Intelligent operation management system and method applied to wireless equipment

Abstract

The invention discloses an intelligent operation management system and method applied to wireless equipment, and relates to the technical field of artificial intelligence. An irrigation area of an intelligent water valve is divided into a plurality of sub-areas, analysis is carried out in combination with historical offline data, the equipment state is accurately monitored, and the offline duration is predicted; the stability of the irrigation system in different areas is ensured, uneven irrigation caused by off-line local equipment is avoided, and the operation efficiency is improved. A water valve off-line monitoring set is constructed, a prediction model is utilized, the accuracy of off-line duration prediction is improved, and normal work of equipment is ensured; according to the method, historical irrigation data and a neural network model are combined, the duration, quantity and timestamp of next-time irrigation are accurately calculated, a cache mechanism is controlled through a water valve, even if equipment is offline, an irrigation task can be independently executed, stability and autonomy of a system are ensured, dependence on network connection is reduced, and continuity and reliability of the irrigation process are ensured.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence technology, and in particular to an intelligent operation management system and method applied to wireless equipment. Background Art

[0002] Wireless devices play a vital role in modern society and are widely used in communications, medical treatment, transportation, smart homes and other fields. They transmit data through wireless signals, breaking the limitations of traditional wired devices and improving flexibility and ease of operation. Among them, smart water valves use wireless technology to achieve automatic regulation and remote monitoring of water flow, optimizing water management. Wireless device technology not only enhances the interconnection between devices, but also promotes the digital transformation of industry, commerce and daily life.

[0003] Smart Water Valve In today's smart irrigation systems, offline problems often occur due to abnormal factors that prevent irrigation in local areas from operating normally. When this offline situation occurs during the irrigation process, it will cause incomplete irrigation in a specific area or be out of sync with other areas, thus affecting the water resource allocation efficiency of the entire irrigation system. Due to uneven water distribution, some areas may have too much or too little 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 for wireless devices to solve the problems raised in the prior art.

[0005] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: an intelligent operation management method for wireless devices, and a supply chain platform data management method comprising the following steps: Step S1, dividing the irrigation area of ​​the smart water valve into multiple sub-areas, recording the smart water valves in the sub-areas as basic smart water valves, analyzing and extracting the historical offline data of the basic smart water valves in the sub-areas, wherein the offline data represents the offline time period during which the basic smart water valves fail to connect to the network normally due to abnormal interference, and fail to upload data or receive control instructions through the network according to a predetermined period; Step S1-1, dividing the irrigation area of ​​the smart water valve into multiple sub-areas according to one smart water valve being 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, wherein the offline data indicates that the basic intelligent water valve is unable 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. The offline time period is calculated based on the timestamp of the basic intelligent water valve starting to go offline and the timestamp of restoring the connection.

[0006] By dividing the irrigation area of ​​the smart water valve into multiple sub-areas, it is helpful to achieve more refined management and control. By analyzing the historical offline data of the basic smart water valve, it is possible to identify the offline time period of the equipment and ensure accurate grasp of the system operation status. Based on the calculation of the offline time, the offline prediction and control strategy can be optimized to improve the stability and efficiency of the system.

[0007] Step S2: construct a water valve offline monitoring set, analyze and extract the historical offline data of the basic intelligent water valve and store it, 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 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 offline; 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: ; In the formula, H t 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 expressed as the impact of the offline duration of the basic smart water valve at the past i timestamps on the predicted offline duration; H t-i It is represented by the actual observed value in the historical data of the basic intelligent water valve; n represents the impact of the data of n historical timestamps on the current predicted value; R j Expressed as a sliding average coefficient; F t-j denoted as the error term at timestamp tj; m denotes the impact of the past m error terms on the predicted offline duration; b t Represented as the current error term at timestamp t.

[0008] By building a water valve offline monitoring set and storing historical offline data, it is helpful to track the offline mode and frequency of the equipment and provide basic data support for system optimization. By optimizing the historical offline data, the future offline duration of the basic intelligent water valve can be accurately predicted, thereby preventing potential system problems in advance. The prediction model combines historical data with multiple timestamps to help improve the accuracy of the prediction, provide real-time data basis for water valve control, and enhance the reliability and stability of the system.

[0009] Step S3, calculating the irrigation duration, irrigation amount and irrigation timestamp of the next irrigation according to the irrigation duration and irrigation amount of each historical normal irrigation of the basic intelligent water valve, and constructing a water valve control cache set, storing the calculated irrigation duration, irrigation amount and irrigation timestamp of the next irrigation in the water valve control cache set, and storing the data of the water valve control cache set in each basic intelligent water valve controller in a cached manner; Step S3-1, obtaining historical normal irrigation data of each basic intelligent water valve, wherein the historical normal irrigation data is represented by each irrigation operation record of the basic intelligent water valve during normal operation in the past period of time, including irrigation duration, irrigation amount and irrigation timestamp; Step S3-2, based on the acquired historical normal irrigation data of each basic intelligent water valve, the irrigation duration, irrigation amount and irrigation timestamp of the next irrigation of the basic intelligent water valve are calculated 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 by caching. The basic intelligent water valve controller is used to independently control the equipment of a single basic intelligent water valve, and uses a cache mechanism to store real-time data. It adjusts the switch state operating parameters of the basic intelligent water valve according to the control instructions, and can independently perform the switch control and flow regulation of the basic intelligent water valve according to preset parameters in an offline state.

[0010] By combining historical irrigation data with the neural network model, the duration, amount, and timestamp of the next irrigation can be accurately calculated, improving the accuracy and efficiency of irrigation scheduling. A valve control cache collection is built and the data is stored in the controller to ensure that each basic intelligent valve can operate independently and perform irrigation tasks according to preset parameters even when offline. This approach not only optimizes valve management, but also enhances the autonomy and stability of the system and reduces the risks of relying on network connections.

[0011] Step S4, set the irrigation timestamp threshold, and monitor the basic intelligent water valve for irrigation. When the irrigation monitoring finds that the basic intelligent water valve is offline, build a temporary irrigation data set, and control the basic intelligent water valve for irrigation through the irrigation timestamp threshold and the water valve control cache set combined with the predicted offline duration.

[0012] Step S4-1, setting the irrigation timestamp threshold G max , use flow sensors to monitor irrigation in real time on basic smart water valves, and use log and event monitoring of basic smart water valves to monitor offline conditions; 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; Step S4-3: when the analysis result of the log and event monitoring of the basic intelligent water valve is normal 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 intelligent water valve; Step S4-4, obtain the irrigation duration data in the basic intelligent water valve controller, and control the basic intelligent water valve for irrigation in combination with the predicted offline duration: Step S4-4-1, when the predicted offline time Ht is less than the irrigation time, the temporary irrigation data set is initialized before the basic intelligent water valve irrigation starts, and the irrigation time, irrigation amount and irrigation timestamp are monitored and stored after the irrigation starts; Step S4-4-1-1, when the basic intelligent water valve is 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 for irrigation through 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 predicted offline time Ht is greater than or equal to the irrigation time, 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, wherein the irrigation control data is expressed as the irrigation time and the irrigation amount, and the basic intelligent water valve controller uses the updated data to control the basic intelligent water valve for irrigation; Step S4-5: When the result of the analysis and judgment 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, 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 for irrigation through the irrigation duration and irrigation amount cached in the basic intelligent water valve controller.

[0013] By setting the irrigation timestamp threshold and combining it with real-time monitoring of the flow sensor, the offline situation of the basic smart water valve can be effectively detected and handled, thereby ensuring the continuity and accuracy of the irrigation task. Even in the offline state, the system can use the temporary irrigation data set and the predicted offline time to flexibly adjust the irrigation time, amount and timestamp to ensure that the basic smart water valve can independently perform the irrigation task after going offline. This mechanism optimizes irrigation management, improves system stability and autonomy, and reduces dependence on network connections.

[0014] Further, an intelligent operation management system applied to wireless devices, 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 the 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 to ensure that irrigation can be performed 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.

[0015] 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 intelligent water valve; the offline data extraction unit is used to extract the historical offline data of the basic intelligent 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; 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 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, and control the basic intelligent water valve to irrigate 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 it is necessary to control it 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 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 the offline state.

[0016] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention can realize accurate monitoring of the equipment status by dividing the irrigation area of ​​the intelligent water valve into multiple sub-areas and analyzing the historical offline data. This method effectively identifies the offline period of the equipment, thereby providing reliable data support for the subsequent optimization control strategy and ensuring the coordination and stability of the irrigation system in different areas. By accurately calculating the offline time, the efficiency of irrigation management is improved, uneven irrigation caused by offline is avoided, and the allocation of water resources is optimized.

[0017] 2. The present invention provides an accurate data basis for predicting the offline duration of intelligent water valves by constructing a water valve offline monitoring set and storing the historical offline data of the equipment. Combining historical data with multiple timestamps, using the sliding average coefficient and error term adjustment, the prediction accuracy can be effectively improved, and the offline status of the equipment can be predicted in advance. The implementation of the prediction model can help the system to quickly take countermeasures when offline occurs, ensuring that the intelligent water valve can maintain normal operation when it runs next time, and further improving the stability and reliability of the system.

[0018] 3. By combining historical normal irrigation data and neural network models, the present invention can accurately calculate the duration, amount and timestamp of the next irrigation, thereby 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 still independently perform irrigation tasks according to preset parameters, avoiding dependence on real-time network connections. This improves the autonomy and stability of the intelligent water valve, reduces system operation risks, and ensures the continuity of the irrigation process. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 A schematic diagram of a flow chart of an intelligent operation management method applied to a wireless device according to the present invention; Figure 2 The present invention is a structural schematic diagram of an intelligent operation management system applied to wireless devices. DETAILED DESCRIPTION

[0020] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] Embodiment 1: Figure 1 As shown, the present invention provides a technical solution, an intelligent operation management method applied to a wireless device, and the intelligent operation management method comprises the following steps: Step S1, dividing the irrigation area of ​​the smart water valve into multiple sub-areas, recording the smart water valves in the sub-areas as basic smart water valves, analyzing and extracting the historical offline data of the basic smart water valves in the sub-areas, wherein the offline data represents the offline time period during which the basic smart water valves fail to connect to the network normally due to abnormal interference, and fail to upload data or receive control instructions through the network according to a predetermined period; Step S1-1, dividing the irrigation area of ​​the smart water valve into multiple sub-areas according to one smart water valve being 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, wherein the offline data indicates that the basic intelligent water valve is unable 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. The offline time period is calculated based on the timestamp of the basic intelligent water valve starting to go offline and the timestamp of restoring the connection.

[0022] In the specific implementation, taking the application of smart water valves in agricultural irrigation systems as an example, the irrigation area is first divided into multiple sub-areas according to the number and distribution of water valves. Each sub-area contains a smart water valve, called a basic smart water valve. Then, by analyzing the historical data of the basic smart water valve, the system extracts the offline time period when the device is disconnected from the network due to abnormal interference. The timestamps of the start of the offline time period and the restoration of the connection are used to calculate the offline duration. In this way, the system can accurately identify the offline duration of each water valve.

[0023] Step S2: construct a water valve offline monitoring set, analyze and extract the historical offline data of the basic intelligent water valve and store it, 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 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 offline; 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: ; In the formula, H t 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 expressed as the impact of the offline duration of the basic smart water valve at the past i timestamps on the predicted offline duration; H t-i It is represented by the actual observed value in the historical data of the basic intelligent water valve; n represents the impact of the data of n historical timestamps on the current predicted value; R j Expressed as a sliding average coefficient; F t-j denoted as the error term at timestamp tj; m denotes the impact of the past m error terms on the predicted offline duration; b t Represented as the current error term at timestamp t.

[0024] For example, the historical offline data of the basic smart water valve in sub-area A is as follows: Time t-1: Offline time is 0.2 hours (H t -1=0.2); Time t-2: Offline time is 0.1 hours (H t -2=0.1); Baseline value a=0.1 hour; sliding average coefficient R j =0.5; error term F t-1 =0.05; error term F t-2 =0.03; According to the offline time prediction calculation formula, we can get: H t =0.1+(1*0.2+1*0.1)+(0.5*0.005+0.5*0.03) =0.1+0.3+0.04 = 0.44 hours; According to calculation, the next offline duration of the basic intelligent water valve in sub-area A is 0.44 hours, about 26 minutes.

[0025] Step S3, calculating the irrigation duration, irrigation amount and irrigation timestamp of the next irrigation according to the irrigation duration and irrigation amount of each historical normal irrigation of the basic intelligent water valve, and constructing a water valve control cache set, storing the calculated irrigation duration, irrigation amount and irrigation timestamp of the next irrigation in the water valve control cache set, and storing the data of the water valve control cache set in each basic intelligent water valve controller in a cached manner; Step S3-1, obtaining historical normal irrigation data of each basic intelligent water valve, wherein the historical normal irrigation data is represented by each irrigation operation record of the basic intelligent water valve during normal operation in the past period of time, including irrigation duration, irrigation amount and irrigation timestamp; Step S3-2, based on the acquired historical normal irrigation data of each basic intelligent water valve, the irrigation duration, irrigation amount and irrigation timestamp of the next irrigation of the basic intelligent water valve are calculated 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 by caching. The basic intelligent water valve controller is used to independently control the equipment of a single basic intelligent water valve, and uses a cache mechanism to store real-time data. It adjusts the switch state operating parameters of the basic intelligent water valve according to the control instructions, and can independently perform the switch control and flow regulation of the basic intelligent water valve according to preset parameters in an offline state.

[0026] In the specific implementation, the historical irrigation data of the basic intelligent water valve is first obtained, including the irrigation duration, irrigation amount and timestamp of each irrigation. These data reflect the performance of the equipment in normal operation and serve as the basis for subsequent irrigation scheduling. Then, by combining the neural network model, the patterns and trends in the historical data are used to predict the duration, irrigation amount and timestamp required for the next irrigation. Then, these predicted values ​​are stored in the water valve control cache set, which is used as an intermediate storage to save the control information of each water valve. In this process, each water valve controller can independently read the cache data and perform switch control and flow regulation according to the preset parameters. Even in the offline state, the water valve can still perform tasks independently according to the cached data. Step S4, set the irrigation timestamp threshold, and monitor the basic intelligent water valve for irrigation. When the irrigation monitoring finds that the basic intelligent water valve is offline, build a temporary irrigation data set, and control the basic intelligent water valve for irrigation through the irrigation timestamp threshold and the water valve control cache set combined with the predicted offline duration.

[0027] Step S4-1, setting the irrigation timestamp threshold G max, use flow sensors to monitor irrigation in real time on basic smart water valves, and use log and event monitoring of basic smart water valves to monitor offline conditions; 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; Step S4-3: when the analysis result of the log and event monitoring of the basic intelligent water valve is normal 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 intelligent water valve; Step S4-4, obtain the irrigation duration data in the basic intelligent water valve controller, and control the basic intelligent water valve for irrigation in combination with the predicted offline duration: Step S4-4-1, when the predicted offline time Ht is less than the irrigation time, the temporary irrigation data set is initialized before the basic intelligent water valve irrigation starts, and the irrigation time, irrigation amount and irrigation timestamp are monitored and stored after the irrigation starts; Step S4-4-1-1, when the basic intelligent water valve is 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 for irrigation through 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 predicted offline time Ht is greater than or equal to the irrigation time, 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, wherein the irrigation control data is expressed as the irrigation time and the irrigation amount, and the basic intelligent water valve controller uses the updated data to control the basic intelligent water valve for irrigation; Step S4-5: When the result of the analysis and judgment 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, 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 for irrigation through the irrigation duration and irrigation amount cached in the basic intelligent water valve controller.

[0028] In the specific implementation, an offline state occurs during the irrigation process, and conventional smart water valves are difficult to continue to control irrigation. The temporary irrigation data set designed in this solution can store the time and amount of irrigation that has been completed, obtain the original planned data from the cache, and after subtracting the data, control the basic smart water valve for irrigation through the basic smart water valve controller. If the basic smart water valve in the sub-area is offline before irrigation starts, it can be judged by the data in the cache and the set irrigation timestamp threshold, so that the basic smart water valve can be controlled for irrigation through the basic smart water valve controller according to the data in the cache.

[0029] Embodiment 2, as Figure 2 As 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 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 the 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 to ensure that irrigation can be performed 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 duration prediction module; the output end of the offline duration 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; 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 intelligent water valve; the offline data extraction unit is used to extract the historical offline data of the basic intelligent 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; 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 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, and control the basic intelligent water valve to irrigate 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 it is necessary to control it 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 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 the offline state.

[0030] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. An intelligent operation management method applied to wireless devices, characterized in that: The intelligent operation management method comprises the following steps: Step S1, dividing the irrigation area of ​​the smart water valve into multiple sub-areas, recording the smart water valves in the sub-areas as basic smart water valves, analyzing and extracting the historical offline data of the basic smart water valves in the sub-areas, wherein the offline data represents the offline time period during which the basic smart water valves fail to connect to the network normally due to abnormal interference, and fail to upload data or receive control instructions through the network according to a predetermined period; Step S2: construct a water valve offline monitoring set, analyze and extract the historical offline data of the basic intelligent water valve and store it, 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, calculating the irrigation duration, irrigation amount and irrigation timestamp of the next irrigation according to the irrigation duration and irrigation amount of each historical normal irrigation of the basic intelligent water valve, and constructing a water valve control cache set, storing the calculated irrigation duration, irrigation amount and irrigation timestamp of the next irrigation in the water valve control cache set, and storing the data of the water valve control cache set in each basic intelligent water valve controller in a cached manner; Step S4, set the irrigation timestamp threshold, and monitor the basic intelligent water valve for irrigation. When the irrigation monitoring finds that the basic intelligent water valve is offline, build a temporary irrigation data set, and control the basic intelligent water valve for irrigation through the irrigation timestamp threshold and the water valve control cache set combined with the predicted offline duration.

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 according to one smart water valve being 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, wherein the offline data indicates that the basic intelligent water valve is unable 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. The offline time period 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 offline; 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: ； In the formula, H t 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 expressed as the impact of the offline duration of the basic smart water valve at the past i timestamps on the predicted offline duration; H t-i It is represented by the actual observed value in the historical data of the basic intelligent water valve; n represents the impact of the data of n historical timestamps on the current predicted value; R j Expressed as a sliding average coefficient; F t-j denoted as the error term at timestamp tj; m denotes the impact of the past m error terms on the predicted offline duration; b t 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, obtaining historical normal irrigation data of each basic intelligent water valve, wherein the historical normal irrigation data is represented by each irrigation operation record of the basic intelligent water valve during normal operation in the past period of time, including irrigation duration, irrigation amount and irrigation timestamp; Step S3-2, based on the acquired historical normal irrigation data of each basic intelligent water valve, the irrigation duration, irrigation amount and irrigation timestamp of the next irrigation of the basic intelligent water valve are calculated 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 by caching. The basic intelligent water valve controller is used to independently control the equipment of a single basic intelligent water valve, and uses a cache mechanism to store real-time data. It adjusts the switch state operating parameters of the basic intelligent water valve according to the control instructions, and can independently perform the switch control and flow regulation 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 , use flow sensors to monitor irrigation in real time on basic smart water valves, and use log and event monitoring of basic smart water valves to monitor offline conditions; 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 log and event monitoring of the basic intelligent water valve is normal 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 intelligent water valve; Step S4-4, obtain the irrigation duration data in the basic intelligent water valve controller, and control the basic intelligent water valve for irrigation in combination with the predicted offline duration: Step S4-4-1, when the predicted offline time Ht is less than the irrigation time, the temporary irrigation data set is initialized before the basic intelligent water valve irrigation starts, and the irrigation time, irrigation amount and irrigation timestamp are monitored and stored after the irrigation starts; Step S4-4-1-1, when the basic intelligent water valve is 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 for irrigation through 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 predicted offline time Ht is greater than or equal to the irrigation time, 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 time and the 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 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, 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 for irrigation through the irrigation duration and irrigation amount cached in the basic intelligent water valve controller.

8. An intelligent operation management system for wireless devices, which is applied to an 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 the 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 performed 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 intelligent water valve; the offline data extraction unit is used to extract the historical offline data of the basic intelligent 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 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, and control the basic intelligent water valve to irrigate 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 it needs to be controlled 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 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 the offline state.

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