A rural real estate and land rights registration data processing system based on the Internet of Things

Abstract

The present invention discloses a rural real estate integrated rights confirmation and registration data processing system based on the Internet of Things, which specifically relates to the field of rights confirmation and registration technology, including a data area division module, a real estate rights confirmation basic data acquisition module, a real estate rights confirmation basic data analysis module, a construction and transaction dynamic data acquisition module, a construction and transaction dynamic data analysis module, a comprehensive analysis module, and an early warning module. The present invention can not only provide comprehensive and accurate data support, but also timely discover potential problems through dynamic monitoring and early warning mechanisms, and provide a scientific basis for policy formulation and market management. In addition, the establishment of a comprehensive analysis module makes it possible to conduct a comprehensive assessment of market conditions, and provides a powerful tool for optimizing resource allocation and promoting stable market development. In general, the present invention improves data processing efficiency, enhances the scientificity and accuracy of market management, and is of great significance to the healthy development of the rural real estate market.

Description

Technical Field

[0001] The present invention relates to the field of property rights confirmation and registration, and more specifically, to a rural real estate integrated property rights confirmation and registration data processing system based on the Internet of Things. Background Art

[0002] With the prosperity of the rural economy and the acceleration of urbanization, the importance of the rural real estate market has become increasingly prominent. As the basic work of the rural real estate market, the integrated real estate and land rights registration is of great significance to protecting the rights and interests of farmers and promoting the development of the rural economy. However, due to the vast rural areas and the complex and diverse real estate resources, the traditional data processing method of the integrated real estate and land rights registration has gradually become unable to meet the needs of modern rural real estate market management.

[0003] At present, the existing rural real estate rights registration data processing systems mostly adopt automated or semi-automated methods. Although they have improved the efficiency of data processing to a certain extent, they still have many limitations. These systems mainly rely on database technology and network communication technology, which can realize centralized storage and remote access of data. However, there are still deficiencies in data collection, integration, analysis and monitoring, and they cannot meet the requirements of real-time monitoring and comprehensive analysis of dynamic changes in the rural real estate market.

[0004] However, there are still some shortcomings in its actual use. For example, the existing systems mostly rely on fixed data sources for data collection, which makes it difficult to achieve real-time and dynamic data acquisition of the rural real estate market. For the massive amount of data collected, the existing systems often lack effective integration and analysis methods, and it is difficult to extract valuable information from them to provide a scientific basis for policy formulation and market management. The existing systems lack a complete early warning mechanism and are unable to promptly discover and deal with potential problems and risks in the rural real estate market, making it difficult to provide timely and effective regulatory information to market regulatory authorities. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a rural real estate integrated title confirmation and registration data processing system based on the Internet of Things, which solves the problems raised in the above-mentioned background technology through the following scheme.

[0006] To achieve the above-mentioned purpose, the present invention provides the following technical solution: a rural real estate integrated rights confirmation and registration data processing system based on the Internet of Things, comprising:

[0007] Data area division module: used to determine the rural real estate and land rights registration data as the target data area, divide the target data area into various sub-data areas by dividing them according to a single administrative village, and mark them as 1, 2...n in sequence, and divide the data collection time of the target data area into various time areas by equal time division, and mark them as 1, 2...m in sequence;

[0008] Real estate rights confirmation basic data collection module: used to collect land ownership subdivision data, land use efficiency data, and cadastral survey and measurement data in each sub-data area, and transmit the collected data to the real estate rights confirmation basic data analysis module;

[0009] Real estate rights confirmation basic data analysis module: including land ownership subdivision data analysis unit, land use efficiency data analysis unit and cadastral survey and measurement data analysis unit, used to analyze the data transmitted by the real estate rights confirmation basic data acquisition module and transmit the analysis results to the comprehensive analysis module;

[0010] Construction and transaction dynamic data collection module: used to collect housing construction and maintenance data, real estate transaction and market dynamic data, and real estate tax and financial data in each sub-data area, and transmit the collected data to the construction and transaction dynamic data analysis module;

[0011] Construction and transaction dynamic data analysis module: including housing construction and maintenance data analysis unit, real estate transaction and market dynamic data analysis unit and real estate tax and financial data analysis unit, used to analyze the data transmitted by the construction and transaction dynamic data acquisition module, and transmit the analysis results to the comprehensive analysis module;

[0012] Comprehensive analysis module: used to establish a comprehensive analysis model, import the data transmitted by the real estate rights confirmation basic data analysis module and the construction and transaction dynamic data analysis module into the comprehensive analysis model, calculate the comprehensive optimization index of each sub-data area, and transmit it to the early warning module;

[0013] Early warning module: used to establish a preset value of the comprehensive optimization index, and judge the comprehensive optimization index of each sub-data area according to the preset value of the comprehensive optimization index, and issue an early warning signal according to the judgment result.

[0014] Preferably, the land ownership subdivision data include the number of changes in land ownership, the number of ownership dispute cases, the proportion of shared land area, and the completeness rate of ownership certification documents, which are marked as Po, Pd, Pc, and Pl, respectively; the land use efficiency data include land utilization rate, building coverage rate, illegal land use ratio, and land use type conversion ratio, which are marked as Lu, Lb, Lv, and Lc, respectively; the cadastral survey and measurement data include boundary point accuracy deviation, cadastral survey update cycle, unregistered land ratio, and elevation change rate, which are marked as Ma, Mu, Mr, and Me, respectively.

[0015] Preferably, the land ownership subdivision data analysis unit is used to establish a land ownership subdivision data analysis model, import the land ownership subdivision data transmitted by the real estate confirmation basic data acquisition module into the land ownership subdivision data analysis model, and calculate the land ownership assessment value of each sub-data area, which is specifically expressed as: , FP i,j Po represents the land ownership assessment value of the jth time zone in the i-th sub-data area, i,j Pd represents the number of changes in the ownership of the land parcels in the jth time zone of the i-th sub-data area. i,j Pc represents the number of ownership dispute cases in the jth time zone of the ith sub-data zone, i,j represents the proportion of the common land area in the jth time zone of the ith sub-data zone, Pl i,j It indicates the completeness rate of ownership certification documents in the jth time zone of the i-th sub-data zone.

[0016] Preferably, the land use efficiency data analysis unit is used to establish a land use efficiency data analysis model, import the land use efficiency data transmitted by the real estate rights confirmation basic data acquisition module into the land use efficiency data analysis model, and calculate the land use efficiency value of each sub-data area, which is specifically expressed as: , F.L. i,j represents the land use efficiency value of the jth time zone of the ith sub-data area, Lu i,j represents the land use rate of the jth time zone of the ith sub-data area, Lb i,j represents the building coverage rate of the jth time zone of the ith sub-data zone, Lv i,j Indicates the proportion of illegal land use in the jth time zone of the ith sub-data area, Lc i,j Indicates the land use type conversion ratio of the jth time zone in the i-th sub-data area, max j (Lu i,j ) represents the maximum land utilization rate of the i-th sub-data area.

[0017] Preferably, the cadastral survey and measurement data analysis unit is used to establish a cadastral survey and measurement data analysis model, import the cadastral survey and measurement data transmitted by the real estate rights confirmation basic data acquisition module into the cadastral survey and measurement data analysis model, and calculate the cadastral dynamic monitoring value of each sub-data area, which is specifically expressed as: , FM i,j It represents the cadastral dynamic monitoring value of the jth time zone in the ith sub-data area, Ma i,j Indicates the accuracy deviation of the boundary point of the jth time zone of the ith sub-data zone, Mu i,j represents the cadastral survey update period of the jth time zone of the ith sub-data zone, Mr i,jThe proportion of unregistered plots in the jth time zone of the ith sub-data zone, Me i,j Indicates the elevation change rate of the j-th time zone in the ith sub-data area.

[0018] Preferably, the real estate rights confirmation basic data analysis module calculates the real estate rights confirmation basic characteristic value of the jth time zone of the i-th sub-data area through the land ownership assessment value of the jth time zone of the i-th sub-data area, the land use efficiency value of the jth time zone of the i-th sub-data area, and the cadastral dynamic monitoring value of the jth time zone of the i-th sub-data area, which is specifically expressed as: , κ i,j represents the basic characteristic value of real estate title confirmation in the jth time zone of the ith sub-data area, and µ1 represents other influencing factors of the basic characteristic value of real estate title confirmation.

[0019] Preferably, the housing construction and maintenance data include the housing construction cycle change rate, maintenance frequency, building material usage, and building energy-saving standard compliance rate, which are marked as Bc, Bf, Bu, and Be, respectively; the real estate transaction and market dynamics data include transaction price volatility, cross-regional transaction proportion, real estate pre-sale volume, and real estate development investment growth rate, which are marked as Df, Dc, Dp, and Dg, respectively; the real estate tax and financial data include real estate tax revenue growth rate, real estate loan default rate, real estate investment return rate, and real estate loan risk exposure ratio, which are marked as Rg, Rd, Ro, and Rx, respectively.

[0020] Preferably, the housing construction and maintenance data analysis unit is used to establish a housing construction and maintenance data analysis model, import the housing construction and maintenance data transmitted by the building and transaction dynamic data acquisition module into the housing construction and maintenance data analysis model, and calculate the housing operation and maintenance efficiency value of each sub-data area, which is specifically expressed as: , TB i,j represents the house operation and maintenance efficiency value of the jth time zone in the i-th sub-data zone, Bc i,j represents the housing construction cycle change rate in the jth time zone of the ith sub-data zone, Bf i,j represents the maintenance frequency of the jth time zone of the ith sub-data zone, Bu i,j represents the amount of building materials used in the jth time zone of the ith sub-data zone, Be i,j Indicates the building energy conservation standard compliance rate in the jth time zone of the ith sub-data area, min j (Bf i,j ) represents the minimum maintenance frequency of the i-th sub-data area.

[0021] Preferably, the real estate transaction and market dynamics data analysis unit is used to establish a real estate transaction and market dynamics data analysis model, import the real estate transaction and market dynamics data transmitted by the building and transaction dynamics data acquisition module into the real estate transaction and market dynamics data analysis model, and calculate the real estate market dynamics efficiency value of each sub-data area, which is specifically expressed as: , TD i,j represents the dynamic efficiency value of the real estate market in the jth time zone of the ith sub-data zone, Df i,j Denotes the transaction price volatility of the jth time zone of the ith sub-data zone, Dc i,j represents the proportion of cross-region transactions in the jth time zone of the ith sub-data zone, Dp i,j represents the real estate pre-sale volume in the jth time zone of the ith sub-data zone, Dg i,j Represents the growth rate of real estate development investment in the jth time zone of the ith sub-data zone.

[0022] Preferably, the real estate tax and financial data analysis unit is used to establish a real estate tax and financial data analysis model, import the real estate tax and financial data transmitted by the building and transaction dynamic data acquisition module into the real estate tax and financial data analysis model, and calculate the real estate financial security assessment value of each sub-data area, which is specifically expressed as: , TR i,j Rg represents the real estate financial security assessment value of the jth time zone in the ith sub-data zone. i,j Rd represents the growth rate of property tax revenue in the jth time zone of the ith sub-data zone. i,j represents the real estate loan default rate in the jth time zone of the ith sub-data zone, Ro i,j represents the real estate investment return rate of the jth time zone in the ith sub-data zone, Rx i,j It represents the real estate loan risk exposure ratio of the jth time period in the i-th sub-data area.

[0023] Preferably, the building and transaction dynamic data analysis module calculates the transaction dynamic characteristic value of the jth time zone of the ith sub-data area through the house operation and maintenance efficiency value of the jth time zone of the ith sub-data area, the real estate market dynamic efficiency value of the jth time zone of the ith sub-data area, and the real estate financial security assessment value of the jth time zone of the ith sub-data area, which is specifically expressed as: , τ i,j represents the transaction dynamic characteristic value of the jth time zone of the ith sub-data zone, and µ2 represents other influencing factors of the transaction dynamic characteristic value.

[0024] Preferably, the comprehensive analysis model is specifically expressed as: , η irepresents the comprehensive optimization index of the ith sub-data region, κ i,j represents the basic characteristic value of real estate rights confirmation in the jth time zone of the ith sub-data zone, τ i,j It represents the transaction dynamic characteristic value of the jth time zone in the ith sub-data area, β1 represents the weight of the basic characteristic value of real estate title confirmation, β2 represents the weight of the transaction dynamic characteristic value, and λ represents other influencing factors of the comprehensive optimization index.

[0025] Preferably, the preset value of the comprehensive optimization index is marked as η Def , when η Def <η i When η is greater than the preset value of the comprehensive optimization index, it means that the overall health and stability of the real estate market in the i-th administrative village is good. Def >η i When , it means that the comprehensive optimization index of the ith sub-data area is less than the preset value of the comprehensive optimization index, indicating that the overall health and stability of the real estate market in the ith administrative village are poor, and a warning signal is sent to the management terminal.

[0026] Technical effects and advantages of the present invention:

[0027] The present invention divides the rural real estate and land rights confirmation and registration data into specific sub-data areas and time areas through the data area division module, thereby realizing the meticulous management and efficient processing of the data, which not only helps to improve the data processing efficiency, but also ensures the orderliness and traceability of the data, and provides a solid foundation for subsequent in-depth analysis. At the same time, by comparing and analyzing the data of different regions and time periods, it helps to reveal the differences and development trends of the real estate markets between different regions, and provides strong support for policy formulation and market management. The basic data required for rural real estate rights confirmation, including land ownership subdivision data, land use efficiency data and cadastral survey and measurement data, is comprehensively collected through the real estate rights confirmation basic data collection module, which not only ensures the data The accuracy and completeness of the data also provide a rich and comprehensive data source for subsequent data analysis. Through in-depth analysis and mining of these data, we can better understand the current situation and potential problems of the rural real estate market, and provide a scientific basis for policy formulation and market management. Through the basic data analysis module of real estate rights confirmation, multiple data analysis units are established to accurately analyze and quantitatively evaluate the collected data, including land ownership subdivision data analysis unit, land use efficiency data analysis unit and cadastral survey and measurement data analysis unit. Each unit conducts in-depth analysis on a specific type of data. Through comprehensive analysis and comparison of these data, key indicators and rules can be extracted to provide comprehensive evaluation of the rural real estate market and future trend forecast. Provide strong support; collect dynamic data of the rural real estate market in real time through the construction and transaction dynamic data collection module, including housing construction and maintenance data, real estate transaction and market dynamic data, and real estate tax and financial data, ensuring the timeliness and accuracy of the data, which helps the market supervision department to grasp the market dynamics and changing trends in a timely manner. Through in-depth analysis of these data, the market activity and health can be revealed, providing a scientific basis for strategy adjustment and market supervision; establish multiple data analysis units through the construction and transaction dynamic data analysis module to conduct in-depth analysis of the collected dynamic data, including housing construction and maintenance data analysis unit, real estate transaction and market dynamic data analysis unit and real estate tax and financial data. According to the analysis units, each unit conducts in-depth mining on specific types of data. Through the comprehensive analysis and evaluation of these data, the market activity and health can be evaluated, the market development trend and potential risks can be revealed, and strong support can be provided for strategy adjustment and market supervision. Through the comprehensive analysis module, a comprehensive analysis model is established, and the basic data of real estate rights confirmation and the dynamic data of construction and transaction are integrated and analyzed to calculate the comprehensive optimization index, which reflects the overall situation and potential problems of the rural real estate market and provides strong support for the formulation of scientific market management strategies. At the same time, by comparing and analyzing the comprehensive optimization indexes of different regions and time periods, it is helpful to reveal the differences and trends of market development and provide a scientific basis for policy formulation and market management.The early warning module establishes a preset value for the comprehensive optimization index, judges the comprehensive optimization index of the sub-data area, and issues early warning signals based on the judgment results, which helps to timely discover potential problems and risks and reduce the impact of market risks and market fluctuations on the rural economy. At the same time, the early warning module can also provide timely and effective supervision information to market supervision departments to promote the smooth operation and healthy development of the rural real estate market. ; BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is a schematic diagram of the overall structure of the present invention. DETAILED DESCRIPTION

[0029] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0030] refer to Figure 1 The rural real estate and land rights integrated registration data processing system based on the Internet of Things is shown, including a data area division module, a real estate and land rights basic data collection module, a real estate and land rights basic data analysis module, a construction and transaction dynamic data collection module, a construction and transaction dynamic data analysis module, a comprehensive analysis module, and an early warning module.

[0031] The data area division module is used to determine the rural real estate and land rights registration data as the target data area, divide the target data area into various sub-data areas by dividing them according to a single administrative village, and mark them as 1, 2...n in sequence; and divide the data collection time of the target data area into various time areas by equal time division, and mark them as 1, 2...m in sequence.

[0032] The real estate title confirmation basic data collection module is used to collect land ownership subdivision data, land use efficiency data, and cadastral survey and measurement data of each sub-data area, and transmit the collected data to the real estate title confirmation basic data analysis module.

[0033] The land ownership subdivision data include the number of changes in land ownership, the number of ownership dispute cases, the proportion of shared land area, and the completeness rate of ownership documents, which are marked as Po, Pd, Pc, and Pl respectively. The land use efficiency data include land utilization rate, building coverage rate, proportion of illegal land use, and proportion of land use type conversion, which are marked as Lu, Lb, Lv, and Lc respectively. The cadastral survey and measurement data include boundary point accuracy deviation, cadastral survey update cycle, proportion of unregistered land, and elevation change rate, which are marked as Ma, Mu, Mr, and Me respectively.

[0034] The real estate title confirmation basic data analysis module includes a land ownership subdivision data analysis unit, a land use efficiency data analysis unit and a cadastral survey and measurement data analysis unit, which is used to analyze the data transmitted by the real estate title confirmation basic data acquisition module and transmit the analysis results to the comprehensive analysis module.

[0035] The land ownership subdivision data analysis unit is used to establish a land ownership subdivision data analysis model, import the land ownership subdivision data transmitted by the real estate confirmation basic data acquisition module into the land ownership subdivision data analysis model, and calculate the land ownership assessment value of each sub-data area, which is specifically expressed as: , FP i,j Po represents the land ownership assessment value of the jth time zone in the i-th sub-data area, i,j Pd represents the number of changes in the ownership of the land parcels in the jth time zone of the i-th sub-data area. i,j Pc represents the number of ownership dispute cases in the jth time zone of the ith sub-data zone, i,j represents the proportion of the common land area in the jth time zone of the ith sub-data zone, Pl i,j It indicates the completeness rate of ownership certification documents in the jth time zone of the i-th sub-data zone.

[0036] The land use efficiency data analysis unit is used to establish a land use efficiency data analysis model, import the land use efficiency data transmitted by the real estate rights confirmation basic data acquisition module into the land use efficiency data analysis model, and calculate the land use efficiency value of each sub-data area, which is specifically expressed as: , F.L. i,j represents the land use efficiency value of the jth time zone of the ith sub-data area, Lu i,j represents the land use rate of the jth time zone of the ith sub-data area, Lb i,j represents the building coverage rate of the jth time zone of the ith sub-data zone, Lv i,j Indicates the proportion of illegal land use in the jth time zone of the ith sub-data area, Lc i,j Indicates the land use type conversion ratio of the jth time zone in the i-th sub-data area, max j (Lu i,j ) represents the maximum land utilization rate of the i-th sub-data area.

[0037] The cadastral survey and measurement data analysis unit is used to establish a cadastral survey and measurement data analysis model, import the cadastral survey and measurement data transmitted by the real estate right confirmation basic data acquisition module into the cadastral survey and measurement data analysis model, and calculate the cadastral dynamic monitoring value of each sub-data area, which is specifically expressed as: , FMi,j It represents the cadastral dynamic monitoring value of the jth time zone in the ith sub-data area, Ma i,j Indicates the accuracy deviation of the boundary point of the jth time zone of the ith sub-data zone, Mu i,j represents the cadastral survey update period of the jth time zone of the ith sub-data zone, Mr i,j The proportion of unregistered plots in the jth time zone of the ith sub-data zone, Me i,j Indicates the elevation change rate of the j-th time zone in the ith sub-data area.

[0038] The real estate rights confirmation basic data analysis module calculates the real estate rights confirmation basic characteristic value of the jth time zone of the ith sub-data area through the land ownership evaluation value of the jth time zone of the ith sub-data area, the land use efficiency value of the jth time zone of the ith sub-data area, and the cadastral dynamic monitoring value of the jth time zone of the ith sub-data area, which is specifically expressed as: , κ i,j represents the basic characteristic value of real estate title confirmation in the jth time zone of the ith sub-data area, and µ1 represents other influencing factors of the basic characteristic value of real estate title confirmation.

[0039] The construction and transaction dynamic data collection module is used to collect housing construction and maintenance data, real estate transaction and market dynamic data, and real estate tax and financial data in each sub-data area, and transmit the collected data to the construction and transaction dynamic data analysis module.

[0040] The housing construction and maintenance data include the housing construction cycle change rate, maintenance frequency, building material usage, and building energy-saving standard compliance rate, marked as Bc, Bf, Bu, and Be respectively. The real estate transaction and market dynamics data include transaction price volatility, cross-regional transaction proportion, real estate pre-sale volume, and real estate development investment growth rate, marked as Df, Dc, Dp, and Dg respectively. The real estate tax and financial data include the real estate tax revenue growth rate, real estate loan default rate, real estate investment return rate, and real estate loan risk exposure ratio, marked as Rg, Rd, Ro, and Rx respectively.

[0041] The construction and transaction dynamic data analysis module includes a housing construction and maintenance data analysis unit, a real estate transaction and market dynamic data analysis unit, and a real estate tax and financial data analysis unit, which are used to analyze the data transmitted by the construction and transaction dynamic data acquisition module and transmit the analysis results to the comprehensive analysis module.

[0042] The housing construction and maintenance data analysis unit is used to establish a housing construction and maintenance data analysis model, import the housing construction and maintenance data transmitted by the building and transaction dynamic data acquisition module into the housing construction and maintenance data analysis model, and calculate the housing operation and maintenance efficiency value of each sub-data area, which is specifically expressed as: , TB i,j represents the house operation and maintenance efficiency value of the jth time zone in the i-th sub-data zone, Bc i,j represents the housing construction cycle change rate in the jth time zone of the ith sub-data zone, Bf i,j represents the maintenance frequency of the jth time zone of the ith sub-data zone, Bu i,j represents the amount of building materials used in the jth time zone of the ith sub-data zone, Be i,j Indicates the building energy conservation standard compliance rate in the jth time zone of the ith sub-data area, min j (Bf i,j ) represents the minimum maintenance frequency of the i-th sub-data area.

[0043] The real estate transaction and market dynamics data analysis unit is used to establish a real estate transaction and market dynamics data analysis model, import the real estate transaction and market dynamics data transmitted by the building and transaction dynamics data acquisition module into the real estate transaction and market dynamics data analysis model, and calculate the real estate market dynamics efficiency value of each sub-data area, which is specifically expressed as: , TD i,j represents the dynamic efficiency value of the real estate market in the jth time zone of the ith sub-data zone, Df i,j Denotes the transaction price volatility of the jth time zone of the ith sub-data zone, Dc i,j represents the proportion of cross-region transactions in the jth time zone of the ith sub-data zone, Dp i,j represents the real estate pre-sale volume in the jth time zone of the ith sub-data zone, Dg i,j Represents the growth rate of real estate development investment in the jth time zone of the ith sub-data zone.

[0044] The real estate tax and financial data analysis unit is used to establish a real estate tax and financial data analysis model, import the real estate tax and financial data transmitted by the building and transaction dynamic data acquisition module into the real estate tax and financial data analysis model, and calculate the real estate financial security assessment value of each sub-data area, which is specifically expressed as: , TR i,j Rg represents the real estate financial security assessment value of the jth time zone in the ith sub-data zone. i,j Rd represents the growth rate of property tax revenue in the jth time zone of the ith sub-data zone. i,j represents the real estate loan default rate in the jth time zone of the ith sub-data zone, Roi,j represents the real estate investment return rate of the jth time zone in the ith sub-data zone, Rx i,j It represents the real estate loan risk exposure ratio of the jth time period in the i-th sub-data area.

[0045] The building and transaction dynamic data analysis module calculates the transaction dynamic characteristic value of the jth time zone of the ith sub-data area through the house operation and maintenance efficiency value of the jth time zone of the ith sub-data area, the real estate market dynamic efficiency value of the jth time zone of the ith sub-data area, and the real estate financial security assessment value of the jth time zone of the ith sub-data area, which is specifically expressed as: , τ i,j represents the transaction dynamic characteristic value of the jth time zone of the ith sub-data zone, and µ2 represents other influencing factors of the transaction dynamic characteristic value.

[0046] The comprehensive analysis module is used to establish a comprehensive analysis model, import the data transmitted by the real estate rights confirmation basic data analysis module and the construction and transaction dynamic data analysis module into the comprehensive analysis model, calculate the comprehensive optimization index of each sub-data area, and transmit it to the early warning module.

[0047] The comprehensive analysis model is specifically expressed as: , η i represents the comprehensive optimization index of the ith sub-data region, κ i,j represents the basic characteristic value of real estate rights confirmation in the jth time zone of the ith sub-data zone, τ i,j It represents the transaction dynamic characteristic value of the jth time zone in the ith sub-data area, β1 represents the weight of the basic characteristic value of real estate title confirmation, β2 represents the weight of the transaction dynamic characteristic value, and λ represents other influencing factors of the comprehensive optimization index.

[0048] The early warning module is used to establish a preset value of the comprehensive optimization index, and judge the comprehensive optimization index of each sub-data area according to the preset value of the comprehensive optimization index, and issue an early warning signal according to the judgment result.

[0049] The preset value of the comprehensive optimization index is marked as η Def , when η Def <η i When η is greater than the preset value of the comprehensive optimization index, it means that the overall health and stability of the real estate market in the i-th administrative village is good. Def >η i When , it means that the comprehensive optimization index of the ith sub-data area is less than the preset value of the comprehensive optimization index, indicating that the overall health and stability of the real estate market in the ith administrative village are poor, and a warning signal is sent to the management terminal.

[0050] The present invention divides the rural real estate and land rights confirmation and registration data into specific sub-data areas and time areas through the data area division module, thereby realizing the meticulous management and efficient processing of the data, which not only helps to improve the data processing efficiency, but also ensures the orderliness and traceability of the data, and provides a solid foundation for subsequent in-depth analysis. At the same time, by comparing and analyzing the data of different regions and time periods, it helps to reveal the differences and development trends of the real estate markets between different regions, and provides strong support for policy formulation and market management. The basic data required for rural real estate rights confirmation, including land ownership subdivision data, land use efficiency data and cadastral survey and measurement data, is comprehensively collected through the real estate rights confirmation basic data collection module, which not only ensures the data The accuracy and completeness of the data also provide a rich and comprehensive data source for subsequent data analysis. Through in-depth analysis and mining of these data, we can better understand the current situation and potential problems of the rural real estate market, and provide a scientific basis for policy formulation and market management. Through the basic data analysis module of real estate rights confirmation, multiple data analysis units are established to accurately analyze and quantitatively evaluate the collected data, including land ownership subdivision data analysis unit, land use efficiency data analysis unit and cadastral survey and measurement data analysis unit. Each unit conducts in-depth analysis on a specific type of data. Through comprehensive analysis and comparison of these data, key indicators and rules can be extracted to provide comprehensive evaluation of the rural real estate market and future trend forecast. Provide strong support; collect dynamic data of the rural real estate market in real time through the construction and transaction dynamic data collection module, including housing construction and maintenance data, real estate transaction and market dynamic data, and real estate tax and financial data, ensuring the timeliness and accuracy of the data, which helps the market supervision department to grasp the market dynamics and changing trends in a timely manner. Through in-depth analysis of these data, the market activity and health can be revealed, providing a scientific basis for strategy adjustment and market supervision; establish multiple data analysis units through the construction and transaction dynamic data analysis module to conduct in-depth analysis of the collected dynamic data, including housing construction and maintenance data analysis unit, real estate transaction and market dynamic data analysis unit and real estate tax and financial data. According to the analysis units, each unit conducts in-depth mining on specific types of data. Through the comprehensive analysis and evaluation of these data, the market activity and health can be evaluated, the market development trend and potential risks can be revealed, and strong support can be provided for strategy adjustment and market supervision. Through the comprehensive analysis module, a comprehensive analysis model is established, and the basic data of real estate rights confirmation and the dynamic data of construction and transaction are integrated and analyzed to calculate the comprehensive optimization index, which reflects the overall situation and potential problems of the rural real estate market and provides strong support for the formulation of scientific market management strategies. At the same time, by comparing and analyzing the comprehensive optimization indexes of different regions and time periods, it is helpful to reveal the differences and trends of market development and provide a scientific basis for policy formulation and market management.The early warning module establishes a preset value for the comprehensive optimization index, judges the comprehensive optimization index of the sub-data area, and issues early warning signals based on the judgment results, which helps to timely discover potential problems and risks and reduce the impact of market risks and market fluctuations on the rural economy. At the same time, the early warning module can also provide timely and effective supervision information to market supervision departments to promote the smooth operation and healthy development of the rural real estate market. ;

[0051] Secondly: In the drawings of the embodiments disclosed in the present invention, only the structures related to the embodiments disclosed in the present invention are involved, and other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of the present invention can be combined with each other;

[0052] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A rural real estate and land rights registration data processing system based on the Internet of Things, characterized by: include: Data area division module: used to determine the rural real estate and land rights registration data as the target data area, divide the target data area into various sub-data areas by dividing them according to a single administrative village, and mark them as 1, 2...n in sequence, and divide the data collection time of the target data area into various time areas by equal time division, and mark them as 1, 2...m in sequence; Real estate rights confirmation basic data collection module: used to collect land ownership subdivision data, land use efficiency data, and cadastral survey and measurement data in each sub-data area, and transmit the collected data to the real estate rights confirmation basic data analysis module; The land ownership subdivision data include the number of changes in land ownership, the number of ownership dispute cases, the proportion of shared land area, and the completeness rate of ownership documents, which are marked as Po, Pd, Pc, and Pl respectively; the land use efficiency data include the land use rate, building coverage rate, illegal land use rate, and land use type conversion rate, which are marked as Lu, Lb, Lv, and Lc respectively; the cadastral survey and measurement data include the boundary point accuracy deviation, cadastral survey update cycle, unregistered land rate, and elevation change rate, which are marked as Ma, Mu, Mr, and Me respectively; Real estate rights confirmation basic data analysis module: including land ownership subdivision data analysis unit, land use efficiency data analysis unit and cadastral survey and measurement data analysis unit, used to analyze the data transmitted by the real estate rights confirmation basic data acquisition module and transmit the analysis results to the comprehensive analysis module; The land ownership subdivision data analysis unit is used to establish a land ownership subdivision data analysis model, import the land ownership subdivision data transmitted by the real estate confirmation basic data acquisition module into the land ownership subdivision data analysis model, and calculate the land ownership assessment value of each sub-data area, which is specifically expressed as: FP i,j Po represents the land ownership assessment value of the jth time zone in the i-th sub-data area, i,j Pd represents the number of changes in the ownership of the land parcels in the jth time zone of the i-th sub-data area. i,j Pc represents the number of ownership dispute cases in the jth time zone of the ith sub-data zone, i,j represents the proportion of the common land area in the jth time zone of the ith sub-data zone, Pl i,j Indicates the completeness rate of ownership certification documents in the jth time zone of the i-th sub-data zone; The land use efficiency data analysis unit is used to establish a land use efficiency data analysis model, import the land use efficiency data transmitted by the real estate rights confirmation basic data acquisition module into the land use efficiency data analysis model, and calculate the land use efficiency value of each sub-data area, which is specifically expressed as: FL i,j represents the land use efficiency value of the jth time zone of the ith sub-data area, Lu i,j represents the land use rate of the jth time zone of the ith sub-data area, Lb i,j represents the building coverage rate of the jth time zone of the ith sub-data zone, Lv i,j Indicates the proportion of illegal land use in the jth time zone of the ith sub-data area, Lc i,j Indicates the land use type conversion ratio of the jth time zone in the i-th sub-data area, max j (Lu i,j ) represents the maximum land utilization rate of the i-th sub-data area; The cadastral survey and measurement data analysis unit is used to establish a cadastral survey and measurement data analysis model, import the cadastral survey and measurement data transmitted by the real estate right confirmation basic data acquisition module into the cadastral survey and measurement data analysis model, and calculate the cadastral dynamic monitoring value of each sub-data area, which is specifically expressed as: FM i,j It represents the cadastral dynamic monitoring value of the jth time zone in the ith sub-data area, Ma i,j Indicates the accuracy deviation of the boundary point of the jth time zone of the ith sub-data zone, Mu i,j represents the cadastral survey update period of the jth time zone of the ith sub-data zone, Mr i,j The proportion of unregistered plots in the jth time zone of the ith sub-data zone, Me i,j It represents the elevation change rate of the jth time zone of the ith sub-data area; The real estate rights confirmation basic data analysis module calculates the real estate rights confirmation basic characteristic value of the jth time zone of the ith sub-data area through the land ownership evaluation value of the jth time zone of the ith sub-data area, the land use efficiency value of the jth time zone of the ith sub-data area, and the cadastral dynamic monitoring value of the jth time zone of the ith sub-data area, which is specifically expressed as: κ i,j =(FP i,j +FL i,j +FM i,j )×μ1,κ i,j represents the basic characteristic value of real estate title confirmation in the jth time zone of the ith sub-data zone, and μ1 represents other influencing factors of the basic characteristic value of real estate title confirmation; Construction and transaction dynamic data collection module: used to collect housing construction and maintenance data, real estate transaction and market dynamic data, and real estate tax and financial data in each sub-data area, and transmit the collected data to the construction and transaction dynamic data analysis module; The housing construction and maintenance data include the housing construction cycle change rate, maintenance frequency, building material usage, and building energy-saving standard compliance rate, which are marked as Bc, Bf, Bu, and Be respectively; the real estate transaction and market dynamics data include transaction price volatility, cross-regional transaction proportion, real estate pre-sale volume, and real estate development investment growth rate, which are marked as Df, Dc, Dp, and Dg respectively; the real estate tax and financial data include real estate tax revenue growth rate, real estate loan default rate, real estate investment return rate, and real estate loan risk exposure ratio, which are marked as Rg, Rd, Ro, and Rx respectively; Construction and transaction dynamic data analysis module: including housing construction and maintenance data analysis unit, real estate transaction and market dynamic data analysis unit and real estate tax and financial data analysis unit, used to analyze the data transmitted by the construction and transaction dynamic data acquisition module, and transmit the analysis results to the comprehensive analysis module; The housing construction and maintenance data analysis unit is used to establish a housing construction and maintenance data analysis model, import the housing construction and maintenance data transmitted by the building and transaction dynamic data acquisition module into the housing construction and maintenance data analysis model, and calculate the housing operation and maintenance efficiency value of each sub-data area, which is specifically expressed as: TB i,j represents the house operation and maintenance efficiency value of the jth time zone in the i-th sub-data zone, Bc i,j represents the housing construction cycle change rate in the jth time zone of the ith sub-data zone, Bf i,j represents the maintenance frequency of the jth time zone of the ith sub-data zone, Bu i,j represents the amount of building materials used in the jth time zone of the ith sub-data zone, Be i,j Indicates the building energy conservation standard compliance rate in the jth time zone of the ith sub-data area, min j (Bf i,j ) represents the minimum maintenance frequency of the i-th sub-data area; The real estate transaction and market dynamics data analysis unit is used to establish a real estate transaction and market dynamics data analysis model, import the real estate transaction and market dynamics data transmitted by the building and transaction dynamics data acquisition module into the real estate transaction and market dynamics data analysis model, and calculate the real estate market dynamics efficiency value of each sub-data area, which is specifically expressed as: TD i,j represents the dynamic efficiency value of the real estate market in the jth time zone of the ith sub-data zone, Df i,j Denotes the transaction price volatility of the jth time zone of the ith sub-data zone, Dc i,j represents the proportion of cross-region transactions in the jth time zone of the ith sub-data zone, Dp i,j represents the real estate pre-sale volume in the jth time zone of the ith sub-data zone, Dg i,j Indicates the growth rate of real estate development investment in the jth time zone of the i-th sub-data zone; The real estate tax and financial data analysis unit is used to establish a real estate tax and financial data analysis model, import the real estate tax and financial data transmitted by the building and transaction dynamic data acquisition module into the real estate tax and financial data analysis model, and calculate the real estate financial security assessment value of each sub-data area, which is specifically expressed as: TR i,j Rg represents the real estate financial security assessment value of the jth time zone in the ith sub-data zone. i,j Rd represents the growth rate of property tax revenue in the jth time zone of the ith sub-data zone. i,j represents the real estate loan default rate in the jth time zone of the ith sub-data zone, Ro i,j represents the real estate investment return rate of the jth time zone in the ith sub-data zone, Rx i,j represents the real estate loan risk exposure ratio of the jth time period in the i-th sub-data area; The building and transaction dynamic data analysis module calculates the transaction dynamic characteristic value of the jth time zone of the ith sub-data area through the house operation and maintenance efficiency value of the jth time zone of the ith sub-data area, the real estate market dynamic efficiency value of the jth time zone of the ith sub-data area, and the real estate financial security assessment value of the jth time zone of the ith sub-data area, which is specifically expressed as: τ i,j =(TB i,j +TD i,j +TR i,j )×μ2,τ i,j represents the transaction dynamic characteristic value of the jth time zone of the ith sub-data zone, and μ2 represents other influencing factors of the transaction dynamic characteristic value; Comprehensive analysis module: used to establish a comprehensive analysis model, import the data transmitted by the real estate rights confirmation basic data analysis module and the construction and transaction dynamic data analysis module into the comprehensive analysis model, calculate the comprehensive optimization index of each sub-data area, and transmit it to the early warning module; Early warning module: used to establish a preset value of the comprehensive optimization index, and judge the comprehensive optimization index of each sub-data area according to the preset value of the comprehensive optimization index, and issue an early warning signal according to the judgment result.

2. According to the Internet of Things-based rural real estate and land rights confirmation and registration data processing system according to claim 1, it is characterized by: The comprehensive analysis model is specifically expressed as: η i represents the comprehensive optimization index of the ith sub-data region, κ i,j represents the basic characteristic value of real estate rights confirmation in the jth time zone of the ith sub-data zone, τ i,j It represents the transaction dynamic characteristic value of the jth time zone in the ith sub-data area, β1 represents the weight of the basic characteristic value of real estate title confirmation, β2 represents the weight of the transaction dynamic characteristic value, and λ represents other influencing factors of the comprehensive optimization index.

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