traverse and read the calculated irrigation duration, irrigation volume, and irrigation time for the next irrigation of the basic intelligent water valve, and store them into the water valve control cache set in sequence. Correspondingly, read the data of each basic intelligent water valve in the water valve control cache set and store it into each basic intelligent water valve controller through the cache method. The basic intelligent water valve controller is used to independently control a single basic intelligent water valve, store real - time data using the cache mechanism, and adjust the operation parameters of the switch state of the basic intelligent water valve according to the control instruction. It can independently execute the switch control and flow regulation of the basic intelligent water valve according to the preset parameters in the off - line state.

[0068] In specific implementation, first, obtain the historical irrigation data of the basic intelligent water valve, including the irrigation duration, irrigation volume, and timestamp for each irrigation. These data reflect the performance of the device during normal operation and serve as the basis for subsequent irrigation scheduling. Then, by combining with a neural network model, utilize the patterns and trends in the historical data to predict the duration, volume, and timestamp required for the next irrigation. Next, store these predicted values in the water valve control cache set. The cache set serves as an intermediate storage for saving the control information of each water valve. During this process, each water valve controller can independently read the cache data and perform on / off control and flow regulation according to preset parameters. Even in an offline state, the water valve can still independently execute tasks according to the cached data.

[0069] Step S4: Set an irrigation timestamp threshold to monitor the irrigation of the basic intelligent water valve. When it is monitored that the basic intelligent water valve is offline, construct a temporary irrigation data set, and combine the irrigation timestamp threshold and the water valve control cache set to predict the offline duration and control the basic intelligent water valve for irrigation.

[0070] Step S4-1: Set an irrigation timestamp threshold G max , conduct real-time irrigation monitoring of the basic intelligent water valve through a flow sensor, and monitor the offline situation through the logs and events of the basic intelligent water valve;

[0071] Step S4-2: When the flow sensor monitors that the basic intelligent water valve starts to irrigate, analyze and judge the logs and events of the basic intelligent water valve;

[0072] Step S4-3: When the analysis and judgment result based on the logs and events of the basic intelligent water valve is normal online, construct a temporary irrigation data set, which is used to store the irrigation duration, irrigation volume, and irrigation timestamp of the basic intelligent water valve;

[0073] Step S4-4: Obtain the irrigation duration data in the basic intelligent water valve controller, and combine the predicted offline duration to control the basic intelligent water valve for irrigation:

[0074] Step S4-4-1: When the predicted offline duration Ht is less than the irrigation duration, initialize the temporary irrigation data set before the basic intelligent water valve starts to irrigate, and monitor and store the irrigation duration, irrigation volume, and irrigation timestamp after the irrigation starts;

[0075] Step S4-4-1-1: When the basic intelligent water valve goes offline during irrigation, read the irrigation duration and irrigation volume in the basic intelligent water valve controller, subtract the irrigation duration and irrigation volume in the temporary irrigation data set as the completed data from the basic intelligent water valve controller, and continue to control the basic intelligent water valve for irrigation with the remaining irrigation duration and irrigation volume;

[0076] Step S4-4-1-2: When the basic intelligent water valve does not go offline during irrigation, normally control the basic intelligent water valve for irrigation;

[0077] Step S4-4-2: When the predicted offline duration Ht is greater than or equal to the irrigation duration, update the data in the basic intelligent water valve controller, update the irrigation control data to the basic intelligent water valve controller, and the irrigation control data is represented as the irrigation duration and irrigation volume, and use the updated data to control the basic intelligent water valve for irrigation through the basic intelligent water valve controller;

[0078] Step S4-5: When the analysis and judgment result based on the log and event monitoring of the basic intelligent water valve is offline, read the irrigation timestamp data cached in the basic intelligent water valve controller. When the cached irrigation timestamp is greater than or equal to the irrigation timestamp threshold G max control the basic intelligent water valve for irrigation through the cached irrigation duration and irrigation volume in the basic intelligent water valve controller.

[0079] In specific implementation, when the offline state occurs during irrigation, it is difficult for the conventional intelligent water valve to continue to control irrigation. The designed temporary irrigation data set in this solution can store the irrigation time and irrigation volume that have been completed, obtain the original planned data from the cache, subtract the data, and then control the basic intelligent water valve for irrigation through the basic intelligent water valve controller. If the basic intelligent water valve in the sub-region is offline before irrigation starts, it can be judged by the data in the cache and the set irrigation timestamp threshold, and then control the basic intelligent water valve for irrigation according to the data in the cache through the basic intelligent water valve controller.

[0080] Embodiment 2, as Figure 2 shown, the present invention provides an intelligent operation management system applied to wireless devices. The intelligent operation management system includes a regional data analysis module, an offline duration prediction module, an irrigation data cache module, and an irrigation control module;

[0081] The area data analysis module is used to divide the irrigation area and analyze the historical offline data of the basic intelligent water valves; the offline duration prediction module is used to store the historical offline data and predict the future offline duration of the basic intelligent water valves; the irrigation data caching module is used to calculate the duration, volume, and timestamp of the next irrigation and cache the data in the water valve controller; the irrigation control module is used to monitor and control the irrigation operations of the basic intelligent water valves to ensure that irrigation can be carried out according to the cached data even when the device is offline.

[0082] The output end of the area data analysis module is electrically connected to the input end of the offline duration prediction module; the output end of the offline duration prediction module is electrically connected to the input end of the irrigation data caching module; the output end of the irrigation data caching module is electrically connected to the input end of the irrigation control module.

[0083] The area data analysis module includes an area division unit and an offline data extraction unit; the area division unit is used to divide the irrigation area into multiple sub-areas, and each sub-area manages a basic intelligent water valve; the offline data extraction unit is used to extract the historical offline data of the basic intelligent water valves.

[0084] The offline duration prediction module includes a data storage unit and an offline duration prediction calculation unit; the data storage unit is used to store the offline timestamps and offline duration data of the basic intelligent water valves; the offline duration prediction calculation unit is used to predict the next offline duration based on the stored data.

[0085] The irrigation data caching module includes an irrigation data calculation unit and a cache storage unit; the irrigation data calculation unit is used to calculate the duration, volume, and timestamp of the next irrigation according to the historical irrigation data in combination with the neural network model; the cache storage unit is used to store the calculated irrigation data in the water valve controller to control the basic intelligent water valves for irrigation in the offline state.

[0086] The irrigation control module includes an offline monitoring unit, a data fusion processing unit, an offline operation control unit, and a temporary data processing unit; the offline monitoring unit is used to monitor the offline state of the water valves in real time and judge whether control is needed through the cached data; the data fusion processing unit is used to fuse the irrigation control data by combining the irrigation timestamp and the predicted offline duration; the offline operation control unit is used to control whether the water valves execute the irrigation task according to the predicted offline duration; the temporary data processing unit is used to temporarily adjust the irrigation operations by analyzing the cached irrigation data in the offline state.

[0087] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above-described exemplary embodiments, and the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-restrictive. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be embraced within the present invention. Any reference signs in the claims should not be construed as limiting the claims involved.

Claims

1. An intelligent operation management method for wireless devices, characterized by: The intelligent operation management method comprises the following steps: Step S1: Divide the irrigation area of the smart water valve into multiple sub-areas, record the smart water valves in the sub-areas as basic smart water valves, and analyze and extract historical offline data of the basic smart water valves in the sub-areas, wherein the offline data represents the offline time period when the basic smart water valve fails to connect to the network normally due to abnormal interference, and cannot upload data or receive control instructions through the network according to a predetermined period; Step S2: Construct a water valve offline monitoring set, store the historical offline data of the basic intelligent water valve extracted from the analysis, optimize the data of the water valve offline monitoring set, and predict the offline duration of the basic intelligent water valve, which is recorded as the predicted offline duration; Step S3: Calculate the irrigation duration, irrigation amount, and irrigation timestamp of the next irrigation based on the historical normal irrigation duration and irrigation amount of each basic intelligent water valve, and construct a water valve control cache set. Store the calculated irrigation duration, irrigation amount, and irrigation timestamp of the next irrigation in the water valve control cache set, and store the data of the water valve control cache set in a cached manner in each basic intelligent water valve controller. Step S4: Set the irrigation timestamp threshold and monitor the basic smart water valve for irrigation. When the irrigation monitoring finds that the basic smart water valve is offline, construct a temporary irrigation data set. Use the irrigation timestamp threshold and the water valve control cache set combined with the predicted offline duration to control the basic smart water valve for irrigation.

2. The intelligent operation management method for wireless devices according to claim 1, characterized in that: The specific steps of step S1 are as follows: Step S1-1, dividing the irrigation area of the smart water valve into multiple sub-areas, with one smart water valve as one sub-area, and recording the smart water valves in the sub-areas as basic smart water valves; Step S1-2: Analyze and extract the historical offline data of the basic intelligent water valves in the sub-area. The offline data indicates that the basic intelligent water valves are unable to connect to the network normally due to abnormal interference, and cannot upload data or receive control instructions through the network according to the predetermined period. The offline duration is calculated based on the timestamp of the basic intelligent water valve starting to go offline and the timestamp of restoring the connection.

3. The intelligent operation management method for wireless devices according to claim 2, characterized in that: The specific steps of step S2 are as follows: Step S2-1: Construct a water valve offline monitoring set, and store the basic intelligent water valve historical data extracted from the analysis into the water valve offline monitoring set; the water valve offline monitoring set is used to store the timestamp and offline duration of the basic intelligent water valve history; Step S2-2: predict the next offline duration of the basic intelligent water valve according to the offline duration in the water valve offline monitoring set, and record the predicted offline duration as the predicted offline duration. The offline duration is predicted using the following formula: ； Where H t It represents the offline duration of the basic smart water valve at time t; a represents the baseline value of the prediction calculation; Y i It is represented by the impact of the offline duration corresponding to the i-th timestamp on the current predicted offline duration in the water valve offline monitoring set; H t-i It is represented by the actual offline duration observation value corresponding to the ti-th timestamp in the water valve offline monitoring set; n is represented by the number of timestamps in the water valve offline monitoring set; R j Expressed as a sliding average coefficient; F t-j is the error term at timestamp tj; m is the number of error terms in the water valve offline monitoring set; b t is represented as the current error term at timestamp t.

4. The intelligent operation management method for wireless devices according to claim 3, characterized in that: The specific steps of step S3 are as follows: Step S3-1: Acquire historical normal irrigation data of each basic smart water valve, wherein the historical normal irrigation data represents each irrigation operation record of the basic smart water valve during normal operation over a period of time in the past, including irrigation duration, irrigation amount, and irrigation timestamp; Step S3-2: Calculate the irrigation duration, irrigation volume, and irrigation timestamp of the next irrigation of the basic intelligent water valve based on the acquired historical normal irrigation data of the basic intelligent water valve and in combination with the neural network model; Step S3-3, construct a water valve control cache set, traverse and read the calculated irrigation duration, irrigation amount and irrigation time of the next irrigation of the basic intelligent water valve, and store them in the water valve control cache set in sequence, and read the data of each basic intelligent water valve in the water valve control cache set accordingly, and store them in each basic intelligent water valve controller through caching. The basic intelligent water valve controller is used to independently control a single basic intelligent water valve, use a cache mechanism to store real-time data, and adjust the switch state operating parameters of the basic intelligent water valve according to the control instructions. It can independently execute the switch control and flow adjustment of the basic intelligent water valve according to preset parameters in an offline state.

5. The intelligent operation management method for wireless devices according to claim 4, characterized in that: The specific steps of step S4 are as follows: Step S4-1, setting the irrigation timestamp threshold G max , through the flow sensor to monitor the irrigation of the basic smart water valve in real time, and through the log and event monitoring of the basic smart water valve to monitor the offline situation; Step S4-2: When the flow sensor detects that the basic intelligent water valve starts irrigation, the log and event monitoring of the basic intelligent water valve are analyzed and judged.

6. The intelligent operation management method for wireless devices according to claim 5, characterized in that: In step S4, it also includes: Step S4-3: When the analysis result of the basic smart water valve log and event monitoring shows that the basic smart water valve is online, a temporary irrigation data set is constructed, wherein the temporary irrigation data set is used to store the irrigation duration, irrigation amount, and irrigation timestamp of the basic smart water valve; Step S4-4: Obtain irrigation duration data from the basic intelligent water valve controller, and control the basic intelligent water valve to perform irrigation based on the predicted offline duration: Step S4-4-1: When the offline duration H is predicted t When the irrigation time is less than the irrigation time, the temporary irrigation data set is initialized before the basic intelligent water valve irrigation starts. After the irrigation starts, the irrigation time, irrigation amount and irrigation timestamp are monitored and stored. Step S4-4-1-1: When the basic intelligent water valve goes offline during irrigation, read the irrigation duration and irrigation amount in the basic intelligent water valve controller, subtract the irrigation duration and irrigation amount in the temporary irrigation data set from the basic intelligent water valve controller as completed data, and continue to control the basic intelligent water valve to irrigate based on the remaining irrigation duration and irrigation amount; Step S4-4-1-2: When the basic intelligent water valve is not offline during irrigation, the basic intelligent water valve is normally controlled to perform irrigation; Step S4-4-2: When the offline duration H is predicted t When it is greater than or equal to the irrigation duration, the data in the basic intelligent water valve controller is updated, and the irrigation control data is updated to the basic intelligent water valve controller. The irrigation control data is represented by the irrigation duration and irrigation amount. The basic intelligent water valve controller uses the updated data to control the basic intelligent water valve for irrigation.

7. The intelligent operation management method for wireless devices according to claim 6, characterized in that: In step S4, it also includes: Step S4-5: When the result of the analysis and judgment of the log and event monitoring of the basic intelligent water valve is offline, read the irrigation timestamp data cached in the basic intelligent water valve controller, and when the cached irrigation timestamp is greater than or equal to the irrigation timestamp threshold G max When irrigation is in progress, the basic intelligent water valve is controlled by the irrigation duration and irrigation amount cached in the basic intelligent water valve controller to perform irrigation.

8. An intelligent operation management system for wireless devices, which is applied to the intelligent operation management method for wireless devices according to any one of claims 1 to 7, characterized in that: The intelligent operation management system includes a regional data analysis module, an offline time prediction module, an irrigation data cache module and an irrigation control module; The regional data analysis module is used to divide the irrigation area and analyze the historical offline data of the basic intelligent water valve; the offline duration prediction module is used to store historical offline data and predict the future offline duration of the basic intelligent water valve; the irrigation data cache module is used to calculate the duration, amount and timestamp of the next irrigation and cache the data in the water valve controller; The irrigation control module is used to monitor and control the irrigation operation of the basic intelligent water valve, ensuring that irrigation can be carried out according to the cached data even if the device is offline; The output end of the regional data analysis module is electrically connected to the input end of the offline time prediction module; the output end of the offline time prediction module is electrically connected to the input end of the irrigation data cache module; the output end of the irrigation data cache module is electrically connected to the input end of the irrigation control module.

9. The intelligent operation management system for wireless devices according to claim 8, characterized in that: The regional data analysis module includes a regional division unit and an offline data extraction unit; the regional division unit is used to divide the irrigation area into multiple sub-areas, each sub-area manages a basic smart water valve; the offline data extraction unit is used to extract historical offline data of the basic smart water valve; The offline duration prediction module includes a data storage unit and an offline duration prediction calculation unit; the data storage unit is used to store the offline timestamp and offline duration data of the basic intelligent water valve; the offline duration prediction calculation unit is used to predict the next offline duration based on the stored data.

10. The intelligent operation management system for wireless devices according to claim 8, characterized in that: The irrigation data cache module includes an irrigation data calculation unit and a cache storage unit; the irrigation data calculation unit is used to calculate the duration, amount and timestamp of the next irrigation based on historical irrigation data in combination with a neural network model; the cache storage unit is used to store the calculated irrigation data in the water valve controller, and control the basic intelligent water valve to perform irrigation in an offline state; The irrigation control module includes an offline monitoring unit, a data fusion processing unit, an offline operation control unit and a temporary data processing unit; The offline monitoring unit is used to monitor the offline status of the water valve in real time and determine whether control is required through cached data; the data fusion processing unit is used to combine the irrigation timestamp and the predicted offline duration to fuse the irrigation control data; the offline operation control unit is used to control whether the water valve performs the irrigation task based on the predicted offline duration; the temporary data processing unit is used to temporarily adjust the irrigation operation by analyzing the cached irrigation data in the offline state.

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