Electricity charge recovery monitoring method and device, storage medium and computer equipment

Abstract

The invention provides an electric charge recovery monitoring method and device, a storage medium and computer equipment, and the method comprises the steps: carrying out the statistics of the debt period and the debt total amount of each debt user through the electric charge debt data, and determining a fee payment strategy of each debt user according to the debt period and the debt total amount of each debt user, and then, by taking the meter reading teams and the meter readers as statistical dimensions, according to the total debt amount and the debt strategy of each debt user, determining debt tracking data and debt strategy distribution of each meter reading team and the debt user corresponding to each meter reader, and further generating a team billboard report and a personal billboard report of each meter reader. By generating the team billboard report and the personal billboard report of each meter reader, the electric charge recovery condition of each meter reading team and each meter reader is summarized, so that the meter readers can directly obtain the analyzed and summarized reports to assist the meter readers in better carrying out electric charge recovery work, and the electric charge recovery efficiency is further improved.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to an electricity fee recovery monitoring method, device, storage medium and computer equipment. Background Art

[0002] Electricity fee recovery refers to the process in which power companies charge users the corresponding electricity fees according to the agreed electricity price and settlement period based on the actual electricity consumption of users, and recover the electricity fees in a timely manner. Its goal is to ensure that power companies can recover the electricity fees that should be collected on time and ensure the normal operation and development of the company. However, due to the large amount of electricity fee recovery and the difficulty in managing the recovery rate, centralized collection of electricity fees is carried out at the end of each year.

[0003] However, in the process of monitoring and managing electricity bill recovery, since each meter reading team needs to first summarize the data of each meter reader, and then summarize the data of each meter reading team to determine the situation of electricity bill recovery, this process requires a lot of manpower maintenance costs and communication costs, which leads to low efficiency of electricity bill recovery. Summary of the invention

[0004] The purpose of this application is to solve at least one of the above-mentioned technical defects, especially in the prior art, in the process of monitoring and managing the recovery of electricity bills, since each meter reading team needs to first summarize the data of each meter reader, and then summarize the data of each meter reading team to determine the recovery of electricity bills, this process requires a lot of manpower maintenance costs and communication costs, which leads to the technical defect of low efficiency of electricity bill recovery.

[0005] In a first aspect, the present application provides a method for monitoring electricity fee recovery, the method comprising:

[0006] Determine the electricity bill arrears data, and based on the electricity bill arrears data, count the number of arrears periods and the total amount of arrears for each user in the electricity bill arrears data;

[0007] Determine the collection strategy for each user in arrears based on the number of arrears and the total amount of arrears for each user in arrears;

[0008] The meter reading team corresponding to each user in arrears is used as the statistical dimension. According to the total amount of arrears and the collection strategy of each user in arrears, the arrears tracking data and collection strategy distribution of the users in each meter reading team are determined to generate a team dashboard report.

[0009] The meter readers corresponding to each user in arrears are used as statistical dimensions. According to the total amount of arrears and collection strategies of each user in arrears, the arrears tracking data and collection strategy distribution of each meter reader in arrears are determined to generate a personal dashboard report for each meter reader.

[0010] The personal dashboard report of each meter reader and the team dashboard report are sent to the corresponding meter readers respectively.

[0011] In one embodiment, determining the collection strategy corresponding to each defaulting user based on the number of defaulting periods and the total amount of defaulting of each defaulting user includes:

[0012] For each user in arrears in the electricity bill arrears data, determining whether the number of arrears periods of the user in arrears is less than a first preset threshold, and if the number of arrears periods of the user in arrears is not less than the first preset threshold, determining that the collection strategy for the user in arrears is a power outage strategy;

[0013] If the number of overdue payments of the user in arrears is less than the first preset threshold, determining whether the number of overdue payments of the user in arrears is greater than the second preset threshold;

[0014] If the number of arrears of the user in arrears is greater than the second preset threshold, it is determined whether the total amount of arrears of the user in arrears exceeds the third preset threshold; if so, the collection strategy for the user in arrears is determined to be a power outage strategy; if not, the collection strategy for the user in arrears is determined to be an observation strategy;

[0015] If the number of overdue payment periods of the defaulting user is not greater than the second preset threshold, it is determined whether the total amount of overdue payment of the defaulting user exceeds the third preset threshold. If it exceeds, the collection strategy for the defaulting user is determined to be a collection reminder strategy; if it does not exceed, the collection strategy for the defaulting user is determined to be an observation strategy.

[0016] In one embodiment, the meter reading team corresponding to each user in arrears is used as a statistical dimension, and according to the total amount of arrears and the collection strategy of each user in arrears, the arrears tracking data and collection strategy distribution of the users in arrears in each meter reading team are determined to generate a team dashboard report, including:

[0017] According to the meter reading team of each user in arrears, each user in arrears is divided to obtain a set of users in arrears in each meter reading team;

[0018] For each meter reading team, read the total amount of arrears and the collection strategy of each arrears user in the set of arrears users corresponding to the meter reading team;

[0019] Determine the strategy distribution and tracking data of the meter reading team according to the total amount of arrears and the collection strategy of each arrears user in the set of arrears users corresponding to the meter reading team;

[0020] After determining the strategy distribution and tracking data of each meter reading team, generating the corresponding fee collection strategy distribution of each meter reading team according to the strategy distribution of each meter reading team, and generating the corresponding arrears tracking data of each meter reading team according to the tracking data of each meter reading team;

[0021] The collection strategy distribution and arrears tracking data of each meter reading team are visualized in a report to obtain a team dashboard report.

[0022] In one embodiment, the determining of the strategy distribution and tracking data of the meter reading team according to the total amount of arrears and the collection strategy of each arrears user in the set of arrears users corresponding to the meter reading team includes:

[0023] Count the number of users in arrears with different collection strategies in the set of users in arrears corresponding to the meter reading team, so as to generate a strategy distribution corresponding to the meter reading team;

[0024] Calculate the first change range of the sum of the total amount of arrears of each user in the set of arrears users corresponding to the meter reading team compared to the previous payment period, and calculate the second change range of the number of arrears users in the set of arrears users corresponding to the meter reading team compared to the previous payment period;

[0025] The tracking data of the meter reading team is generated according to the first change amplitude and the second change amplitude.

[0026] In one embodiment, the meter reader corresponding to each user in arrears is used as a statistical dimension, and according to the total amount of arrears and the collection strategy of each user in arrears, the arrears tracking data and collection strategy distribution of the user in arrears corresponding to each meter reader are determined to generate a personal dashboard report for each meter reader, including:

[0027] According to the meter readers of each user in arrears, each user in arrears is divided to obtain a set of users in arrears belonging to each meter reader;

[0028] For each meter reader, read the total amount of arrears and collection strategy of each arrears user in the set of arrears users corresponding to the meter reader;

[0029] Counting the number of delinquent users with different collection strategies in the delinquent user set corresponding to the meter reader, so as to generate a collection strategy distribution corresponding to the meter reader;

[0030] Calculate a third change range of the sum of the total amount of arrears of each user in the set of arrears users corresponding to the meter reader compared with the previous payment period, and calculate a fourth change range of the number of arrears users in the set of arrears users corresponding to the meter reader compared with the previous payment period;

[0031] generating the meter reader's arrears tracking data according to the third change range and the fourth change range;

[0032] The meter reader's fee collection strategy distribution and the arrears tracking data are visualized in a report to obtain a personal dashboard report of the meter reader.

[0033] In one embodiment, determining the electricity bill arrears data includes:

[0034] Obtain the detailed list of outstanding fees and the meter reading team list;

[0035] Connect and merge the arrears details table and the meter reading team table to obtain target data;

[0036] The target data is preprocessed, and the preprocessed target data is determined as electricity fee arrears data.

[0037] In one embodiment, the method further comprises:

[0038] When the team dashboard report and each meter reader's personal dashboard report are generated, the electricity fee recovery trend is analyzed and predicted based on the team dashboard report and each meter reader's personal dashboard report.

[0039] In a second aspect, the present application provides an electricity fee recovery monitoring device, the device comprising:

[0040] A data determination module is used to determine the electricity bill arrears data, and based on the electricity bill arrears data, count the number of arrears periods and the total amount of arrears for each user in the electricity bill arrears data;

[0041] A strategy determination module, used to determine the corresponding collection strategy for each user in arrears based on the number of arrears periods and the total amount of arrears of each user in arrears;

[0042] The team dashboard generation module is used to use the meter reading team corresponding to each user in arrears as the statistical dimension, determine the arrears tracking data and collection strategy distribution of the arrears users in each meter reading team according to the total amount of arrears and collection strategy of each user in arrears, so as to generate a team dashboard report;

[0043] The personal dashboard generation module is used to use the meter readers corresponding to each user in arrears as statistical dimensions, determine the arrears tracking data and collection strategy distribution of each meter reader according to the total amount of arrears and collection strategy of each user in arrears, so as to generate a personal dashboard report for each meter reader;

[0044] The report sending module is used to send the personal dashboard report of each meter reader and the team dashboard report to the corresponding meter reader respectively.

[0045] In a third aspect, the present application provides a storage medium storing computer-readable instructions. When the computer-readable instructions are executed by one or more processors, the one or more processors execute the steps of the electricity fee recovery monitoring method as described in any of the above embodiments.

[0046] In a fourth aspect, the present application provides a computer device, comprising: one or more processors, and a memory;

[0047] The memory stores computer-readable instructions, and when the one or more processors execute the computer-readable instructions, the steps of the electricity fee recovery monitoring method described in any one of the above embodiments are performed.

[0048] It can be seen from the above technical solutions that the embodiments of the present application have the following advantages:

[0049] The present application provides an electricity fee recovery monitoring method, device, storage medium and computer equipment, the method comprising: using the electricity fee arrears data to count the arrears cycle and the total amount of arrears for each user, and then determining the collection strategy of each user according to the arrears cycle and the total amount of arrears, so that the collection strategy of each user can be automatically analyzed based on the electricity fee arrears data. Then, the meter reading team and the meter reader are used as statistical dimensions, and the arrears tracking data and collection strategy distribution of the arrears users corresponding to each meter reading team and each meter reader are determined according to the total amount of arrears and the collection strategy of each user, and then the team dashboard report and the personal dashboard report of each meter reader are generated and sent to the corresponding meter reader. By generating the team dashboard report and the personal dashboard report of each meter reader to summarize the electricity fee recovery of each meter reading team and each meter reader, the meter reader can directly obtain the analyzed and summarized report to assist the meter reader to better carry out the electricity fee recovery work, reduce the manpower maintenance cost and communication cost, and thus improve the efficiency of electricity fee recovery. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0051] Figure 1 A flow chart of an electricity fee recovery monitoring method provided in an embodiment of the present application;

[0052] Figure 2 A flow chart of determining a corresponding collection strategy for each delinquent user based on the number of delinquent periods and the total amount of delinquent payments provided in an embodiment of the present application;

[0053] Figure 3 A schematic diagram of the structure of an electricity fee recovery monitoring device provided in an embodiment of the present application;

[0054] Figure 4An internal structure diagram of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0055] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0056] In one embodiment, the present application provides a method for monitoring electricity fee recovery, and the following embodiment is described by applying the method to a server. It can be understood that the method for monitoring electricity fee recovery can be performed by a single server or a server cluster composed of multiple servers, and the present application does not make specific restrictions on this.

[0057] like Figure 1 As shown, the present application provides a method for monitoring electricity fee recovery, the method comprising:

[0058] S101: Determine the electricity bill arrears data, and based on the electricity bill arrears data, count the number of arrears periods and the total amount of arrears for each user in the electricity bill arrears data.

[0059] The electricity bill arrears data refers to the arrears data of the electricity users corresponding to each meter reading team, including but not limited to the meter reading team, meter reader, arrears user, user ID, arrears amount, meter reading serial number, arrears user contact information, etc. The number of arrears periods refers to the number of months that the electricity user has not paid the electricity bill on time, and the total amount of arrears refers to the total amount of electricity bills owed by the electricity user.

[0060] In this step, when the power company employees need to know the electricity bill recovery status, the power company employees can initiate a recovery monitoring instruction through the client. When the server receives the recovery monitoring instruction, the server will determine the electricity bill arrears data, and then based on the electricity bill arrears data, count the number of arrears periods and the total amount of arrears for each user in arrears.

[0061] It is understandable that the electricity bill arrears data records the current arrears status of each user in arrears, so the electricity bill arrears data needs to be re-determined each time the electricity bill recovery monitoring is performed to ensure the accuracy and reliability of the electricity bill recovery monitoring.

[0062] Furthermore, the process of counting the number of arrears periods and the total amount of arrears for each user in the electricity bill arrears data includes: determining the records with the same user identifier in the electricity bill arrears data, and determining the number of records with the same user identifier as the number of arrears periods for the arrears users corresponding to the user identifier, so as to determine the number of arrears periods for each user in the electricity bill arrears; and summing the arrears amounts of the records with the same user identifier, and determining the result of the sum as the total amount of arrears for the arrears users corresponding to the user identifier.

[0063] S102: Determine a collection strategy corresponding to each user in arrears based on the number of arrears periods and the total amount of arrears of each user in arrears.

[0064] Among them, the collection strategy refers to the collection measures against users in arrears.

[0065] In this step, the number of overdue periods and the total amount of overdue payments of each user in arrears may be analyzed to determine the arrears situation of each user in arrears, and then the corresponding collection strategy for each user in arrears may be determined according to the arrears situation of each user in arrears.

[0066] Specifically, analysis rules can be set to analyze the number of overdue periods and the total amount of overdue payments for each delinquent user, or a pre-trained learning model can be used to analyze the number of overdue periods and the total amount of overdue payments for each delinquent user. This application does not impose any specific restrictions on this.

[0067] S103: Taking the meter reading team corresponding to each user in arrears as the statistical dimension, according to the total amount of arrears and the collection strategy of each user in arrears, the arrears tracking data and collection strategy distribution of the users in arrears in each meter reading team are determined to generate a team dashboard report.

[0068] Among them, statistical dimensions refer to the attributes used for grouping when organizing and analyzing data, arrears tracking data is used to indicate changes in arrears compared with the previous payment cycle, and collection strategy distribution is used to indicate the distribution of collection strategies.

[0069] In this step, the meter reading team corresponding to each user in arrears is used as the dimension for group analysis. Based on the total amount of arrears and the collection strategy of each user in arrears, the arrears tracking data and collection strategy distribution of the arrears users in each meter reading team are counted. After the arrears tracking data and collection strategy distribution of the arrears users in each meter reading team are determined, a team dashboard report is generated based on the arrears tracking data and collection strategy distribution corresponding to each meter reading team.

[0070] Specifically, the team dashboard report includes the overdue payment tracking data and collection strategy distribution of each meter reading team, and the class dashboard report can be displayed in the form of a visual chart.

[0071] S104: Taking the meter readers corresponding to each delinquent user as the statistical dimension, according to the total amount of delinquent payment and the collection strategy of each delinquent user, the delinquent payment tracking data and collection strategy distribution of each meter reader are determined to generate a personal dashboard report for each meter reader.

[0072] In this step, the meter readers corresponding to each delinquent user are used as the dimension of group analysis. Based on the total amount of delinquent payments and the collection strategies of each delinquent user, the delinquent payment tracking data and collection strategy distribution of each meter reader are counted. After the delinquent payment tracking data and collection strategy distribution of each meter reader are determined, a personal dashboard report for each meter reader is generated based on the delinquent payment tracking data and collection strategy distribution corresponding to each meter reading team.

[0073] Specifically, the personal dashboard report includes the arrears tracking data and collection strategy distribution of one of the meter readers, and the personal dashboard report can be displayed in a visual form of a chart.

[0074] S105: Send the personal dashboard report and the team dashboard report of each meter reader to the corresponding meter reader respectively.

[0075] In this step, for each meter reader, the personal dashboard report and the team dashboard report of the meter reader can be sent to the meter reader, so that each meter reader can understand the collection status of the meter reading team in each meter reading team, and can also understand the arrears status of the users in arrears for which he is responsible.

[0076] It is understandable that the team dashboard report and each meter reader's personal dashboard report can also be sent to each meter reading team or to a higher level. The specific settings can be based on actual needs, and this application does not impose any specific restrictions on this.

[0077] The present application provides an electricity fee recovery monitoring method, device, storage medium and computer equipment, the method comprising: using the electricity fee arrears data to count the arrears cycle and the total amount of arrears for each user, and then determining the collection strategy of each user according to the arrears cycle and the total amount of arrears, so that the collection strategy of each user can be automatically analyzed based on the electricity fee arrears data. Then, the meter reading team and the meter reader are used as statistical dimensions, and the arrears tracking data and collection strategy distribution of the arrears users corresponding to each meter reading team and each meter reader are determined according to the total amount of arrears and the collection strategy of each user, and then the team dashboard report and the personal dashboard report of each meter reader are generated and sent to the corresponding meter reader. By generating the team dashboard report and the personal dashboard report of each meter reader to summarize the electricity fee recovery of each meter reading team and each meter reader, the meter reader can directly obtain the analyzed and summarized report to assist the meter reader to better carry out the electricity fee recovery work, reduce the manpower maintenance cost and communication cost, and thus improve the efficiency of electricity fee recovery.

[0078] like Figure 2 As shown, in one embodiment, based on the number of overdue periods and the total amount of overdue payments of each overdue user, a collection strategy corresponding to each overdue user is determined, including:

[0079] S201: For each user in arrears of electricity bills in the arrears electricity bills data, determine whether the number of arrears periods of the user in arrears is less than a first preset threshold.

[0080] The first preset threshold is an empirical value and can be set and adjusted according to the historical arrears of users.

[0081] S202: If the number of overdue payment periods of the user in arrears is not less than a first preset threshold, determining that the collection strategy for the user in arrears is a power outage strategy.

[0082] The fee collection strategies in this embodiment include a power outage strategy, a payment reminder strategy, and an observation strategy.

[0083] In this step, when the number of arrears of payment by the user in arrears is greater than or equal to the first preset threshold, the collection strategy for the user in arrears is determined as a power outage strategy, wherein the power outage strategy refers to the measure of stopping power supply to the user in arrears.

[0084] S203: If the number of overdue payments of the user in arrears is less than the first preset threshold, determine whether the number of overdue payments of the user in arrears is greater than the second preset threshold.

[0085] The second preset threshold is an empirical value, and the second preset threshold can be set and adjusted according to the historical arrears of users.

[0086] S204: If the number of overdue payments of the user in arrears is greater than the second preset threshold, determine whether the total amount of overdue payments of the user in arrears exceeds a third preset threshold.

[0087] In this step, when the number of overdue periods of the defaulting user is less than the first preset threshold and greater than the second preset threshold, the total amount of the defaulting user is compared with the third preset threshold to determine the collection strategy.

[0088] S205: If it exceeds, determining that the collection strategy for the delinquent user is a power outage strategy.

[0089] S206: If it does not exceed, determining that the collection strategy for the delinquent user is an observation strategy.

[0090] Specifically, when the number of arrears of the user in arrears is less than the first preset threshold and greater than the second preset threshold, if the total amount of arrears of the user in arrears exceeds the third preset threshold, the collection strategy for the user in arrears is determined to be a power outage strategy, and if the total amount of arrears of the user in arrears does not exceed the third preset threshold, the collection strategy for the user in arrears is determined to be an observation strategy. The observation strategy refers to measures to continuously observe the arrears of the user in arrears.

[0091] S207: If the number of overdue payment periods of the user in arrears is not greater than the second preset threshold, determine whether the total amount of overdue payment of the user in arrears exceeds a third preset threshold.

[0092] In this step, when the number of overdue periods of the defaulting user is less than the first preset threshold and not greater than the second preset threshold, the total amount of the defaulting user is compared with the third preset threshold to determine the collection strategy.

[0093] S208: If it exceeds, the collection strategy for the delinquent user is determined to be a collection reminder strategy.

[0094] S209: If it does not exceed, determining that the collection strategy for the delinquent user is an observation strategy.

[0095] Specifically, when the number of arrears of the user in arrears is less than the first preset threshold and not greater than the second preset threshold, if the total amount of arrears of the user in arrears exceeds the third preset threshold, the collection strategy for the user in arrears is determined as a collection strategy, and if the total amount of arrears of the user in arrears does not exceed the third preset threshold, the collection strategy for the user in arrears is determined as an observation strategy. The collection strategy refers to measures to urge the user in arrears to pay.

[0096] For example, assuming that the first preset threshold is 9, the second preset threshold is 1, and the third preset value is 500, when the number of arrears of user A is 10 and the total amount of arrears is 800, the number of arrears of user A is not less than 9, so the collection strategy for user A is a power outage strategy; when the number of arrears of user B is 2 and the total amount of arrears is 800, the number of arrears of user B is less than 9 and greater than 1, and the total amount of arrears exceeds 500, so the collection strategy for user B is a power outage strategy; when the number of arrears of user C is 3 and the total amount of arrears is 300, The number of arrears of user C is less than 9 and greater than 1, and the total amount of arrears does not exceed 500. Therefore, the collection strategy for user C is an observation strategy; when the number of arrears of user D is 1 and the total amount of arrears is 600, the number of arrears of user D is not greater than 1, and the total amount of arrears exceeds 500. Therefore, the collection strategy for user D is a reminder strategy; when the number of arrears of user E is 1 and the total amount of arrears is 200, the number of arrears of user E is not greater than 1, and the total amount of arrears does not exceed 500. Therefore, the collection strategy for user C is an observation strategy.

[0097] In this embodiment, the severity of different arrears situations is divided according to the number of arrears periods and the total amount of arrears of the users, and different collection strategies are adopted. In this way, the collection strategy of each arrears user can be quickly determined through pre-set rules, and different collection strategies are pre-divided, so that the meter reader can quickly determine the collection strategy of each arrears user and understand the arrears situation of each arrears user, and then scientifically recover the electricity charges from the arrears users based on the collection strategies.

[0098] In one embodiment, the meter reading team corresponding to each user in arrears is used as a statistical dimension, and according to the total amount of arrears and the collection strategy of each user in arrears, the arrears tracking data and collection strategy distribution of the users in arrears in each meter reading team are determined to generate a team dashboard report, including:

[0099] S1: Divide each user in arrears according to the meter reading team of each user in arrears, and obtain a set of users in arrears in each meter reading team.

[0100] The set of users in arrears is a set of users in arrears corresponding to the corresponding meter reading team.

[0101] In this step, when the meter reading team corresponding to each user in arrears is used as the statistical dimension, each user in arrears will first be divided according to the meter reading team to which it belongs, and then the set of users in arrears in each meter reading team is obtained.

[0102] S2: For each meter reading team, read the total amount of arrears and the collection strategy of each overdue user in the set of overdue users corresponding to the meter reading team.

[0103] After the delinquent users are divided, for each meter reading team, the total amount of delinquent payments and the collection strategy of each delinquent user in the delinquent user set corresponding to the meter reading team are read.

[0104] S3: Determine the strategy distribution and tracking data of the meter reading team according to the total amount of arrears and the collection strategy of each arrears user in the set of arrears users corresponding to the meter reading team.

[0105] The strategy distribution and tracking data of the meter reading team are calculated based on the total amount of arrears and the collection strategy of each delinquent user corresponding to the meter reading team.

[0106] It can be understood that the strategy distribution refers to the distribution of different collection strategies of the corresponding meter reading team, and the tracking data refers to the changes in the arrears of the arrears users of the corresponding meter reading team compared with the previous payment cycle.

[0107] S4: After the strategy distribution and tracking data of each meter reading team are determined, the fee collection strategy distribution corresponding to each meter reading team is generated according to the strategy distribution of each meter reading team, and the overdue payment tracking data corresponding to each meter reading team is generated according to the tracking data of each meter reading team.

[0108] After determining the policy distribution and tracking data of each meter reading team, a collection policy distribution capable of representing the policy distribution of each meter reading team is generated according to the policy distribution of each meter reading team, and overdue payment tracking data capable of representing the tracking data of each meter reading team is generated according to the tracking data of each meter reading team.

[0109] Specifically, the collection strategy distribution corresponding to each meter reading team in this step refers to the distribution that summarizes the strategy distribution of each meter reading team, and the overdue payment tracking data corresponding to each meter reading team refers to the data that summarizes the tracking data of each meter reading team.

[0110] S5: Visualize the collection strategy distribution and arrears tracking data of each meter reading team in a report to obtain a team dashboard report.

[0111] Specifically, after determining the collection strategy distribution and arrears tracking data of each meter reading team, the collection strategy distribution and arrears tracking data of each meter reading team can be visualized in a report, for example, using a pie chart, a bar chart or other data visualization method to visualize the collection strategy distribution and arrears tracking data, and then obtain a team dashboard report. In this embodiment, by analyzing the statistical data and then visualizing the report, on the one hand, it can save labor costs and improve the efficiency of electricity fee recovery monitoring, and on the other hand, it can ensure the quality of electricity fee recovery work and maintain the good operation of the power company.

[0112] In one embodiment, according to the total amount of arrears and the collection strategy of each user in arrears in the set of users in arrears corresponding to the meter reading team, the strategy distribution and tracking data of the meter reading team are determined, including:

[0113] S1: Count the number of delinquent users with different payment collection strategies in the delinquent user set corresponding to the meter reading team to generate a strategy distribution corresponding to the meter reading team.

[0114] By calculating the number of delinquent users with different collection strategies among the delinquent users corresponding to the meter reading team, and then calculating the proportion of the number of delinquent users with each collection strategy to the number of delinquent users corresponding to the meter reading team, the strategy distribution corresponding to the meter reading team is generated based on this.

[0115] For example, assuming that the set of delinquent users corresponding to meter reading team A includes delinquent users a, b, c and d, and the collection strategies of delinquent users a, b, c and d are reminder strategy, observation strategy, observation strategy and power outage strategy respectively, then it can be determined that the number of delinquent users whose collection strategy is the reminder strategy is 1, and the number of delinquent users whose collection strategy is the observation strategy is 2, and the number of delinquent users whose collection strategy is the power outage strategy is 1, and the number of delinquent users in the set of delinquent users is 4. At this time, the proportion of the reminder strategy is 25% (1 / 4), the proportion of the observation strategy is 50% (2 / 4), and the proportion of the power outage strategy is 25% (1 / 4). According to these three proportions, the strategy distribution corresponding to meter reading team A can be determined.

[0116] S2: Calculate the first change range of the sum of the total amount of arrears of each user in the set of arrears users corresponding to the meter reading team compared with the previous payment period, and calculate the second change range of the number of arrears users in the set of arrears users corresponding to the meter reading team compared with the previous payment period.

[0117] S3: Generate tracking data of the meter reading team according to the first change amplitude and the second change amplitude.

[0118] Specifically, the first range of change between the two can be determined by obtaining the sum of the total amount of arrears of each user in the set of arrears users corresponding to the meter reading team in the previous payment period, and then comparing it with the sum of the total amount of arrears of each user in the set of arrears users corresponding to the meter reading team calculated by the current electricity fee recovery monitoring, and the second range of change between the two can be determined by obtaining the number of arrears users in the set of arrears users corresponding to the meter reading team in the previous payment period, and then comparing it with the number of arrears users in the set of arrears users corresponding to the meter reading team calculated by the current electricity fee recovery monitoring.

[0119] For example, assuming that the total amount of arrears of each user in the set of arrears users corresponding to the meter reading team in the previous payment period is a, and the total amount of arrears of each user in the set of arrears users corresponding to the meter reading team calculated by this electricity fee recovery monitoring is b, then the first change range is (ba) / a, and the second change range is the same.

[0120] In this embodiment, the change between the current electricity fee recovery monitoring and the electricity fee recovery monitoring in the previous payment cycle is intuitively reflected by calculating the first change amplitude and the second change amplitude, so that the trend curve of the user's arrears can be further determined, so that the information can be quickly conveyed to the meter reader, and compared with manual calculation and analysis, this method can save labor costs and time costs, and improve the efficiency of electricity fee recovery.

[0121] In one embodiment, the meter readers corresponding to each user in arrears are used as statistical dimensions, and according to the total amount of arrears and the collection strategy of each user in arrears, the arrears tracking data and collection strategy distribution of the user in arrears corresponding to each meter reader are determined to generate a personal dashboard report for each meter reader, including:

[0122] S1: Divide the users in arrears according to their meter readers, and obtain a set of users in arrears belonging to each meter reader.

[0123] S2: For each meter reader, read the total amount of arrears and the collection strategy of each delinquent user in the set of delinquent users corresponding to the meter reader.

[0124] S3: Count the number of delinquent users with different collection strategies in the delinquent user set corresponding to the meter reader, so as to generate a collection strategy distribution corresponding to the meter reader.

[0125] S4: Calculate a third change range of the sum of the total amount of arrears of each user in the set of arrears users corresponding to the meter reader compared with the previous payment cycle, and calculate a fourth change range of the number of arrears users in the set of arrears users corresponding to the meter reader compared with the previous payment cycle.

[0126] S5: Generate the arrears tracking data of the meter reader according to the third change range and the fourth change range.

[0127] S6: Visualize the distribution of the collection strategy and the arrears tracking data of the meter reader in a report to obtain a personal dashboard report of the meter reader.

[0128] It should be noted that this embodiment is different from the above two embodiments only in statistical dimensions. For the description of this embodiment, reference may be made to the description of the above two embodiments.

[0129] In this embodiment, by analyzing the statistical data and then visualizing the report, on the one hand, it can save labor costs and improve the efficiency of electricity fee recovery monitoring, and on the other hand, it can ensure the quality of electricity fee recovery and maintain the good operation of the power company. In addition, the statistics are summarized in two dimensions: meter reading team and meter reader, so that the meter reader can not only understand the arrears of the users in arrears that he is responsible for, but also understand the overall situation of his meter reading team and other meter reading teams.

[0130] In one embodiment, determining the electricity bill arrears data includes:

[0131] S1: Obtain the details of outstanding payments and meter reading team list.

[0132] S2: Connect and merge the arrears details table and the meter reading team table to obtain the target data.

[0133] S3: Preprocess the target data, and determine the preprocessed target data as electricity fee arrears data.

[0134] Among them, the arrears details table includes but is not limited to arrears users, user identification, arrears amount, overdue serial number, arrears users' contact information, etc., and the meter reading team table includes but is not limited to meter readers, meter reading teams, meter reading serial numbers, etc.

[0135] In this embodiment, when the arrears detail table and the meter reading team table are obtained, the arrears detail table and the meter reading team table are connected and merged. For example, the arrears detail table and the meter reading team table are connected together with the meter reading sequence number as the foreign key to obtain the target data. Then, the target data is preprocessed to remove abnormal records in the target data, such as records with null values, user identifiers that have been cancelled, etc. Finally, the preprocessed target data is determined as the electricity bill arrears data.

[0136] In one embodiment, the electricity fee recovery monitoring method further includes: collecting the records removed during preprocessing to form an abnormality record table. This makes it convenient for operation and maintenance personnel to review the abnormality record table and locate the cause of the abnormality to improve the electricity fee recovery process.

[0137] In one embodiment, the electricity fee recovery monitoring method further includes:

[0138] When the team dashboard report and each meter reader's personal dashboard report are generated, the electricity fee recovery trend is analyzed and predicted based on the team dashboard report and each meter reader's personal dashboard report.

[0139] In this embodiment, based on the team dashboard report and each meter reader's personal dashboard report, big data analysis technology can be used to analyze and predict the electricity fee recovery trend, understand the future electricity fee recovery trend in advance, and thus deploy electricity fee recovery measures in a targeted manner, while also improving the intelligence level of electricity fee recovery monitoring.

[0140] In one example, when the electricity fee recovery monitoring method described in this application is applied to an application deployed on the server side, the data processing layer of the application can be built using the Python language, the user UI layer can be built using the Electron tool, and the data storage layer can use SQLite. The deployed operating system is not limited to Windows, Linux, and Galaxy Kirin. In this example, the tools or environments used are not limited to the above examples. This application does not make specific restrictions on this.

[0141] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0142] The following is a description of the electricity fee recovery monitoring device provided in an embodiment of the present application. The electricity fee recovery monitoring device described below and the electricity fee recovery monitoring method described above can be referenced to each other.

[0143] like Figure 3 As shown, the present application provides an electricity fee recovery monitoring device 300, the device comprising:

[0144] The data determination module 301 is used to determine the electricity bill arrears data, and based on the electricity bill arrears data, count the number of arrears periods and the total amount of arrears for each user in the electricity bill arrears data;

[0145] A strategy determination module 302 is used to determine a corresponding collection strategy for each defaulting user based on the number of defaulting periods and the total amount of defaulting of each defaulting user;

[0146] The team dashboard generation module 303 is used to determine the arrears tracking data and collection strategy distribution of the arrears users in each meter reading team based on the total amount of arrears and collection strategy of each arrears user, so as to generate a team dashboard report;

[0147] The personal dashboard generation module 304 is used to determine the arrears tracking data and collection strategy distribution of the arrears users corresponding to each meter reader based on the total amount of arrears and collection strategies of each arrears user, so as to generate a personal dashboard report for each meter reader;

[0148] The report sending module 305 is used to send the personal dashboard report and the team dashboard report of each meter reader to the corresponding meter reader.

[0149] In one embodiment, the policy determination module includes:

[0150] The first strategy determination submodule is used to determine, for each user in arrears in the electricity bill arrears data, whether the number of arrears periods of the user in arrears is less than a first preset threshold value, and if the number of arrears periods of the user in arrears is not less than the first preset threshold value, determine that the collection strategy for the user in arrears is a power outage strategy;

[0151] The term number determination submodule is used to determine whether the number of unpaid terms of the user in arrears is greater than a second preset threshold value if the number of unpaid terms of the user in arrears is less than a first preset threshold value;

[0152] The second strategy determination submodule is used to determine whether the total amount of arrears of the user in arrears exceeds a third preset threshold if the number of arrears of the user in arrears is greater than the second preset threshold, and if so, determine that the collection strategy for the user in arrears is a power outage strategy; if not, determine that the collection strategy for the user in arrears is an observation strategy;

[0153] The third strategy determination submodule is used to determine whether the total amount of arrears of the user in arrears exceeds the third preset threshold if the number of arrears periods of the user in arrears is not greater than the second preset threshold; if so, determine that the collection strategy for the user in arrears is a collection reminder strategy; if not, determine that the collection strategy for the user in arrears is an observation strategy.

[0154] In one embodiment, the team kanban generation module includes:

[0155] The user classification submodule is used to classify each user in arrears according to the meter reading team of each user in arrears, and obtain a set of users in arrears in each meter reading team;

[0156] The first data reading submodule is used to read, for each meter reading team, the total amount of arrears and the collection strategy of each arrears user in the set of arrears users corresponding to the meter reading team;

[0157] The first data determination submodule is used to determine the strategy distribution and tracking data of the meter reading team according to the total amount of arrears and the collection strategy of each arrears user in the set of arrears users corresponding to the meter reading team;

[0158] The second data determination submodule is used to generate the corresponding fee collection strategy distribution of each meter reading team according to the strategy distribution of each meter reading team after determining the strategy distribution and tracking data of each meter reading team, and to generate the corresponding arrears tracking data of each meter reading team according to the tracking data of each meter reading team;

[0159] The visualization submodule is used to visualize the collection strategy distribution and arrears tracking data of each meter reading team in a report to obtain a team dashboard report.

[0160] In one embodiment, the first data determination submodule includes:

[0161] A distribution generating unit, used for counting the number of users in arrears with different payment collection strategies in the set of users in arrears corresponding to the meter reading team, so as to generate a strategy distribution corresponding to the meter reading team;

[0162] A range calculation unit is used to calculate a first change range of the sum of the total amount of arrears of each user in the set of arrears users corresponding to the meter reading team compared with the previous payment period, and to calculate a second change range of the number of arrears users in the set of arrears users corresponding to the meter reading team compared with the previous payment period;

[0163] The data generating unit is used to generate tracking data of the meter reading team according to the first change amplitude and the second change amplitude.

[0164] In one embodiment, the personal dashboard generation module includes:

[0165] A set determination submodule is used to divide each user in arrears according to the meter reader of each user in arrears, and obtain a set of users in arrears of each meter reader;

[0166] The second data reading submodule is used to read, for each meter reader, the total amount of arrears and the collection strategy of each arrears user in the set of arrears users corresponding to the meter reader;

[0167] A distribution generation submodule is used to count the number of users in arrears with different collection strategies in the set of users in arrears corresponding to the meter reader, so as to generate a collection strategy distribution corresponding to the meter reader;

[0168] A range calculation submodule, used to calculate a third change range of the sum of the total amount of arrears of each user in the set of arrears users corresponding to the meter reader compared with the previous payment period, and to calculate a fourth change range of the number of arrears users in the set of arrears users corresponding to the meter reader compared with the previous payment period;

[0169] A third data determination submodule, for generating the meter reader's arrears tracking data according to the third change range and the fourth change range;

[0170] The report generation submodule is used to visualize the collection strategy distribution and the arrears tracking data of the meter reader to obtain a personal dashboard report of the meter reader.

[0171] In one embodiment, the data determination module includes:

[0172] The table acquisition submodule is used to obtain the arrears details table and the meter reading team table;

[0173] The table merging submodule is used to connect and merge the arrears details table and the meter reading team table to obtain the target data;

[0174] The preprocessing submodule is used to preprocess the target data and determine the preprocessed target data as electricity fee arrears data.

[0175] In one embodiment, the electricity fee recovery monitoring device further includes:

[0176] The recovery prediction module is used to analyze and predict the electricity fee recovery trend according to the team dashboard report and the personal dashboard report of each meter reader when generating the team dashboard report and the personal dashboard report of each meter reader.

[0177] The division of each module in the above-mentioned electricity fee recovery monitoring device is only used for illustration. In other embodiments, the electricity fee recovery monitoring device can be divided into different modules as needed to complete all or part of the functions of the above-mentioned electricity fee recovery monitoring device. Each module in the above-mentioned electricity fee recovery monitoring device can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0178] In one embodiment, the present application also provides a storage medium, in which computer-readable instructions are stored. When the computer-readable instructions are executed by one or more processors, the one or more processors execute the steps of the electricity fee recovery monitoring method as described in any of the above embodiments.

[0179] In one embodiment, the present application also provides a computer device, in which computer-readable instructions are stored. When the computer-readable instructions are executed by one or more processors, the one or more processors execute the steps of the electricity fee recovery monitoring method as described in any of the above embodiments.

[0180] Indicatively, Figure 4 As shown, Figure 4 This is a schematic diagram of the internal structure of a computer device provided in an embodiment of the present application. The computer device 400 may be provided as a server. Figure 4 The computer device 400 includes a processing component 402, which further includes one or more processors, and a memory resource represented by a memory 401, for storing instructions executable by the processing component 402, such as an application. The application stored in the memory 401 may include one or more modules, each corresponding to a set of instructions. In addition, the processing component 402 is configured to execute instructions to perform the electricity fee recovery monitoring method of any of the above embodiments.

[0181] The computer device 400 may further include a power supply component 403 configured to perform power management of the computer device 400, a wired or wireless network interface 404 configured to connect the computer device 400 to a network, and an input / output (I / O) interface 405. The computer device 400 may operate based on an operating system stored in the memory 401, such as Windows Server TM, Mac OS X TM, Unix TM, Linux TM, Free BSD TM, or the like.

[0182] Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0183] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish an entity or operation from another entity or operation, and do not necessarily require or imply that there is any such actual relationship or order between these entities or operations. Moreover, the term "include", "comprise" or any other variant thereof is intended to cover non-exclusive inclusion, so that the process, method, article or equipment including a series of elements not only include those elements, but also include other elements that are not clearly listed, or also include elements inherent to such process, method, article or equipment. In the absence of more restrictions, the elements limited by the sentence "comprise one..." do not exclude the existence of other identical elements in the process, method, article or equipment including the elements. Herein, the singular "one", "one" and "described / the" may also include plural forms, unless the context clearly indicates another way. It should also be understood that the terms "include / comprise" or "have" etc. specify the existence of stated features, wholes, steps, operations, components, parts or combinations thereof, but do not exclude the possibility of the existence or addition of one or more other features, wholes, steps, operations, components, parts or combinations thereof. At the same time, the term "and / or" used in this specification includes any and all combinations of the relevant listed items.

[0184] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The various embodiments can be combined as needed, and the same or similar parts can refer to each other.

[0185] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for monitoring electricity fee recovery, characterized in that: The method comprises: Determine the electricity bill arrears data, and based on the electricity bill arrears data, count the number of arrears periods and the total amount of arrears for each user in the electricity bill arrears data; Determine the collection strategy for each user in arrears based on the number of arrears and the total amount of arrears for each user in arrears; The meter reading team corresponding to each user in arrears is used as the statistical dimension. According to the total amount of arrears and the collection strategy of each user in arrears, the arrears tracking data and collection strategy distribution of the users in each meter reading team are determined to generate a team dashboard report. The meter readers corresponding to each user in arrears are used as statistical dimensions. According to the total amount of arrears and collection strategies of each user in arrears, the arrears tracking data and collection strategy distribution of each meter reader in arrears are determined to generate a personal dashboard report for each meter reader. The personal dashboard report of each meter reader and the team dashboard report are sent to the corresponding meter readers respectively.

2. The method for monitoring electricity fee recovery according to claim 1, characterized in that: The method of determining the corresponding collection strategy for each user in arrears based on the number of arrears periods and the total amount of arrears of each user in arrears includes: For each user in arrears in the electricity bill arrears data, determining whether the number of arrears periods of the user in arrears is less than a first preset threshold, and if the number of arrears periods of the user in arrears is not less than the first preset threshold, determining that the collection strategy for the user in arrears is a power outage strategy; If the number of overdue payments of the user in arrears is less than the first preset threshold, determining whether the number of overdue payments of the user in arrears is greater than the second preset threshold; If the number of arrears of the user in arrears is greater than the second preset threshold, it is determined whether the total amount of arrears of the user in arrears exceeds the third preset threshold; if so, the collection strategy for the user in arrears is determined to be a power outage strategy; if not, the collection strategy for the user in arrears is determined to be an observation strategy; If the number of overdue payment periods of the defaulting user is not greater than the second preset threshold, it is determined whether the total amount of overdue payment of the defaulting user exceeds the third preset threshold. If it exceeds, the collection strategy for the defaulting user is determined to be a collection reminder strategy; if it does not exceed, the collection strategy for the defaulting user is determined to be an observation strategy.

3. The method for monitoring electricity fee recovery according to claim 1, characterized in that: The meter reading team corresponding to each user in arrears is used as a statistical dimension, and according to the total amount of arrears and the collection strategy of each user in arrears, the arrears tracking data and collection strategy distribution of the users in arrears in each meter reading team are determined to generate a team dashboard report, including: According to the meter reading team of each user in arrears, each user in arrears is divided to obtain a set of users in arrears in each meter reading team; For each meter reading team, read the total amount of arrears and the collection strategy of each arrears user in the set of arrears users corresponding to the meter reading team; Determine the strategy distribution and tracking data of the meter reading team according to the total amount of arrears and the collection strategy of each arrears user in the set of arrears users corresponding to the meter reading team; After determining the strategy distribution and tracking data of each meter reading team, generating the corresponding fee collection strategy distribution of each meter reading team according to the strategy distribution of each meter reading team, and generating the corresponding arrears tracking data of each meter reading team according to the tracking data of each meter reading team; The collection strategy distribution and arrears tracking data of each meter reading team are visualized in a report to obtain a team dashboard report.

4. The method for monitoring electricity fee recovery according to claim 3, characterized in that: Determining the strategy distribution and tracking data of the meter reading team according to the total amount of arrears and the collection strategy of each arrears user in the set of arrears users corresponding to the meter reading team includes: Count the number of users in arrears with different collection strategies in the set of users in arrears corresponding to the meter reading team, so as to generate a strategy distribution corresponding to the meter reading team; Calculate the first change range of the sum of the total amount of arrears of each user in the set of arrears users corresponding to the meter reading team compared to the previous payment period, and calculate the second change range of the number of arrears users in the set of arrears users corresponding to the meter reading team compared to the previous payment period; The tracking data of the meter reading team is generated according to the first change amplitude and the second change amplitude.

5. The method for monitoring electricity fee recovery according to claim 1, characterized in that: The meter reader corresponding to each user in arrears is used as a statistical dimension, and according to the total amount of arrears and the collection strategy of each user in arrears, the arrears tracking data and collection strategy distribution of the user in arrears corresponding to each meter reader are determined to generate a personal dashboard report for each meter reader, including: According to the meter readers of each user in arrears, each user in arrears is divided to obtain a set of users in arrears belonging to each meter reader; For each meter reader, read the total amount of arrears and collection strategy of each arrears user in the set of arrears users corresponding to the meter reader; Counting the number of delinquent users with different collection strategies in the delinquent user set corresponding to the meter reader, so as to generate a collection strategy distribution corresponding to the meter reader; Calculate a third change range of the sum of the total amount of arrears of each user in the set of arrears users corresponding to the meter reader compared with the previous payment period, and calculate a fourth change range of the number of arrears users in the set of arrears users corresponding to the meter reader compared with the previous payment period; generating the meter reader's arrears tracking data according to the third change range and the fourth change range; The meter reader's fee collection strategy distribution and the arrears tracking data are visualized in a report to obtain a personal dashboard report of the meter reader.

6. The method for monitoring electricity fee recovery according to claim 1, characterized in that: The determining of the electricity fee arrears data includes: Obtain the detailed list of outstanding fees and the meter reading team list; Connect and merge the arrears details table and the meter reading team table to obtain target data; The target data is preprocessed, and the preprocessed target data is determined as electricity fee arrears data.

7. The method for monitoring electricity fee recovery according to any one of claims 1 to 6, characterized in that: The method further comprises: When the team dashboard report and each meter reader's personal dashboard report are generated, the electricity fee recovery trend is analyzed and predicted based on the team dashboard report and each meter reader's personal dashboard report.

8. An electricity fee recovery monitoring device, characterized in that: The device comprises: A data determination module is used to determine the electricity bill arrears data, and based on the electricity bill arrears data, count the number of arrears periods and the total amount of arrears for each user in the electricity bill arrears data; A strategy determination module, used to determine the corresponding collection strategy for each user in arrears based on the number of arrears periods and the total amount of arrears of each user in arrears; The team dashboard generation module is used to use the meter reading team corresponding to each user in arrears as the statistical dimension, determine the arrears tracking data and collection strategy distribution of the arrears users in each meter reading team according to the total amount of arrears and collection strategy of each user in arrears, so as to generate a team dashboard report; The personal dashboard generation module is used to use the meter readers corresponding to each user in arrears as statistical dimensions, determine the arrears tracking data and collection strategy distribution of each meter reader according to the total amount of arrears and collection strategy of each user in arrears, so as to generate a personal dashboard report for each meter reader; The report sending module is used to send the personal dashboard report of each meter reader and the team dashboard report to the corresponding meter reader respectively.

9. A storage medium, characterized in that: The storage medium stores computer-readable instructions, and when the computer-readable instructions are executed by one or more processors, the one or more processors execute the steps of the electricity fee recovery monitoring method as described in any one of claims 1 to 7.

10. A computer device, characterized in that: include: one or more processors, and memory; The memory stores computer-readable instructions, and when the computer-readable instructions are executed by the one or more processors, the steps of the electricity fee recovery monitoring method as described in any one of claims 1 to 7 are performed.

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