Smart community life service system and platform

Abstract

The invention discloses a smart community life service system and platform, and relates to the technical field of smart communities, and the system comprises a community user division module, a user behavior optimization module, a smart community analysis module, an early warning terminal and a database. Analyzing the users in different levels based on the payment attitudes to obtain enthusiasm keeping measures corresponding to the high-quality users and dynamic characteristic values and basic characteristic values corresponding to the target users, and analyzing to obtain dressing modes and dressing measures corresponding to the target users based on the obtained characteristic values; and then the effectiveness of the trimming measures corresponding to the target users is judged, so that the efficient management of the smart community is realized, the service efficiency and system of the smart community are further improved, the frequency and viscosity of the user application life service platform are enhanced, the targeted management aiming at the feature level of each user is realized, and the user satisfaction is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of smart communities, and in particular to a smart community life service system and platform. Background Art

[0002] With the continuous coverage of smart communities, the corresponding life services in the communities have become more convenient, and based on the new generation of information technology adopted by smart communities, the efficiency and intelligence of community life services have been realized. By monitoring the user execution of life services covered by smart communities, we can understand whether the life service platform provided by the smart community is in efficient service and whether it is in effective operation when providing life services to users. In this way, we can realize the supervision of intelligent platform service systems and provide efficient, comprehensive and effective life services.

[0003] Prior art, such as the invention patent application disclosed in announcement number CN109397300B, discloses a smart community life service platform, which includes a life service robot and a user terminal that controls the life service robot. The life service robot includes a body, a camera, a screen, a code scanning area, movable arms, movable legs, a cleaning device, a garbage storage box, an item storage box, a control module, a power module, a power module, a GPS module, and a communication module. The camera is used for shooting and monitoring, the screen is used to display the use status of the life service robot or input operating instructions, and the code scanning area is used to obtain the barcode or order number of an item. The garbage storage box and the item storage box are used to store garbage and items, respectively. The power module is used to provide electrical energy, the power module is used to provide power, and the GPS module is used for location positioning and walking route navigation. The life service robot is connected to the user terminal via the communication module to transmit operating instructions. The present invention provides multifunctional and convenient life services.

[0004] Regarding the above scheme, there are the following technical problems: the above invention is mainly based on providing multifunctional and convenient life services based on life service robots, and does not analyze and understand the payment attitudes of each user in the community, and thus cannot divide the payment attitudes of each user into high-quality and unqualified. It cannot timely know and solve the delay problem in community life services, and cannot ensure that the corresponding smart life services of the community are effectively implemented, which reduces the efficient embodiment of the corresponding smart life services of the community. At the same time, it is also impossible to analyze and obtain the corresponding enthusiasm maintenance measures of each high-quality user based on the payment attitude evaluation value of each high-quality user, and cannot guarantee the enthusiasm of each high-quality user to pay for life in the long term. It also does not obtain the dynamic data and life data corresponding to each target user, and cannot analyze and obtain the dynamic characteristic values ​​and basic characteristic values ​​corresponding to each target user. It is impossible to understand the characteristics of each target user in life, and thus cannot analyze and obtain the corresponding adjustment methods and adjustment measures of each target user, and fails to achieve timely and effective solution to the payment problem. It also does not monitor the corresponding target users after the adjustment measures are implemented, and cannot ensure the effectiveness of the corresponding adjustment measures of each target user. Summary of the Invention

[0005] In response to the above-mentioned technical deficiencies, the purpose of the present invention is to provide a smart community life service system and platform.

[0006] In order to solve the above technical problems, the present invention adopts the following technical solutions: The present invention provides a smart community life service system, including: a community user classification module, which is used to monitor the property payment of each user corresponding to the community, and then obtain the corresponding payment data, and analyze the payment attitude of each user corresponding to the community, and based on the payment attitude evaluation value of each user corresponding to the community, further divide the community into high-quality users and target users.

[0007] The user behavior optimization module is used to analyze the payment attitude evaluation values ​​of each high-quality user, and then obtain the corresponding enthusiasm maintenance measures for each high-quality user, and obtain the dynamic data and life data of each target user respectively, and analyze them to obtain the dynamic feature values ​​and basic feature values ​​of each target user respectively.

[0008] The smart community analysis module is used to analyze the dynamic characteristic values ​​and basic characteristic values ​​corresponding to each target user, and then obtain the corresponding adjustment method and adjustment measures for each target user. It also monitors the corresponding target users after the adjustment measures are implemented, and determines the effectiveness of the adjustment measures for each target user.

[0009] The early warning terminal is used to issue early warning prompts when a user's payment attitude is unsatisfactory or the corresponding correction measures for a target user are ineffective.

[0010] In a second aspect, the present invention provides a software scheduling method for load balancing of a circuit controller communication link, including a server end, which is used to provide a community announcement end, a neighborhood social end, a community e-commerce end, and a property life payment end. Compared with the existing technology, the beneficial effect of the present invention is that: the present invention provides a smart community life service system and platform, which analyzes the payment attitude of each user corresponding to the community, and then analyzes each user at different levels based on the payment attitude, obtains the enthusiasm maintenance measures corresponding to each high-quality user and the dynamic characteristic values ​​and basic characteristic values ​​corresponding to each target user, and based on the obtained characteristic values, analyzes the corresponding adjustment methods and adjustment measures for each target user, and then judges the effectiveness of the corresponding adjustment measures for each target user, thereby realizing efficient management of the smart community, further improving the service efficiency and system of the smart community, enhancing the frequency and viscosity of users applying the life service platform, and realizing targeted management at the characteristic level of each user, so as to improve the service satisfaction of the user application experience and make the life service of the smart community more comprehensively optimized.

[0011] 2. It is used to monitor the property payment of each user in the community, and then analyze the payment attitude of each user in the community, so as to make a more detailed classification of user types, thereby providing a reference benchmark in different directions for the subsequent optimization and improvement of the corresponding life services of the smart community, so as to achieve more comprehensive optimization of the life services of the smart community.

[0012] 3. Through analysis, we can obtain the corresponding measures to maintain the enthusiasm of each high-quality user, and obtain the dynamic data and life data corresponding to each target user respectively. We can analyze and obtain the dynamic characteristic values ​​and basic characteristic values ​​corresponding to each target user, and implement differentiated strategies for different user groups to enhance the frequency and stickiness of users' application of the life service platform, realize targeted management at the characteristic level of each user, and ensure the efficient application and operation of the smart community.

[0013] 4. Based on the dynamic characteristic values ​​and basic characteristic values ​​corresponding to each target user, the corresponding adjustment methods and adjustment measures of each target user are analyzed, and the corresponding target users after the implementation of the adjustment measures are monitored to judge the effectiveness of the adjustment measures corresponding to each target user, and to have a more comprehensive understanding of the needs and preferences of each target user, so as to take targeted rectification measures, so as to mobilize the enthusiasm of users to pay actively in an all-round way, solve the problem of payment arrears or overdue, and further improve the life service system of the smart community. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0015] Figure 1 This is a schematic diagram of the system structure connection of the present invention.

[0016] Figure 2 Schematic diagram of the platform structure of the present invention. DETAILED DESCRIPTION

[0017] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts are within the scope of protection of the present invention.

[0018] See also Figure 1 As shown, a smart community life service system includes a community user classification module, a user behavior optimization module, a smart community analysis module, an early warning terminal and a database.

[0019] The community user segmentation module is connected to the user behavior optimization module, the early warning terminal and the database respectively; the chain user behavior optimization module is connected to the smart community analysis module and the database respectively; and the chain smart community analysis module is connected to the early warning terminal and the database respectively.

[0020] The link load monitoring unit includes a link performance testing module, a link flow testing module, a link status testing module and a communication link load classification module.

[0021] The community user segmentation module is used to monitor the property payment of each user in the community, obtain the corresponding payment data, and analyze the payment attitude of each user in the community. Based on the payment attitude evaluation value of each user in the community, it is divided into high-quality users and target users.

[0022] It should be noted that when community properties notify users that they need to pay property fees, they will take advance notice of property payment fees to reserve sufficient time for users to pay property fees. In the present invention, after the property issues a property payment notice to each user in the community, the reaction behavior of each user under the notice is monitored, and then the payment attitude of each user in the community is judged, so as to divide each user and carry out corresponding service management.

[0023] As an optional implementation method, the analysis obtains the payment attitude of each user corresponding to the community. The specific analysis process is as follows: after sending a payment notification to each user through the community's corresponding life service platform, the payment data of each user corresponding to the community is monitored, including the payment cycle, delay days and communication response time, and the standard range of the corresponding user payment data during the community's historical property payment is obtained from the database, and then the payment attitude evaluation value of each user corresponding to the community is analyzed. When the payment attitude evaluation value of the community corresponding to a certain user is 1, the user is defined as a high-quality user, and each high-quality user is obtained by analysis, and the enthusiasm maintenance measures corresponding to each high-quality user are analyzed. When the payment attitude evaluation value of the community corresponding to a certain user is -1, the user is defined as a target user, and each target user is obtained by analysis.

[0024] As an optional implementation, the analysis obtains the payment attitude evaluation value of each user in the community. The specific analysis process is as follows: by calculating the formula: ,in For the community The payment attitude evaluation value of each user, is the ID of each user, , is any integer greater than 2, The payment data number. , 1, 2 and 3 are payment cycle, delay days and communication response time respectively, For the community Payment data of each user, The standard range of user payment data corresponding to the payment of historical properties in the community.

[0025] It is used to monitor the property payment of each user in the community, and then analyze the payment attitude of each user in the community, so as to make a more detailed classification of user types, thereby providing a reference benchmark in different directions for the subsequent optimization and improvement of the corresponding life services of the smart community, so as to achieve more comprehensive optimization of smart community life services.

[0026] It should be noted that the payment data of each user in the community is extracted from the property fee payment terminal corresponding to the life service platform; the standard range is set by professional community management personnel; the standard range is a reference value for judging the payment attitude of each user in the current community when fulfilling their payment tasks; the payment data contains payment cycles, delay days and communication response time, which correspond to their respective standard ranges, namely the payment cycle standard range, delay days standard range and communication response time standard range.

[0027] The user behavior optimization module is used to analyze the payment attitude evaluation values ​​of each high-quality user, and then obtain the corresponding enthusiasm maintenance measures for each high-quality user, and obtain the dynamic data and life data of each target user respectively, and analyze them to obtain the dynamic feature values ​​and basic feature values ​​of each target user respectively.

[0028] As an optional implementation method, the analysis obtains the corresponding motivation maintenance measures of each high-quality user. The specific analysis process is as follows: Based on the payment attitude evaluation value corresponding to each high-quality user , and preset the threshold intervals of each reference payment attitude evaluation value corresponding to the user's quality level. One threshold interval corresponds to one quality level. The quality levels include C level, B level and A level. If the payment attitude evaluation value corresponding to a quality user is Belongs to the threshold interval of a certain reference payment attitude evaluation value, and the quality level corresponding to the threshold interval of the reference payment attitude evaluation value is level A, then the enthusiasm maintenance measures corresponding to the quality user under level A are executed. If the payment attitude evaluation value corresponding to a quality user is Belongs to the threshold interval of a reference payment attitude evaluation value, and the quality level corresponding to the threshold interval of the reference payment attitude evaluation value is level B, then the enthusiasm maintenance measures corresponding to the B level of the quality user are executed. If the payment attitude evaluation value corresponding to a quality user is Belonging to a threshold interval of a reference payment attitude evaluation value, the quality level corresponding to the threshold interval of the reference payment attitude evaluation value is C level, then the enthusiasm maintenance measures corresponding to the C level of the high-quality user are executed, so as to obtain the enthusiasm maintenance measures corresponding to each high-quality user.

[0029] It should be noted that if the measures to maintain the enthusiasm of a high-quality user under level A are implemented: by granting the high-quality user corresponding special privileges, such as priority reservation rights for housekeeping and cleaning services, discounts or an 8% discount on property fees, and commending the high-quality user in the form of text and medals in the community announcements and community dynamics sections of the smart community, the measures to maintain the enthusiasm of the high-quality user under level A will be implemented; if the measures to maintain the enthusiasm of a high-quality user under level B are implemented: by presetting the corresponding continuous payment time points for the high-quality user, for example, if the user maintains the property fee payment at the same time as the current time for 6 consecutive months, he can redeem Exchange for supermarket shopping vouchers or movie tickets, etc., and invite the high-quality user to participate in the community service plan research, and the adopted suggestions will be announced in the corresponding community; if the enthusiasm maintenance measures under the C level of a high-quality user are implemented: by setting a preliminary reward for the high-quality user who reaches the high-quality user level for the first time, such as rewarding supermarket or car wash vouchers, and then pre-setting the high-quality user level upgrade reward. When the user pays the property fee on the basis of the current payment period for 6 consecutive months, the high-quality user will be rewarded with corresponding daily necessities or community service free experience vouchers, etc., among which daily necessities include rice, oil or paper, etc.; community service free experience vouchers include car wash or community fitness experience, etc.

[0030] As an optional implementation method, the analysis obtains the dynamic feature value corresponding to each target user. The specific analysis process is as follows: by monitoring the dynamic trajectory of each target user on the community life service platform, and presetting the reference vocabulary frequency, the dynamic vocabulary corresponding to each target user in the service end is extracted. When a dynamic vocabulary corresponding to a target user is greater than or equal to the preset reference vocabulary frequency, the dynamic vocabulary corresponding to the target user is recorded as a high-frequency vocabulary, and the high-frequency vocabulary is used as the target point corresponding to the target user in the platform end. In this way, the target point corresponding to each target user in the platform end is extracted.

[0031] Based on the dynamic data of the target points corresponding to each target user on the community service end, including dynamic publishing frequency, dynamic group discussion frequency and dynamic announcement reading volume, the dynamic data corresponding to each target user is processed to obtain the dynamic feature value corresponding to each target user. , is the number of each target user, , is any integer greater than 2.

[0032] As an optional implementation method, the analysis obtains the basic characteristic values ​​corresponding to each target user. The specific analysis process is as follows: based on the target points corresponding to each user obtained by analysis, the implementation participation of each target user in the corresponding target point is monitored, and the community service activities consistent with the target point type are extracted at the community announcement terminal and the social neighborhood terminal. The participation data of each target user in each community service activity is extracted, including the number of participations, the number of related persons driven by participation, and the response speed of participation. The participation data corresponding to each target user is processed to obtain the participation characteristic value corresponding to each target user. .

[0033] By analyzing the corresponding measures to maintain the enthusiasm of each high-quality user, and obtaining the dynamic data and life data of each target user respectively, the dynamic characteristic values ​​and basic characteristic values ​​of each target user are analyzed to implement differentiated strategies for different user groups, so as to enhance the frequency and stickiness of users' application of the life service platform, realize targeted management at the characteristic level of each user, and ensure the efficient application and operation of the smart community.

[0034] It should be noted that the reference vocabulary frequency is set by professional community managers; the reference vocabulary frequency is a reference value used to determine high-frequency vocabulary.

[0035] It should be noted that the number of related persons brought about by participation refers to the number of related persons other than the target user himself, such as relatives, friends, and work partners of the target user; Data processing: Check whether there are missing values ​​in the dynamic data corresponding to each target user. If so, use the average value filling method to fill in the missing values. For example, calculate the average number of participations of all target users and use the average value to fill in the missing number of participations data. Based on the different data dimensions of the three dimensions of participation, number of related persons brought about by participation, and response speed of participation, avoid a certain dimension from having a great influence on the final result, and then standardize the data. The Z-score standardization method is used, and the calculation formula is: ,in is the original data, is the mean of the data, is the standard deviation of the data. After the normalization processing of the dynamic data corresponding to each target user is completed, its mean is 0 and the standard deviation is 1. In this way, the data processing of the dynamic data corresponding to each target user is completed. The data processing of the participation data corresponding to each target user is consistent with the data processing method of the dynamic data corresponding to each target user, so it is not repeated here.

[0036] The smart community analysis module is used to analyze the dynamic characteristic values ​​and basic characteristic values ​​corresponding to each target user, and then obtain the corresponding adjustment method and adjustment measures for each target user. It also monitors the corresponding target users after the adjustment measures are implemented, and determines the effectiveness of the adjustment measures for each target user.

[0037] As an optional implementation, the analysis obtains the corresponding trimming method for each target user. The specific analysis process is as follows: Based on the dynamic feature value corresponding to each target user and the basic eigenvalues ,when , the number will be The target users are recorded as Class I active personnel, and a first-level correction measure is adopted for each Class I active personnel.

[0038] when , the number will be The target users are recorded as Class II active personnel, and secondary remedial measures are adopted for each Class II active personnel.

[0039] when , the number will be The target users are classified into three categories of active personnel, and three-level repair measures are adopted for each category of active personnel.

[0040] As an optional implementation method, the analysis obtains the corresponding correction measures for each target user. The specific analysis process is as follows: when a target user is a type of active person, it is determined that the target user is a user who likes activities and is keen to participate, then the relevant announcement activities of the target user's corresponding target point are published on the corresponding announcement terminal and neighborhood social terminal of the community, and the relevant information is pushed to the target user in real time. At the same time, the relevant announcement is set with a title related to the target point and the content of the announcement activity, the associated benefits of the target point and timely payment, so as to serve as a correction measure when the target user is a type of active person.

[0041] When a target user is a Category 2 active person, it is determined that the target user is either a person who likes to watch activities or a person who is keen on participating in activities. Then, when a relevant activity is held in the community, a relevant announcement article is sent to the target user of this category, and an activity reward is set in the announcement article for the target user of this category after the preset payment period is reached. When the target user of this category reaches the preset payment period, the target user can enjoy free tickets to watch the activity or discounts on the activity content, thereby obtaining a correction measure when the target user is a Category 2 active person; When a target user is a Category 3 active person, the target user is determined to be a low-activity user. The list of delinquent persons is published on the community announcement terminal, and multi-level push notifications are sent to this type of target user through mini-programs and text messages at regular intervals and locations. At the same time, relevant personnel are arranged for offline door-to-door communication and relevant restrictive measures are taken to obtain the correction measures when the target user is a Category 3 active person. The corresponding correction measures for each target user are obtained by combining the above.

[0042] It should be noted that the corrective measures for the first type of active personnel: the associated benefits of the announced activity content target point and timely payment may include that if the target user completes the payment immediately or before the deadline within the time of the payment announcement, when the society holds relevant activities, the user can directly participate in the relevant activities without subsequent selection and screening, and based on the user's previous performance in activities, the user's relevant responsible position can be arranged; the corrective measures for the second type of active personnel: free gifting of relevant parent-child tickets or e-commerce shopping coupons can also be set up; the corrective measures for the third type of active personnel: relevant restrictive measures are taken: if the user immediately pays the relevant fees after offline communication, the life restrictions of the target user will not be temporarily taken; if the user has not paid within a short time after offline communication, the user's corresponding online purchase will be restricted or the deposit for borrowing items will be increased; if the user has not paid within a long time after offline communication, the user's basic rights in life services will be restricted, including not providing repair services or free cleaning services; professional community management personnel set associated benefits, activity rewards and restrictive measures to solve the problem of overdue or unpaid property fees for each target personnel.

[0043] As an optional implementation method, the effectiveness of the rectification measures corresponding to each target user is judged, and the specific judgment process is as follows: by presetting a reference payment period, and then obtaining the payment time of each target user within the reference period, the payment time corresponding to each target user is compared with the reference payment time interval corresponding to the community property payment notice. If a target user has two or more payment times that are not within the reference payment time interval corresponding to the community property payment notice, then the rectification measures corresponding to the target user are judged to be invalid. If all payment times corresponding to a target user are within the reference payment time interval corresponding to the community property payment notice, or a target user has one payment time that is not within the reference payment time interval corresponding to the community property payment notice, then the rectification measures corresponding to the target user are judged to be valid, so as to judge the effectiveness of the rectification measures corresponding to each target user.

[0044] Based on the dynamic characteristic values ​​and basic characteristic values ​​corresponding to each target user, we analyze and obtain the corresponding adjustment methods and adjustment measures for each target user, monitor the corresponding target users after the implementation of the adjustment measures, judge the effectiveness of the adjustment measures corresponding to each target user, and have a more comprehensive understanding of the needs and preferences of each target user, so as to take targeted rectification measures, so as to mobilize the enthusiasm of users to pay actively in all aspects, solve the problem of payment arrears or overdue, and further improve the life service system of the smart community.

[0045] It should be noted that the reference payment period and reference payment time interval are set by professional community managers. The reference payment time interval is used as a reference value to judge the effectiveness of the corresponding remedial measures for each target user; the reference payment period refers to a preset time period, such as six months or eight months.

[0046] The database is used to store payment data, standard intervals of payment data, payment attitude assessment values, reference payment attitude assessment value threshold intervals, dynamic data, participation data, payment times and reference payment time intervals.

[0047] The early warning terminal is used to issue early warning prompts when a user's payment attitude is unsatisfactory or the corresponding correction measures for a target user are ineffective.

[0048] See also Figure 2 As shown, a smart community life service platform includes a server end, which is used to provide a community announcement end, a neighborhood social end, a community e-commerce end, and a property life payment end.

[0049] The embodiment of the present invention analyzes the payment attitude of each user in the community, and then analyzes each user at different levels based on the payment attitude, obtains the enthusiasm maintenance measures corresponding to each high-quality user and the dynamic characteristic values ​​and basic characteristic values ​​corresponding to each target user, and based on the obtained characteristic values, analyzes the corresponding adjustment methods and adjustment measures for each target user, and then judges the effectiveness of the corresponding adjustment measures for each target user, thereby realizing efficient management of the smart community, further improving the service efficiency and system of the smart community, enhancing the frequency and viscosity of users applying the life service platform, and realizing targeted management at the characteristic level of each user, so as to improve the service satisfaction of the user application experience and make the life services of the smart community more comprehensively optimized.

[0050] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A smart community life service system, characterized by: include: The community user segmentation module is used to monitor the property payment of each user in the community, obtain the corresponding payment data, and analyze the payment attitude of each user in the community. Based on the payment attitude evaluation value of each user in the community, it is further divided into high-quality users and target users; The user behavior optimization module is used to analyze the payment attitude evaluation values ​​of each high-quality user and obtain the corresponding motivation maintenance measures for each high-quality user. It also obtains the dynamic data and life data of each target user and analyzes them to obtain the dynamic feature value and basic feature value of each target user. The smart community analysis module is used to analyze the dynamic characteristic values ​​and basic characteristic values ​​corresponding to each target user, obtain the corresponding correction method for each target user, analyze the corresponding correction measures for each target user, monitor the corresponding target users after the correction measures are implemented, and judge the effectiveness of the corresponding correction measures for each target user; The early warning terminal is used to issue early warning prompts when a user's payment attitude is unsatisfactory or the corresponding correction measures for a target user are ineffective.

2. A smart community life service system according to claim 1, characterized in that: The analysis obtains the payment attitude of each user in the community. The specific analysis process is as follows: After sending payment notifications to each user through the community's corresponding life service platform, the payment data of each user in the community is monitored, including the payment cycle, delay days and communication response time, and the standard range of the corresponding user payment data during the community's historical property payment is obtained from the database, and then the payment attitude evaluation value of each user in the community is analyzed. When the payment attitude evaluation value of a user in the community is 1, the user is defined as a high-quality user, and the high-quality users are analyzed, and the enthusiasm maintenance measures corresponding to each high-quality user are analyzed. When the payment attitude evaluation value of a user in the community is -1, the user is defined as a target user, and the target users are analyzed.

3. A smart community life service system as claimed in claim 2, characterized in that: The analysis obtains the payment attitude evaluation value of each user in the community. The specific analysis process is as follows: By calculation formula: ,in For the community The payment attitude evaluation value of each user, is the ID of each user, , is any integer greater than 2, The payment data number. , 1, 2 and 3 are payment cycle, delay days and communication response time respectively, For the community Payment data of each user, The standard range of user payment data corresponding to the payment of historical properties in the community.

4. A smart community life service system as claimed in claim 3, characterized in that: The analysis obtains the corresponding motivation maintenance measures for each high-quality user. The specific analysis process is as follows: Based on the payment attitude evaluation value of each high-quality user , and preset the threshold intervals of each reference payment attitude evaluation value corresponding to the user's quality level. One threshold interval corresponds to one quality level. The quality levels include C level, B level and A level. If the payment attitude evaluation value corresponding to a quality user is Belongs to the threshold interval of a certain reference payment attitude evaluation value, and the quality level corresponding to the threshold interval of the reference payment attitude evaluation value is level A, then the enthusiasm maintenance measures corresponding to the quality user under level A are executed. If the payment attitude evaluation value corresponding to a quality user is Belongs to the threshold interval of a reference payment attitude evaluation value, and the quality level corresponding to the threshold interval of the reference payment attitude evaluation value is level B, then the enthusiasm maintenance measures corresponding to the B level of the quality user are executed. If the payment attitude evaluation value corresponding to a quality user is Belonging to a threshold interval of a reference payment attitude evaluation value, the quality level corresponding to the threshold interval of the reference payment attitude evaluation value is C level, then the enthusiasm maintenance measures corresponding to the C level of the high-quality user are executed, so as to obtain the enthusiasm maintenance measures corresponding to each high-quality user.

5. The smart community life service system according to claim 1, characterized in that: The analysis obtains the dynamic feature value corresponding to each target user. The specific analysis process is as follows: By monitoring the dynamic trajectory of each target user on the community life service platform, and presetting the reference word frequency, the dynamic words corresponding to each target user in the service end are extracted. When a dynamic word corresponding to a target user is greater than or equal to the preset reference word frequency, the dynamic word corresponding to the target user is recorded as a high-frequency word, and the high-frequency word is used as the target point corresponding to the target user in the platform end. In this way, the target point corresponding to each target user in the platform end is extracted; Based on the dynamic data of the target points corresponding to each target user on the community service end, including dynamic publishing frequency, dynamic group discussion frequency and dynamic announcement reading volume, the dynamic data corresponding to each target user is processed to obtain the dynamic feature value corresponding to each target user. , is the number of each target user, , is any integer greater than 2.

6. A smart community life service system as claimed in claim 5, characterized in that: The analysis obtains the basic feature values ​​corresponding to each target user. The specific analysis process is as follows: Based on the target points corresponding to each user obtained by analysis, the implementation and participation of each target user in the corresponding target points are monitored. By extracting various community service activities consistent with the target point type at the community announcement terminal and the social neighborhood terminal, the participation data of each target user in each community service activity is extracted, including the number of participations, the number of related personnel driven by participation, and the response speed of participation. The participation data corresponding to each target user are processed to obtain the participation feature value corresponding to each target user. .

7. A smart community life service system according to claim 6, characterized in that: The analysis obtains the corresponding trimming method for each target user. The specific analysis process is as follows: Based on the dynamic feature values ​​corresponding to each target user and the basic eigenvalues ,when , the number will be The target users are recorded as Class I active personnel, and a first-level correction measure is adopted for each Class I active personnel; when , the number will be The target users are recorded as Class II vitality personnel, and the second-level repair measures are adopted for each Class II vitality personnel; when , the number will be The target users are classified into three categories of active personnel, and three-level repair measures are adopted for each category of active personnel.

8. A smart community life service system according to claim 7, characterized in that: The analysis obtains the corresponding correction measures for each target user. The specific analysis process is as follows: When a target user is a type of active person, it is determined that the target user is a user who likes activities and is keen to participate. Then, the relevant announcement activities of the target user's corresponding target point will be published on the corresponding announcement terminal of the community and the neighborhood social terminal respectively, and the relevant information will be pushed to the target user in real time. At the same time, the relevant announcement will be set with a title related to the target point and the content of the announcement activity, and the benefits associated with the target point and timely payment, so as to serve as a correction measure when the target user is a type of active person; When a target user is a Category 2 active person, it is determined that the target user is either a person who likes to watch activities or a person who is keen on participating in activities. Then, when a relevant activity is held in the community, a relevant announcement article is sent to the target user of this category, and an activity reward is set in the announcement article for the target user of this category after the preset payment period is reached. When the target user of this category reaches the preset payment period, the target user can enjoy free tickets to watch the activity or discounts on the activity content, thereby obtaining a correction measure when the target user is a Category 2 active person; When a target user is a Category 3 active person, the target user is determined to be a low-activity user. The list of delinquent persons is published on the community announcement terminal, and multi-level push notifications are sent to this type of target user through mini-programs and text messages at regular intervals and locations. At the same time, relevant personnel are arranged for offline door-to-door communication and relevant restrictive measures are taken to obtain the correction measures when the target user is a Category 3 active person. The corresponding correction measures for each target user are obtained by combining the above.

9. A smart community life service system according to claim 8, characterized in that: The specific process of judging the effectiveness of the corresponding correction measures for each target user is as follows: By presetting a reference payment period, we obtain the payment times of each target user within the reference period, and compare the payment times corresponding to each target user with the reference payment time interval corresponding to the community property payment notice. If a target user has two or more payment times that are not within the reference payment time interval corresponding to the community property payment notice, then the correction measures corresponding to the target user are determined to be invalid. If all payment times corresponding to a target user are within the reference payment time interval corresponding to the community property payment notice, or if a target user has one payment time that is not within the reference payment time interval corresponding to the community property payment notice, then the correction measures corresponding to the target user are determined to be valid, thereby judging the effectiveness of the correction measures corresponding to each target user.

10. A smart community life service platform for executing the smart community life service system according to any one of claims 1 to 9, characterized in that: It also includes a server side, which is used to provide community announcements, neighborhood social networking, community e-commerce, and property life payment.

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