A property payment data fusion processing method and system

Abstract

The present invention proposes a property payment data fusion processing method and system, which relates to the technical field of business data fusion processing, and obtains owner information and building information within the property management scope, generates a building information model, obtains owner building information and building collection information; splits the building collection information to obtain a building payment split group, integrates the building collection information of the building payment split group, and obtains business fusion data; obtains fusion collection fee information, splits it, obtains type split fees, distributes and pays, calculates payment anomaly coefficients, and then performs anomaly positioning, marking and early warning; obtains the information collection amount of the building collection information, updates the fee collection and payment according to the information collection amount, and obtains fee payment update data. The present invention realizes the accurate collection and efficient management of property fees, which not only improves the efficiency and accuracy of property management, but also enhances the intelligence and transparency of fee collection.

Description

Technical Field

[0001] The present invention proposes a property payment data fusion processing method and system, and relates to the technical field of business data fusion processing. Background Art

[0002] In the existing property management system, the collection and payment process of property fees often relies on traditional manual operations and paper records, which is not only inefficient but also prone to errors, resulting in untimely and inaccurate fee collection, and even causing disputes between owners and property management parties. In addition, with the expansion of the scope of property management and the increase in the complexity of building information, traditional management methods can no longer meet the needs of modern property management. Existing technologies make it difficult to intelligently allocate and pay fees to owners and identify anomalies, and it is difficult to update information in real time. Summary of the invention

[0003] The present invention provides a method and system for fusion processing of property payment data, which is used to solve the problems of traditional manual operation and paper records, which are not only inefficient but also prone to errors, resulting in untimely and inaccurate fee collection, and even causing disputes between owners and property management parties. In addition, with the expansion of the scope of property management and the increase in the complexity of building information, traditional management methods have been unable to meet the needs of modern property management. Existing technologies are difficult to intelligently allocate and pay the fees to be paid by owners, identify abnormalities, and update information in real time.

[0004] The present invention proposes a method and system for fusion processing of property fee payment data, the method comprising:

[0005] S1. Obtain owner information and building information within the property management scope, generate a building information model, locate the owner's building, obtain the owner's building information, collect the owner's pending payment information, and obtain building collection information;

[0006] S2. Split the building collection information to obtain a building payment split group, and integrate the building collection information of the building payment split group to obtain business integration data;

[0007] S3. Obtain fusion fee information based on business fusion data, split the fusion fee information, obtain the fee split by category, distribute and pay, calculate the payment abnormality coefficient, compare the abnormal situation, and then perform abnormal location marking and warning;

[0008] S4. Obtain the amount of information collected of the building information, update fee collection and payment according to the amount of information collected, and obtain fee payment update data.

[0009] Furthermore, the S1 includes:

[0010] Obtain property management scope information, and determine the owner information within the scope based on the property management scope;

[0011] Obtain building information within the property management scope and generate a building information model based on the building information;

[0012] Locate the owner's building in the building information model according to the owner's information to obtain the owner's location information;

[0013] Obtain the owner's building information based on the owner's location information;

[0014] The owner's information on fees to be paid is collected based on the owner's building information to obtain building collection information.

[0015] Further, the S2 includes:

[0016] Preprocessing the building collection information to obtain preprocessed building collection information;

[0017] Obtaining preset payment types, splitting the preprocessed building collection information according to the preset payment types, and obtaining building payment splitting groups of multiple preset payment types;

[0018] Obtain the building collection information of each building payment split group, integrate all building collection information, and obtain business integration data.

[0019] Further, the S3 includes:

[0020] Comprehensively collect property fees based on business integration data to obtain integrated fee information;

[0021] Split the integrated fee information according to the preset payment types of the building payment split group to obtain the type split fee of each preset payment type;

[0022] Pay the fees for the building payment split groups corresponding to the preset payment categories by splitting the fees by category, and obtain the fee payment data for each building payment split group;

[0023] Calculate the payment anomaly coefficient based on the building collection information, integrated collection information and fee payment data;

[0024] Compare the payment anomaly coefficient with the preset anomaly threshold to obtain a payment anomaly comparison result;

[0025] Based on the payment anomaly comparison results, the payment process is identified for anomalies, anomaly location marking and warning are performed, and abnormal payment update processing is performed.

[0026] Further, the S4 includes:

[0027] Collect building information according to a preset collection cycle to obtain information collection volume;

[0028] Compare the information collection amount with a preset collection amount threshold to obtain a collection amount comparison result;

[0029] The property fees are re-collected and paid based on the comparison results of the collected quantities to obtain updated fee payment data.

[0030] Furthermore, the system comprises:

[0031] The building collection module is used to obtain the owner information and building information within the property management scope, generate a building information model, locate the owner's building, obtain the owner's building information, collect the owner's pending payment information, and obtain building collection information;

[0032] The payment splitting and integration module is used to split the building collection information to obtain the building payment splitting group, integrate the building collection information of the building payment splitting group, and obtain business integration data;

[0033] The payment integration and splitting module is used to obtain integrated fee information based on business integration data, split the integrated fee information, obtain the split fees by category, distribute the payment, calculate the payment anomaly coefficient, compare the anomaly situation, and then perform anomaly location marking and warning;

[0034] The collection and update module is used to obtain the information collection volume of the building collection information, update the fee collection and payment according to the information collection volume, and obtain the fee payment update data.

[0035] Furthermore, the building collection module includes:

[0036] The owner information collection module is used to obtain the property management scope information and determine the owner information within the scope according to the property management scope;

[0037] The owner's building positioning module is used to obtain building information within the property management scope and generate a building information model based on the building information;

[0038] Locate the owner's building in the building information model according to the owner's information to obtain the owner's location information;

[0039] The owner's building payment collection module is used to obtain the owner's building information based on the owner's location information;

[0040] The owner's information on fees to be paid is collected based on the owner's building information to obtain building collection information.

[0041] Furthermore, the payment splitting and integration module includes:

[0042] The collected information splitting module is used to pre-process the building collected information to obtain the pre-processed building collected information;

[0043] Obtaining preset payment types, splitting the preprocessed building collection information according to the preset payment types, and obtaining building payment splitting groups of multiple preset payment types;

[0044] The module for integrating information to be paid is used to obtain the building collection information of each building payment split group, integrate all building collection information, and obtain business integration data.

[0045] Furthermore, the payment integration and splitting module includes:

[0046] The fusion and splitting module is used to collect property fees in a comprehensive manner based on the business fusion data and obtain fusion collection fee information;

[0047] Split the integrated fee information according to the preset payment types of the building payment split group to obtain the type split fee of each preset payment type;

[0048] The split payment module is used to pay the building payment split group corresponding to the preset payment type by splitting the fee by type, and obtain the fee payment data of each type of building payment split group;

[0049] The abnormal calculation and comparison module is used to calculate the payment abnormality coefficient based on the building collection information, the integrated collection information and the fee payment data;

[0050] Compare the payment anomaly coefficient with the preset anomaly threshold to obtain a payment anomaly comparison result;

[0051] The abnormal warning processing module is used to identify abnormalities in the payment process according to the payment abnormality comparison results, and to locate and mark abnormalities and issue warnings, and to perform abnormal payment update processing.

[0052] Furthermore, the acquisition and update module includes:

[0053] A periodic collection module is used to collect building information according to a preset collection period to obtain information collection volume;

[0054] A collection comparison module is used to compare the information collection amount with a preset collection amount threshold to obtain a collection amount comparison result;

[0055] The data update module is used to re-collect and pay the property fees based on the collection volume comparison results and obtain fee payment update data.

[0056] Beneficial effects of the present invention: Through automated and digital management methods, human intervention is reduced, and the efficiency and accuracy of property management are improved. Based on BIM models and real-time data, optimal allocation and scheduling of resources are achieved, and resource utilization is improved. Through timely monitoring and early warning, problems are discovered and solved in a timely manner, and the satisfaction and trust of owners are improved. By reducing manpower input and avoiding waste of resources, the operating costs of property management are reduced. Comprehensive and accurate data support is provided to provide a strong basis for the decision-making of property companies. This solution realizes the intelligent, refined and efficient property management through the comprehensive use of modern information technology and management strategies, providing owners with a better quality and more convenient service experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 It is a schematic diagram of a method for fusion processing of property payment data;

[0058] Figure 2 It is a schematic diagram of information location;

[0059] Figure 3 This is a diagram of the payment process. DETAILED DESCRIPTION

[0060] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0061] One embodiment of the present invention provides a method and system for fusion processing of property fee payment data, the method comprising:

[0062] S1. Obtain owner information and building information within the property management scope, generate a building information model, locate the owner's building, obtain the owner's building information, collect the owner's pending payment information, and obtain building collection information;

[0063] S2. Split the building collection information to obtain a building payment split group, and integrate the building collection information of the building payment split group to obtain business integration data;

[0064] S3. Obtain fusion fee information based on business fusion data, split the fusion fee information, obtain the fee split by category, distribute and pay, calculate the payment abnormality coefficient, compare the abnormal situation, and then perform abnormal location marking and warning;

[0065] S4. Obtain the amount of information collected of the building collection information, update the fee collection and payment according to the amount of information collected, and obtain the fee payment update data, such as Figure 1 shown.

[0066] The working principle of the above technical solution is: through the community property information management system, computer network technology is used to collect the basic information of the owner (such as name, contact information, address, etc.) and building information (such as building location, structure, area, etc.). The collected building information is integrated into a unified three-dimensional model to achieve comprehensive coordination and integrated management of building information. The building location of the owner is accurately located through information positioning technology (such as Wi-Fi positioning, Bluetooth positioning, etc.) or combined with BIM model. Real-time data inside the building, such as indicator data of various fees, are collected using Internet of Things technology, sensors and other equipment. The owner's pending payment information, including property fees, water and electricity fees, etc., is recorded through the system. The building collection information is split to form a building payment split group, and this information is integrated to obtain business fusion data. These data are used for subsequent fee calculation and allocation. The fusion collection fee information is obtained according to the business fusion data, and the category is split, and finally the fee is allocated and paid. The payment abnormality coefficient is calculated, and by comparing with the preset threshold, it is identified whether there is an abnormal situation. The abnormal situation is located and marked, and an early warning signal is issued so that measures can be taken to solve the problem in time. According to the amount of information collected by the building collection information, the rules for fee collection and payment are dynamically adjusted. According to the new information collection volume and fee rules, the fee payment data is updated to ensure the accuracy and timeliness of the fees. The present invention processes information in multiple scenarios such as owner and building information management, fee collection and management, data update and maintenance, multi-terminal and multi-channel interaction, report analysis and decision support, making property management more intelligent and more scalable.

[0067] The technical effects of the above technical solutions are: through automated and digital management methods, reduce manual intervention and improve the efficiency and accuracy of property management. Based on BIM models and real-time data, realize the optimal allocation and scheduling of resources and improve resource utilization. Through timely monitoring and early warning, timely discover and solve problems, and improve the satisfaction and trust of owners. Reduce the operating costs of property management by reducing manpower input and avoiding waste of resources. Provide comprehensive and accurate data support to provide a strong basis for the decision-making of property companies. This solution realizes the intelligent, refined and efficient property management through the comprehensive use of modern information technology and management strategies, providing owners with a better quality and more convenient service experience. This method can realize the precise positioning of owner data and intelligent data collection, realize comprehensive data payment, and the system implements accurate allocation of payment, abnormal judgment, and automatic update of payment data.

[0068] In one embodiment of the present invention, the S1 includes:

[0069] Obtain property management scope information, and determine the owner information within the scope based on the property management scope;

[0070] Obtain building information within the property management scope and generate a building information model based on the building information;

[0071] Locate the owner's building in the building information model according to the owner's information to obtain the owner's location information;

[0072] Obtain the owner's building information based on the owner's location information;

[0073] According to the owner's building information, the owner's pending payment information is collected to obtain building collection information, such as Figure 2 At this time, the building collection information is a mixed collection of information to be paid by the owner, and there is no clear category.

[0074] The working principle of the above technical solution is as follows: the property management system first obtains clear property management scope information through geographic information system (GIS) or database query, which usually includes geographic coordinates, boundary lines, etc. According to the property management scope information, the system determines and obtains the basic information of all owners within the scope, such as name, contact information, residential address, etc., through database query or docking with other relevant systems (such as owner information system). The system further collects building information within the property management scope, including building location, structure, floor, room number, etc. Using building information modeling (BIM) technology or three-dimensional modeling technology, these building information are converted into a three-dimensional model or digital model, namely a building information model (BIM model). The model can intuitively display the physical structure and spatial layout of the building. According to the owner information and the building information model, the system accurately locates the living space of each owner in the building information model through algorithm matching or spatial analysis technology, and generates owner positioning information. Based on the owner positioning information, the system can further obtain detailed building information related to the owner's living space, such as room area, orientation, facilities, etc. Based on the owner's building information, the system can identify the type of fees (such as property fees, water and electricity fees, maintenance funds, etc.) and the amount that each owner should pay. Through database query, IoT sensor data collection (such as electricity meter and water meter readings) or docking with other financial systems, the system collects mixed data of the owner's pending payment information. These data have not been clearly classified or split at this time (to improve data collection efficiency), but they already contain all the fee information that needs to be paid.

[0075] The technical effects of the above technical solutions are as follows: through the establishment of a building information model, accurate management and positioning of buildings within the scope of property management are achieved, and the precision and accuracy of management are improved. Based on the building information model and the owner's location information, the system can more reasonably obtain the information to be paid, allocate and dispatch resources, such as maintenance personnel, cleaning personnel, etc., to improve the efficiency of resource utilization. The automated and digital information collection method reduces manual intervention and error rates, and improves the efficiency of fee collection and management. Integrating data from multiple sources (such as owner information, building information, payment information, etc.) into the same platform realizes centralized management and sharing of data, providing strong support for subsequent data analysis and decision-making. By obtaining detailed owner building information and information to be paid, the system can provide owners with more personalized and accurate services, such as customized payment reminders, preferential policy push, etc.

[0076] In one embodiment of the present invention, S2 includes:

[0077] Preprocessing the building collection information to obtain preprocessed building collection information;

[0078] Obtaining preset payment types, splitting the preprocessed building collection information according to the preset payment types, and obtaining building payment splitting groups of multiple preset payment types;

[0079] Obtain the building collection information of each building payment split group (i.e. the owner's pending payment information), integrate all building collection information, and obtain business integration data. By splitting the collected complex pending payment data, you can obtain clear pending payment data for each payment type. The integration is to facilitate the owner to make a one-time comprehensive payment, save the payment process and complexity, and then save time. Then, the system can accurately allocate payment for each pending payment data, realizing flexible and intelligent payment.

[0080] The working principle of the above technical solution is as follows: First, the building collection information collected from various channels (such as databases, IoT sensors, etc.) is cleaned, deduplicated, and formatted in a unified manner to ensure the accuracy and consistency of the data. The preprocessing step may also include data missing value processing, outlier detection and processing, etc. to further improve the data quality. The system maintains a preset list of payment types, which are usually determined according to property management regulations and owner needs, such as property fees, water and electricity fees, parking fees, maintenance funds, etc. According to this preset payment type list, the preprocessed building collection information is split, and each payment record is classified into the corresponding payment type to form multiple building payment split groups. Within each building payment split group, the building collection information belonging to the same payment type is integrated to form a set of data to be paid for that type. Then, the data sets to be paid for all payment types are aggregated to generate business fusion data. This process ensures the logical unity and integrity of the data and facilitates subsequent payment processing. Splitting complex data to be paid can clearly display the specific amount and details of each payment type, allowing owners to understand their payment status more intuitively. The integrated business fusion data facilitates owners to make a one-time comprehensive payment, reduces the cumbersome process of multiple payments, and saves time. The system can accurately allocate payment for each type of data to be paid based on business fusion data, automatically complete the calculation, verification and deduction of fees, and realize flexible and intelligent payment.

[0081] The technical effects of the above technical solutions are as follows: through the preprocessing steps, the data quality of building collection information is effectively improved, laying a solid foundation for subsequent data analysis and processing. The complex data to be paid is split into clear payment types and integrated into business integration data, which greatly simplifies the payment process and improves payment efficiency. The one-time comprehensive payment and clear display of payment types have improved the owner's payment experience and enhanced the owner's satisfaction and trust in property management. The system can automatically complete the calculation, verification and deduction of fees, reducing manual intervention and improving the intelligent level of property management. Business integration data provides strong support for the decision-making of property companies, helping companies to better understand the needs of owners and market changes, and formulate more scientific and reasonable management strategies.

[0082] In one embodiment of the present invention, S3 includes:

[0083] Comprehensively collect property fees based on business integration data to obtain integrated fee information;

[0084] Split the integrated fee information according to the preset payment types of the building payment split group to obtain the type split fee of each preset payment type;

[0085] By splitting the fees by category, the fees are paid for the building payment split groups corresponding to the preset payment categories, and the fee payment data of each type of building payment split group is obtained, such as Figure 3 shown.

[0086] Calculate the payment anomaly coefficient based on the building collection information, integrated collection information and fee payment data;

[0087] The calculation formula for the payment abnormality coefficient is:

[0088]

[0089] Among them, Y jnxs To pay the abnormal coefficient, R sq To integrate the fee collection information, Z is the number of preset payment types, F jni The payment data for the i-th type of building payment split group, F ci Collect building information for the i-th type of building payment split group (i.e., information on owner payment to be made).

[0090] Compare the payment anomaly coefficient with the preset anomaly threshold to obtain a payment anomaly comparison result;

[0091] When the payment abnormality coefficient is greater than the preset abnormality threshold, the payment process is identified as abnormal, otherwise, no abnormality is identified.

[0092] Based on the payment anomaly comparison results, the payment process is identified for anomalies, anomaly location marking and warning are performed, and abnormal payment updates are performed (payment recalculation is performed, excess amounts are refunded and shortages are supplemented).

[0093] The working principle of the above technical solution is: the system performs the comprehensive collection operation of property fees according to the business integration data (i.e. the integrated information to be paid), and generates integrated collection fee information. This process may involve communication confirmation with the owner, electronic payment or bank transfer and other methods. The integrated collection fee information is split according to the previously established building payment split group and its corresponding preset payment type, ensuring that the fees of each payment type are accurately allocated to the corresponding building payment split group. In this way, each payment type corresponds to a set of specific fee data. For each preset payment type, the system splits the fees according to the split type and pays the fees to the corresponding building payment split group. This step may include the transfer of funds, the update of financial records, etc. After the payment is completed, the system will generate the fee payment data of each type of building payment split group for subsequent verification and audit. In order to monitor the abnormal situations that may occur during the payment process (such as wrong payment, missed payment, etc.), the system calculates the payment abnormality coefficient based on the building collection information (such as the actual amount payable), the integrated collection information (such as the actual amount collected) and the fee payment data (such as the actual amount paid). This coefficient reflects the degree of deviation between the actual payment and the payable situation. The calculated payment anomaly coefficient is compared with the preset anomaly threshold. If the payment anomaly coefficient is greater than the preset threshold, it is considered that there is an anomaly in the payment process, and the system will identify the anomaly, and perform an abnormal location mark and warning. This helps to quickly locate the problem and take appropriate measures. If the payment anomaly coefficient does not exceed the preset threshold, the payment process is considered normal and no anomaly identification is performed. For the identified abnormal payment situation, the system performs abnormal payment update processing. This usually includes recalculating the payment to ensure the accuracy of the fees; for overpayment or underpayment, the corresponding refund or supplementary payment operation is performed to achieve "more refund and less supplement".

[0094] The technical effect of the above technical solution is: through the comprehensive collection, splitting and payment process, it ensures that the fees of each payment type are collected and allocated accurately and timely, reducing the occurrence of wrong payment, missed payment and other problems. The real-time update and display of business integration data and fee payment data improves the transparency of fee management, allowing owners to clearly understand their payment situation. Through the calculation of the payment abnormality coefficient and the abnormality identification mechanism, the system can promptly detect and handle abnormal situations in the payment process, reducing losses and disputes caused by abnormal situations. and Calculate the difference between the integrated fee collection information and the comprehensive fee payment data of all types of building payment split groups, the difference between the fee payment data of all types of building payment split groups and the building collection information (i.e. the owner's payment information) of all types of building payment split groups. The larger the difference, the higher the abnormality coefficient. When the abnormality coefficient is zero, it means that there is no abnormality in the payment. Abnormal payment update processing (such as over-refund and under-supplement) ensures that the interests of the owners are not harmed and improves the user's satisfaction and trust in property management services. The automated fee collection, splitting, payment and exception handling process reduces manual intervention and the use of paper documents, and improves the efficiency and digital level of property management.

[0095] In one embodiment of the present invention, the S4 includes:

[0096] Collect building information according to a preset collection cycle to obtain information collection volume;

[0097] Compare the information collection amount with a preset collection amount threshold to obtain a collection amount comparison result;

[0098] The property fees are re-collected and paid based on the comparison results of the collected quantities to obtain updated fee payment data.

[0099] When the amount of information collected is greater than the preset collection amount threshold, the property fees will be collected and paid again, otherwise, they will not be collected and paid again.

[0100] Calculate the dynamic adjustment coefficient of the collection cycle based on the amount of information collected, the preset collection cycle and the historical payment abnormal coefficient information;

[0101] The calculation formula of the acquisition cycle dynamic adjustment coefficient is:

[0102]

[0103] Among them, D cq is the dynamic adjustment coefficient of the acquisition cycle, Z yq is the preset collection cycle days, L xc is the current accumulated amount of information collected, L yc is the preset collection volume threshold;

[0104] Compare the acquisition cycle dynamic adjustment coefficient with a preset adjustment threshold to obtain an adjustment comparison result;

[0105] When the dynamic adjustment coefficient of the acquisition cycle is greater than the preset adjustment threshold, the acquisition cycle is adjusted to a shorter value. cq ;

[0106] On the contrary, adjust D cq ;

[0107] The preset acquisition period is dynamically adjusted according to the adjustment comparison result to obtain a dynamic adjustment result.

[0108] The working principle of the above technical solution is: the system automatically collects building information according to a preset collection cycle (such as daily, weekly or monthly). This collected information may include but is not limited to the use of facilities in the building, energy consumption data, security monitoring records, etc., depending on the needs and goals of property management. The system compares the collected information collection volume (i.e. the actual amount of data collected or the number of information points) with the preset collection volume threshold. This threshold is used to determine whether the current information collection volume has reached the standard that requires re-evaluation or adjustment of property fees. According to the collection volume comparison result, the system performs corresponding operations. If the information collection volume is greater than the preset collection volume threshold, it means that the use of facilities in the building, energy consumption or other related factors have changed significantly, and the property fees may need to be adjusted to reflect these changes. At this time, the system will trigger the re-collection and payment process of the property fees, including recalculating fees, generating new payment notices, updating financial records, etc., and generating fee payment update data for subsequent verification and auditing. If the information collection volume does not exceed the preset collection volume threshold, it is considered that the current property fee level is reasonable and there is no need to re-collect and pay. The monitoring function of data accuracy and periodic update is guaranteed. The system first collects information according to the preset collection cycle. As time goes by, the system accumulates the amount of information collected, which reflects the amount of data collected by the system within a certain period of time. Calculate the dynamic adjustment coefficient of the collection cycle. This coefficient is determined based on the relationship between the current accumulated information collection amount (Lxc) and the preset collection amount threshold (Lyc). The influence coefficient of the periodic adjustment amount on the accumulated information amount and the payment abnormality coefficient can be calculated. or The larger the value is, the larger the dynamic adjustment coefficient of the collection cycle is, and the shorter the collection cycle is adjusted. The calculated dynamic adjustment coefficient of the collection cycle (Dcq) is compared with the preset adjustment threshold. Based on the comparison result, the system decides whether the preset collection cycle needs to be adjusted. If Dcq exceeds the threshold, the system will shorten the collection cycle accordingly, otherwise it will be extended. Through the above steps, the system dynamically adjusts the collection cycle to adapt to different data collection requirements and external environment changes.

[0109] The technical effect of the above technical solution is that by regularly collecting building information and comparing it with the preset threshold, the system can dynamically evaluate the rationality of property fees and adjust them according to the actual situation. This helps to ensure that the property fees are consistent with the actual use of the building, avoiding the problem of excessive or low fees that may be caused by the fixed fee model. The mechanism allows the property manager to flexibly adjust the fees based on factors such as the use of facilities in the building, changes in energy consumption and periodic changes, thereby improving the flexibility and adaptability of fee management. This helps to better meet the needs of owners and improve the overall level of property management services. The decision-making process of re-collecting and paying fees is based on the actual collected data and the preset threshold, which enhances the transparency and fairness of fee collection. Owners can clearly understand the reasons and basis for fee adjustments, thereby enhancing their trust in property management services. By regularly collecting building information, property managers can promptly discover problems such as abnormal energy consumption or improper use of facilities, and take corresponding measures to optimize them. This helps to reduce energy consumption, improve resource utilization efficiency, and bring long-term economic benefits to property management. The entire process is automated, reducing manual intervention and the use of paper documents, and improving the efficiency and digitalization of property management. At the same time, the real-time generation and display of fee payment update data provides property managers with convenient verification and auditing tools, further improving work efficiency.

[0110] In one embodiment of the present invention, the system comprises:

[0111] The building collection module is used to obtain the owner information and building information within the property management scope, generate a building information model, locate the owner's building, obtain the owner's building information, collect the owner's pending payment information, and obtain building collection information;

[0112] The payment splitting and integration module is used to split the building collection information to obtain the building payment splitting group, integrate the building collection information of the building payment splitting group, and obtain business integration data;

[0113] The payment integration and splitting module is used to obtain integrated fee information based on business integration data, split the integrated fee information, obtain the split fees by category, distribute the payment, calculate the payment anomaly coefficient, compare the anomaly situation, and then perform anomaly location marking and warning;

[0114] The collection and update module is used to obtain the information collection volume of the building collection information, update the fee collection and payment according to the information collection volume, and obtain the fee payment update data.

[0115] The working principle of the above technical solution is: through the community property information management system, computer network technology is used to collect the basic information of the owner (such as name, contact information, address, etc.) and building information (such as building location, structure, area, etc.). The collected building information is integrated into a unified three-dimensional model to achieve comprehensive coordination and integrated management of building information. The building location of the owner is accurately located through information positioning technology (such as Wi-Fi positioning, Bluetooth positioning, etc.) or combined with BIM model. Real-time data inside the building, such as indicator data of various fees, are collected using Internet of Things technology, sensors and other equipment. The owner's pending payment information, including property fees, water and electricity fees, etc., is recorded through the system. The building collection information is split to form a building payment split group, and this information is integrated to obtain business fusion data. These data are used for subsequent fee calculation and allocation. The fusion collection fee information is obtained according to the business fusion data, and the category is split, and finally the fee is allocated and paid. The payment abnormality coefficient is calculated, and by comparing with the preset threshold, it is identified whether there is an abnormal situation. The abnormal situation is located and marked, and an early warning signal is issued so that measures can be taken to solve the problem in time. According to the amount of information collected by the building collection information, the rules for fee collection and payment are dynamically adjusted. Update fee payment data based on new information collection volumes and fee rules to ensure accuracy and timeliness of fees.

[0116] The technical effects of the above technical solutions are: through automated and digital management methods, reduce manual intervention and improve the efficiency and accuracy of property management. Based on BIM models and real-time data, realize the optimal allocation and scheduling of resources and improve resource utilization. Through timely monitoring and early warning, timely discover and solve problems, and improve the satisfaction and trust of owners. Reduce the operating costs of property management by reducing manpower input and avoiding waste of resources. Provide comprehensive and accurate data support to provide a strong basis for the decision-making of property companies. This solution realizes the intelligent, refined and efficient property management through the comprehensive use of modern information technology and management strategies, providing owners with a better quality and more convenient service experience. This method can realize the precise positioning of owner data and intelligent data collection, realize comprehensive data payment, and the system implements accurate allocation of payment, abnormal judgment, and automatic update of payment data.

[0117] In one embodiment of the present invention, the building collection module includes:

[0118] The owner information collection module is used to obtain the property management scope information and determine the owner information within the scope according to the property management scope;

[0119] The owner's building positioning module is used to obtain building information within the property management scope and generate a building information model based on the building information;

[0120] Locate the owner's building in the building information model according to the owner's information to obtain the owner's location information;

[0121] The owner's building payment collection module is used to obtain the owner's building information based on the owner's location information;

[0122] The owner's pending payment information is collected according to the owner's building information to obtain building collection information. At this time, the building collection information is a mixed collection data of the owner's pending payment information, and there is no clear category.

[0123] The working principle of the above technical solution is as follows: the property management system first obtains clear property management scope information through geographic information system (GIS) or database query, which usually includes geographic coordinates, boundary lines, etc. According to the property management scope information, the system determines and obtains the basic information of all owners within the scope, such as name, contact information, residential address, etc., through database query or docking with other relevant systems (such as owner information system). The system further collects building information within the property management scope, including building location, structure, floor, room number, etc. Using building information modeling (BIM) technology or three-dimensional modeling technology, these building information are converted into a three-dimensional model or digital model, namely a building information model (BIM model). The model can intuitively display the physical structure and spatial layout of the building. According to the owner information and the building information model, the system accurately locates the living space of each owner in the building information model through algorithm matching or spatial analysis technology, and generates owner positioning information. Based on the owner positioning information, the system can further obtain detailed building information related to the owner's living space, such as room area, orientation, facilities, etc. Based on the owner's building information, the system can identify the type of fees (such as property fees, water and electricity fees, maintenance funds, etc.) and the amount that each owner should pay. Through database query, IoT sensor data collection (such as electricity meter and water meter readings) or docking with other financial systems, the system collects mixed data of the owner's pending payment information. These data have not been clearly classified or split at this time (to improve data collection efficiency), but they already contain all the fee information that needs to be paid.

[0124] The technical effects of the above technical solutions are as follows: through the establishment of a building information model, accurate management and positioning of buildings within the scope of property management are achieved, and the precision and accuracy of management are improved. Based on the building information model and the owner's location information, the system can more reasonably obtain the information to be paid, allocate and dispatch resources, such as maintenance personnel, cleaning personnel, etc., to improve the efficiency of resource utilization. The automated and digital information collection method reduces manual intervention and error rates, and improves the efficiency of fee collection and management. Integrating data from multiple sources (such as owner information, building information, payment information, etc.) into the same platform realizes centralized management and sharing of data, providing strong support for subsequent data analysis and decision-making. By obtaining detailed owner building information and information to be paid, the system can provide owners with more personalized and accurate services, such as customized payment reminders, preferential policy push, etc.

[0125] In one embodiment of the present invention, the payment splitting and integration module includes:

[0126] The collected information splitting module is used to pre-process the building collected information to obtain the pre-processed building collected information;

[0127] Obtaining preset payment types, splitting the preprocessed building collection information according to the preset payment types, and obtaining building payment splitting groups of multiple preset payment types;

[0128] The module for integrating information to be paid is used to obtain the building collection information (i.e. the information to be paid by the owner) of each building payment split group, integrate all the building collection information, and obtain business integration data. By splitting the collected complex data to be paid, clear data to be paid for each payment type can be obtained. The purpose of integration is to facilitate the owner to make a one-time comprehensive payment, save the payment process and complexity, and thus save time. Then, the system can accurately allocate payment for each type of data to be paid, and realize flexible and intelligent payment.

[0129] The working principle of the above technical solution is as follows: First, the building collection information collected from various channels (such as databases, IoT sensors, etc.) is cleaned, deduplicated, and formatted in a unified manner to ensure the accuracy and consistency of the data. The preprocessing step may also include data missing value processing, outlier detection and processing, etc. to further improve the data quality. The system maintains a preset list of payment types, which are usually determined according to property management regulations and owner needs, such as property fees, water and electricity fees, parking fees, maintenance funds, etc. According to this preset payment type list, the preprocessed building collection information is split, and each payment record is classified into the corresponding payment type to form multiple building payment split groups. Within each building payment split group, the building collection information belonging to the same payment type is integrated to form a set of data to be paid for that type. Then, the data sets to be paid for all payment types are aggregated to generate business fusion data. This process ensures the logical unity and integrity of the data and facilitates subsequent payment processing. Splitting complex data to be paid can clearly display the specific amount and details of each payment type, allowing owners to understand their payment status more intuitively. The integrated business fusion data facilitates owners to make a one-time comprehensive payment, reduces the cumbersome process of multiple payments, and saves time. The system can accurately allocate payment for each type of data to be paid based on business fusion data, automatically complete the calculation, verification and deduction of fees, and realize flexible and intelligent payment.

[0130] The technical effects of the above technical solutions are as follows: through the preprocessing steps, the data quality of building collection information is effectively improved, laying a solid foundation for subsequent data analysis and processing. The complex data to be paid is split into clear payment types and integrated into business integration data, which greatly simplifies the payment process and improves payment efficiency. The one-time comprehensive payment and clear display of payment types have improved the owner's payment experience and enhanced the owner's satisfaction and trust in property management. The system can automatically complete the calculation, verification and deduction of fees, reducing manual intervention and improving the intelligent level of property management. Business integration data provides strong support for the decision-making of property companies, helping companies to better understand the needs of owners and market changes, and formulate more scientific and reasonable management strategies.

[0131] In one embodiment of the present invention, the payment integration and splitting module includes:

[0132] The fusion and splitting module is used to collect property fees in a comprehensive manner based on the business fusion data and obtain fusion collection fee information;

[0133] Split the integrated fee information according to the preset payment types of the building payment split group to obtain the type split fee of each preset payment type;

[0134] The split payment module is used to pay the building payment split group corresponding to the preset payment type by splitting the fee by type, and obtain the fee payment data of each type of building payment split group;

[0135] The abnormal calculation and comparison module is used to calculate the payment abnormality coefficient based on the building collection information, the integrated collection information and the fee payment data;

[0136] The calculation formula for the payment abnormality coefficient is:

[0137]

[0138] Among them, Y jnxs To pay the abnormal coefficient, R sq To integrate the fee collection information, Z is the number of preset payment types, F jni The payment data for the i-th type of building payment split group, F ci Collect building information for the i-th type of building payment split group (i.e., information on owner payment to be made).

[0139] Compare the payment anomaly coefficient with the preset anomaly threshold to obtain a payment anomaly comparison result;

[0140] When the payment abnormality coefficient is greater than the preset abnormality threshold, the payment process is identified as abnormal, otherwise, no abnormality is identified.

[0141] The abnormal warning processing module is used to identify abnormalities in the payment process according to the payment abnormality comparison results, and to locate and mark the abnormalities and issue warnings, and to perform abnormal payment update processing (recalculate the payment, refund the excess and supplement the shortage).

[0142] The working principle of the above technical solution is: the system performs the comprehensive collection operation of property fees according to the business integration data (i.e. the integrated information to be paid), and generates integrated collection fee information. This process may involve communication confirmation with the owner, electronic payment or bank transfer and other methods. The integrated collection fee information is split according to the previously established building payment split group and its corresponding preset payment type, ensuring that the fees of each payment type are accurately allocated to the corresponding building payment split group. In this way, each payment type corresponds to a set of specific fee data. For each preset payment type, the system splits the fees according to the split type and pays the fees to the corresponding building payment split group. This step may include the transfer of funds, the update of financial records, etc. After the payment is completed, the system will generate the fee payment data of each type of building payment split group for subsequent verification and audit. In order to monitor the abnormal situations that may occur during the payment process (such as wrong payment, missed payment, etc.), the system calculates the payment abnormality coefficient based on the building collection information (such as the actual amount payable), the integrated collection information (such as the actual amount collected) and the fee payment data (such as the actual amount paid). This coefficient reflects the degree of deviation between the actual payment and the payable situation. The calculated payment anomaly coefficient is compared with the preset anomaly threshold. If the payment anomaly coefficient is greater than the preset threshold, it is considered that there is an anomaly in the payment process, and the system will identify the anomaly, and perform an abnormal location mark and warning. This helps to quickly locate the problem and take appropriate measures. If the payment anomaly coefficient does not exceed the preset threshold, the payment process is considered normal and no anomaly identification is performed. For the identified abnormal payment situation, the system performs abnormal payment update processing. This usually includes recalculating the payment to ensure the accuracy of the fees; for overpayment or underpayment, the corresponding refund or supplementary payment operation is performed to achieve "more refund and less supplement".

[0143] The technical effect of the above technical solution is: through the comprehensive collection, splitting and payment process, it ensures that the fees of each payment type are collected and allocated accurately and timely, reducing the occurrence of problems such as wrong payment and missed payment. The real-time update and display of business integration data and fee payment data improves the transparency of fee management, allowing owners to clearly understand their payment situation. Through the calculation of payment abnormality coefficients and the abnormality identification mechanism, the system can promptly detect and handle abnormal situations in the payment process, reducing losses and disputes caused by abnormal situations. Abnormal payment update processing (such as over-refund and under-supplement) ensures that the interests of owners are not harmed and improves users' satisfaction and trust in property management services. The automated fee collection, splitting, payment and abnormality handling process reduces manual intervention and the use of paper documents, and improves the efficiency and digital level of property management.

[0144] In one embodiment of the present invention, the acquisition and update module includes:

[0145] A periodic collection module is used to collect building information according to a preset collection period to obtain information collection volume;

[0146] A collection comparison module is used to compare the information collection amount with a preset collection amount threshold to obtain a collection amount comparison result;

[0147] The data update module is used to re-collect and pay the property fees based on the collection volume comparison results and obtain fee payment update data.

[0148] When the amount of information collected is greater than the preset collection amount threshold, the property fees will be collected and paid again, otherwise, they will not be collected and paid again.

[0149] When the amount of information collected is greater than the preset collection amount threshold, the property fees will be collected and paid again, otherwise, they will not be collected and paid again.

[0150] Calculate the dynamic adjustment coefficient of the collection cycle based on the amount of information collected, the preset collection cycle and the historical payment abnormal coefficient information;

[0151] The calculation formula of the acquisition cycle dynamic adjustment coefficient is:

[0152]

[0153] Among them, D cq is the dynamic adjustment coefficient of the acquisition cycle, Z yq is the number of days of a shot collection cycle, L xc is the current accumulated amount of information collected, L yc is the preset collection volume threshold;

[0154] Compare the acquisition cycle dynamic adjustment coefficient with a preset adjustment threshold to obtain an adjustment comparison result;

[0155] When the dynamic adjustment coefficient of the acquisition cycle is greater than the preset adjustment threshold, the acquisition cycle is adjusted to a shorter value. cq ;

[0156] On the contrary, adjust D cq ;

[0157] The preset acquisition period is dynamically adjusted according to the adjustment comparison result to obtain a dynamic adjustment result.

[0158] The working principle of the above technical solution is: the system automatically collects building information according to a preset collection cycle (such as daily, weekly or monthly). This collected information may include but is not limited to the use of facilities in the building, energy consumption data, security monitoring records, etc., depending on the needs and goals of property management. The system compares the collected information collection volume (i.e. the actual amount of data collected or the number of information points) with the preset collection volume threshold. This threshold is used to determine whether the current information collection volume has reached the standard that requires re-evaluation or adjustment of property fees. According to the collection volume comparison result, the system performs corresponding operations. If the information collection volume is greater than the preset collection volume threshold, it means that the use of facilities in the building, energy consumption or other related factors have changed significantly, and the property fees may need to be adjusted to reflect these changes. At this time, the system will trigger the re-collection and payment process of the property fees, including recalculating fees, generating new payment notices, updating financial records, etc., and generating fee payment update data for subsequent verification and auditing. If the information collection volume does not exceed the preset collection volume threshold, it is considered that the current property fee level is reasonable and there is no need to re-collect and pay. The monitoring function of data accuracy and periodic update is guaranteed.

[0159] The technical effect of the above technical solution is that by regularly collecting building information and comparing it with the preset threshold, the system can dynamically evaluate the rationality of property fees and adjust them according to the actual situation. This helps to ensure that the property fees are consistent with the actual use of the building, avoiding the problem of excessive or low fees that may be caused by the fixed fee model. The mechanism allows the property manager to flexibly adjust the fees based on factors such as the use of facilities in the building, changes in energy consumption and periodic changes, thereby improving the flexibility and adaptability of fee management. This helps to better meet the needs of owners and improve the overall level of property management services. The decision-making process of re-collecting and paying fees is based on the actual collected data and the preset threshold, which enhances the transparency and fairness of fee collection. Owners can clearly understand the reasons and basis for fee adjustments, thereby enhancing their trust in property management services. By regularly collecting building information, property managers can promptly discover problems such as abnormal energy consumption or improper use of facilities, and take corresponding measures to optimize them. This helps to reduce energy consumption, improve resource utilization efficiency, and bring long-term economic benefits to property management. The entire process is automated, reducing manual intervention and the use of paper documents, and improving the efficiency and digitalization of property management. At the same time, the real-time generation and display of fee payment update data provides property managers with convenient verification and auditing tools, further improving work efficiency.

[0160] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for fusion processing of property payment data, characterized in that: The method comprises: S1. Obtain owner information and building information within the property management scope, generate a building information model, locate the owner's building, obtain the owner's building information, collect the owner's pending payment information, and obtain building collection information; Wherein, the S1 includes: Obtain property management scope information, and determine the owner information within the scope based on the property management scope; Obtain building information within the property management scope and generate a building information model based on the building information; Locate the owner's building in the building information model according to the owner's information to obtain the owner's location information; Obtain the owner's building information based on the owner's location information; Collect the owner's pending payment information based on the owner's building information to obtain building collection information; S2. Split the building collection information to obtain a building payment split group, and integrate the building collection information of the building payment split group to obtain business integration data; Wherein, the S2 includes: Preprocessing the building collection information to obtain preprocessed building collection information; Obtaining preset payment types, splitting the preprocessed building collection information according to the preset payment types, and obtaining building payment splitting groups of multiple preset payment types; Obtain the building collection information of each building payment split group, integrate all building collection information, and obtain business integration data; S3. Obtain fusion fee information based on business fusion data, split the fusion fee information, obtain the fee split by category, distribute and pay, calculate the payment abnormality coefficient, compare the abnormal situation, and then perform abnormal location marking and warning; Wherein, the S3 includes: Comprehensively collect property fees based on business integration data to obtain integrated fee information; Split the integrated fee information according to the preset payment types of the building payment split group to obtain the type split fee of each preset payment type; Pay the fees for the building payment split groups corresponding to the preset payment categories by splitting the fees by category, and obtain the fee payment data for each building payment split group; Calculate the payment anomaly coefficient based on the building collection information, integrated collection information and fee payment data; Among them, the building collection information includes the actual amount payable, the integrated collection information includes the actual amount collected, and the fee payment data includes the actual amount paid; The calculation formula for the payment abnormality coefficient is: Among them, Y jnxs To pay the abnormal coefficient, R sq To integrate the fee collection information, Z is the number of preset payment types, F jni The payment data for the i-th type of building payment split group, F ci Collect information for the buildings in the i-th type of building payment split group; Compare the payment anomaly coefficient with the preset anomaly threshold to obtain a payment anomaly comparison result; According to the payment anomaly comparison results, the payment process is identified as abnormal, and abnormal location marking and warning are performed, and abnormal payment update processing is performed; S4. Obtaining the amount of information collected of the building collection information, updating fee collection and payment according to the amount of information collected, and obtaining fee payment update data; Wherein, the S4 includes: Collect building information according to a preset collection cycle to obtain information collection volume; Compare the information collection amount with a preset collection amount threshold to obtain a collection amount comparison result; The property fees are re-collected and paid based on the comparison results of the collected quantities to obtain updated fee payment data.

2. A property payment data fusion processing system, characterized in that: The system comprises: The building collection module is used to obtain the owner information and building information within the property management scope, generate a building information model, locate the owner's building, obtain the owner's building information, collect the owner's pending payment information, and obtain building collection information; Wherein, the building collection module includes: The owner information collection module is used to obtain the property management scope information and determine the owner information within the scope according to the property management scope; The owner's building positioning module is used to obtain building information within the property management scope and generate a building information model based on the building information; Locate the owner's building in the building information model according to the owner's information to obtain the owner's location information; The owner's building payment collection module is used to obtain the owner's building information based on the owner's location information; Collect the owner's pending payment information based on the owner's building information to obtain building collection information; The payment splitting and integration module is used to split the building collection information to obtain the building payment splitting group, integrate the building collection information of the building payment splitting group, and obtain business integration data; The payment splitting and integration module includes: The collected information splitting module is used to pre-process the building collected information to obtain the pre-processed building collected information; Obtaining preset payment types, splitting the preprocessed building collection information according to the preset payment types, and obtaining building payment splitting groups of multiple preset payment types; The information integration module to be paid is used to obtain the building collection information of each building payment split group, integrate all the building collection information, and obtain business integration data; The payment integration and splitting module is used to obtain integrated fee information based on business integration data, split the integrated fee information, obtain the split fees by category, distribute the payment, calculate the payment anomaly coefficient, compare the anomaly situation, and then perform anomaly location marking and warning; Wherein, the payment integration and splitting module includes: The fusion and splitting module is used to collect property fees in a comprehensive manner based on the business fusion data and obtain fusion collection fee information; Split the integrated fee information according to the preset payment types of the building payment split group to obtain the type split fee of each preset payment type; The split payment module is used to pay the building payment split group corresponding to the preset payment type by splitting the fee by type, and obtain the fee payment data of each type of building payment split group; The abnormal calculation and comparison module is used to calculate the payment abnormality coefficient based on the building collection information, the integrated collection information and the fee payment data; Among them, the building collection information includes the actual amount payable, the integrated collection information includes the actual amount collected, and the fee payment data includes the actual amount paid; The calculation formula for the payment abnormality coefficient is: Among them, Y jnxs To pay the abnormal coefficient, R sq To integrate the fee collection information, Z is the number of preset payment types, F jni The payment data for the i-th type of building payment split group, F ci Collect information for the buildings in the i-th type of building payment split group; Compare the payment anomaly coefficient with the preset anomaly threshold to obtain a payment anomaly comparison result; The abnormal warning processing module is used to identify abnormalities in the payment process according to the payment abnormality comparison results, and to locate and mark abnormalities, issue warnings, and perform abnormal payment update processing; A collection and update module is used to obtain the information collection amount of the building collection information, update the fee collection and payment according to the information collection amount, and obtain the fee payment update data; Wherein, the acquisition and update module includes: A periodic collection module is used to collect building information according to a preset collection period to obtain information collection volume; A collection comparison module is used to compare the information collection amount with a preset collection amount threshold to obtain a collection amount comparison result; The data update module is used to re-collect and pay the property fees based on the collection volume comparison results and obtain fee payment update data.

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