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KR-20260065993-A - System and Method for Housing Asset Liquidity and Modular Supply Optimization Management Based on Artificial Intelligence and Blockchain

KR20260065993AKR 20260065993 AKR20260065993 AKR 20260065993AKR-20260065993-A

Abstract

The present invention relates to a sales decision-making system that generates a candidate set of sales points by time-series matching real estate ownership information, external taxation standard data, price data, and policy application period data, and determines an optimal sales range based on tax burden indicators and objective function evaluations. Based on the decision results, it issues divisible digital right tokens, automatically settles and distributes profit data according to equity ratios, and records the settlement and right determination results in a manner capable of detecting changes. Furthermore, it provides a closed-loop control structure that calculates a housing supply plan and transmits instruction signals based on demand and liquidity indicators derived from ledger records, and performs re-evaluation and re-planning when policy, price, or process constraints or collateral value fluctuation events are detected.

Inventors

  • 김성금

Assignees

  • 김성금

Dates

Publication Date
20260512
Application Date
20260213

Claims (9)

  1. (System independent term) A communication unit (210) that receives real estate ownership information from a user terminal (100); A data normalization/integration unit (220) that collects tax base data, real estate price data, and policy application period data from an external data server (300), and generates an integrated dataset by performing item mapping and time series matching with the real estate ownership information; A selling decision engine (230) that calculates a tax burden indicator for a plurality of candidate selling points based on the above integrated dataset, evaluates an objective function value with the policy application period and user holding conditions as constraints to determine an optimal selling range or a break-even selling point, and transmits a selling proposal signal to the user terminal (100); When a sell approval signal is received from the user terminal (100), a token generation unit (240) calculates an asset value based on the optimal sell range or break-even sell point information and initiates the issuance of a divisible digital right token corresponding to the asset value; A settlement execution unit (250) that automatically executes settlement and dividends according to the ownership share ratio of the digital right token, using revenue data (which may include rental revenue and/or deposit operation revenue) as input; A ledger record (260) that provides verifiable integrity by recording the issuance, trading, ownership change, settlement, dividend, and rights determination results of the above digital rights token in a manner that allows for change detection; A supply control unit (270) that calculates a housing supply plan based on demand indicators and/or liquidity indicators derived from information recorded in the above ledger record unit (260), generates instruction signals including production instructions, shipment instructions, and assembly instructions, and transmits them to a factory server (500) and a logistics/field server (600); A smart collateral setting module (280) configured to replace all or part of the rental deposit by setting or depositing the digital right tokens held by the user as collateral; and A residential subscription authentication server (290) configured to grant, revoke, or renew access rights to the access control device (700) of the affiliated residential area to the user terminal (100) when the above collateral setting or deposit is confirmed; Includes, When a change event in policy application period data, a renewal event in price data, a violation of fair constraints, or a fluctuation event in the value of the digital right token is detected, the results of the sell decision engine (230), supply control unit (270), and residential subscription authentication server (290) are configured to be re-evaluated or re-planned and updated. AI and blockchain-based housing listing liquidity and modular supply optimization management system.
  2. (Method independent term) (i) A step of receiving real estate ownership information from a user terminal; (ii) a step of collecting tax base data, price data, and policy application period data from an external data server, and generating an integrated dataset by performing item mapping and time series matching; (iii) a step of calculating a tax burden indicator for a group of candidate selling points, evaluating an objective function to determine an optimal selling range or a break-even selling point, and transmitting a selling proposal signal; (iv) a step of calculating the asset value and initiating the issuance of divisible digital rights tokens when a sell approval signal is received; (v) A step of automatically executing settlement and dividends based on the token holding share ratio using profit data as input; (vi) A step of recording the results of token issuance, trading, change of ownership, settlement, dividend, and determination of rights in a manner that allows for change detection; (vii) a step of calculating a housing supply plan based on indicators generated from ledger records and transmitting an instruction signal; and (viii) a step of re-performing the above steps to update the result when a policy change, price update, violation of fair constraints, or change in collateral value event is detected; A housing property securitization and supply optimization management method including
  3. In claim 1, The above-mentioned selling decision engine (230) is a system characterized by modeling tax events (acquisition, holding, transfer) as time series state variables to calculate a tax burden indicator.
  4. In claim 1, A system characterized in that the above objective function is a weighted combined function including at least two indicators among minimizing tax burden, maximizing net profit, and minimizing accumulated holding tax.
  5. In claim 1, The above settlement execution unit (250) is characterized by including an invariant verification rule for detecting settlement errors or double payments.
  6. In claim 1, The above ledger record (260) is characterized by including a hash-based linkage structure and/or a consensus mechanism.
  7. In claim 1, The above supply control unit (270) is a system characterized by reflecting factory production capacity (CAPA), material procurement, logistics constraints and on-site assembly constraints as inputs.
  8. In claim 1, The system is characterized in that the supply control unit (270) includes a replanning module that replans the supply plan and updates and transmits the instruction signal when a constraint violation or schedule delay is detected.
  9. In claim 1, A system characterized by being configured to generate a signal requesting additional deposit or to restrict or revoke access rights in stages when the value of the above digital rights token falls below a predetermined collateral threshold.

Description

System and Method for Housing Asset Liquidity and Modular Supply Optimization Management Based on Artificial Intelligence and Blockchain The present invention relates to the fields of real estate technology (PropTech), financial technology (FinTech), distributed ledger technology (DLT), and construction supply chain management (Construction SCM), and relates to an integrated management system and method that calculates the timing of sale by normalizing user-held real estate information, external taxation standard data, price data, and policy application period data, flawlessly records the issuance and settlement of digital right tokens, updates housing supply plans on an event basis based on demand indicators, and controls digital collateral-based housing subscriptions. The conventional housing market faces a complex combination of issues, including a lock-up of listings due to increased tax burdens on multi-home owners, market entry barriers for small-scale investors caused by high-priced housing, and long lead times for new supply. Furthermore, as the application periods of tax laws and policies change frequently, it is difficult for individuals to determine the optimal selling time, and technical means are required to ensure the reliability of settlement and rights management during the real estate securitization process. Figure 1 is an overall configuration diagram of an artificial intelligence and blockchain-based housing listing liquidity and modular supply optimization management system according to the present invention. Figure 2 is a block diagram illustrating the data normalization and sell decision flow. Figure 3 is a flowchart illustrating the process of token issuance, automatic tax/fee deduction, settlement, and integrity recording. Figure 4 is a flowchart illustrating the supply control and replanning process based on demand and liquidity indicator feedback. Figure A1 is an event-based sell control configuration diagram. Figure B1 is a configuration diagram of a integrity log-based settlement control system. Figure C1 is a configuration diagram of digital collateral-based access control. Figure D1 is a demand indicator-based supply replanning configuration diagram. [Example] [Example 1: Overall System Configuration - See Fig. 1] The system according to the present invention may include a user terminal (100), a service providing server (200), an external data server (300), a ledger network (400), a factory server (500), a logistics/field server (600), and an access control device (700). The service providing server (200) may include a communication unit (210), a data normalization/integration unit (220), a selling decision engine (230), a token generation unit (240), a ledger record unit (260), a supply control unit (270), a smart collateral setting module (280), and a residential subscription authentication server (290). The user terminal (100) can input residential subscription application and modular option selection information, and said information can be reflected in the plan calculation of the supply control unit (270). [Example 2: Data Normalization and Sell Decision-Making - See Fig. 2] As shown in FIG. 2, In step S210, user-held information is received. In step S220, tax base data, price data, and policy application period data are collected from an external data server (300). In step S230, item mapping and time series matching are performed. In step S240, a candidate set of selling points is generated. In step S250, a tax burden indicator is calculated based on the tax event model. In step S260, an objective function evaluation considering constraints is performed. In step S270, determine the optimal selling range or break-even point. In step S280, a sell offer signal is transmitted to the user terminal. Detects policy or price events in step S290, and In step S295, a re-evaluation and update loop is performed. [Example 3: Token Issuance and Settlement/Integrity Recording - See FIG. 3 and FIG. B1] As shown in Fig. 3, Receive S310 sell approval signal. S320 asset values are calculated based on AVM or rules. Commence the issuance of S330 digital rights tokens. Receive S340 revenue data. S345 automatically deducts taxes and fees. Settlement and dividends are executed based on the S350 shareholding ratio. Prevent double spending by performing S360 invariant verification. Perform S370 rights determination. S380 performs ledger recording in a change-detectable manner. Derivs S390 trading volume, number of holders, settlement frequency, and concentration indicators. As illustrated in Fig. B1, the settlement calculation unit, invariant verification unit, settlement control unit, and ledger record unit can control execution/hold/retry by interacting with each other. [Example 4: Collateral-based access control - See FIG. C1] As shown in Fig. C1, When a collateral event occurs at the user terminal (100), the collateral event detection unit detects it. The Collateral Adequacy Assessment Departm