KR20220001127U - Commercial Real Estate Simulator using Public data and Vehicle Analysis - Google Patents

Commercial Real Estate Simulator using Public data and Vehicle Analysis Download PDF

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KR20220001127U
KR20220001127U KR2020200004097U KR20200004097U KR20220001127U KR 20220001127 U KR20220001127 U KR 20220001127U KR 2020200004097 U KR2020200004097 U KR 2020200004097U KR 20200004097 U KR20200004097 U KR 20200004097U KR 20220001127 U KR20220001127 U KR 20220001127U
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floating population
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김광수
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Abstract

본 발명은 상업용 부동산의 상권 분석을 위해 공개된 공공데이터와 차량 인식 기술을 활용한 유동인구지수를 통하여, 유동인구지수에 근거한 실질적인 단위 지역의 유동인구지수 구축을 가능하게하여 그에 맞는 상권 분석을 위한 시스템 및 그 방법을 제공한다.
이를 위해 본 발명은 차량 인식 기술에 기초하여 특정 지역의 차량 분석을 통하여 차량 유동인구 데이터를 데이터 성격 등에 따라 재분류하고, 공개된 공공데이터를 활용하여 체류 차량 분석과 유동인파분석, 산업분포 및 부동산 지표와 세금의 소득 가중치와 산업별 소득 평균등을 분석하여 지역별 방문자의 소득수준 추정치 산출과 그 지역 거주자의 자산수준 분포 산출 및 해당 지역 근무자의 소득수준 분포 산출등을 생성하여 데이터베이스화를 통하여 세밀하고 계산된 자료로 유동지수를 산출하는 것으로 지역 단위의 유동인구지수 구축을 특징으로 한다.The present invention enables the construction of a floating population index of a practical unit area based on the floating population index through the floating population index using public data and vehicle recognition technology disclosed for the analysis of the commercial area of commercial real estate, so that the appropriate commercial area analysis A system and method are provided.
To this end, the present invention reclassifies vehicle floating population data according to data characteristics, etc. through vehicle analysis in a specific area based on vehicle recognition technology, and utilizes public data to analyze staying vehicles and floating population, industrial distribution and real estate By analyzing the income weight of indicators and taxes and the average income by industry, it is possible to calculate the estimated income level of visitors by region, the distribution of the wealth level of the residents of the region, and the income level distribution of the workers in the region, and make detailed calculations through databaseization. It is characterized by the construction of a floating population index at the regional level by calculating the floating index using the collected data.

Figure utm00001
Figure utm00001

Description

비정형 데이터 분석을 통한 부동산 투자 의사 결정 시뮬레이터 및 그 방법 {Commercial Real Estate Simulator using Public data and Vehicle Analysis}Real estate investment decision-making simulator and method through unstructured data analysis {Commercial Real Estate Simulator using Public data and Vehicle Analysis}

본 발명은 마케팅을 위한 상권 분석을 위해서 비정형 데이터인 공공데이터 및 차량 인식등을 활용한 유동인구지수를 구축하여 활용하기 위한 상권 분석을 위한 지역별 유동인구 계층 세분화 관점에서 부동산 투자 의사 결정 시뮬레이터 시스템 및 그 방법에 관한 것이다.The present invention provides a real estate investment decision-making simulator system and its it's about how

일반적으로, 기업 활동에 따른 마케팅이나 중,소 규모의 상품 또는 서비스 판매 업체의 보다 효과적인 판매 전략 수립을 위해서는, 판매 시장에 대한 잠재력 정보를 정확하게 파악할 필요가 있고, 이를 위한 기본적인 정보로서 배후지의 인구 규모, 주변에 상주해 있는 직장인의 규모, 유동인구의 규모 및 소득 수준 등을 포함한 다량의 정보로서 파악할 필요가 있다.In general, in order to establish a more effective sales strategy for marketing according to corporate activities or small and medium-sized product or service vendors, it is necessary to accurately grasp potential information on the sales market, and for this purpose, as basic information, the population size of the hinterland , it is necessary to grasp it as a large amount of information including the size of the office workers residing in the vicinity, the size of the floating population, and the income level.

통상적으로, 상권에서 말하는 잠재고객은 주간상주 인구와, 야간상주 인구, 유동인구의 합을 의미하는 바, 직장근무자 등과 같이 해당 지역에 주간 시간대에 상주하는 주간상주 인구와, 해당 지역에 거주하는 야간상주 인구의 경우에는 업종과 무관하게 명확한 의미를 가지고 있으며 인구수의 파악이 용이한 반면에, 유동인구의 경우에는 업종별로 다르게 정의되어야 하며, 보통 점포 앞을 지나는 모든 인구를 중심으로 상권 잠재력을 계산하도록 되어 있으나 차량에 대한 분석 데이터가 포함되지 않아 실질적인 상권 분석을 위해서 유동인구지수 구축에 차량 정보 및 소득 수준을 포함한 많은 량의 통계 데이터가 추가해야 할 필요가 있다.In general, potential customers in commercial districts refer to the sum of the daytime resident population, the nighttime resident population, and the floating population. In the case of the resident population, it has a clear meaning regardless of the industry and it is easy to grasp the number of the population, whereas in the case of the floating population, it should be defined differently for each industry, and it is necessary to calculate the commercial potential based on all the people who usually pass in front of the store. However, it is necessary to add a large amount of statistical data, including vehicle information and income level, to the construction of the floating population index for actual commercial area analysis as it does not include vehicle analysis data.

그러나, 최근까지도 유동인구지수에 차량정보를 포함한 여러 지수의 공공데이터를 활용한 개발이 부족한 실정이다.However, until recently, development using public data of various indices including vehicle information in the floating population index was insufficient.

따라서, 본 발명은 상기한 종래의 사정을 감안하여 이루어진 것으로서, 그 목적은 지역별 유동인구 계층 세분화 관점에서 상권 분석을 위해 비정형 데이터 분석을 통한 부동산 투자 의사 결정 시뮬레이터를 통한 유동인구지수 구축 시스템 및 그 방법을 제공하는 것이다.Therefore, the present invention has been made in view of the above-mentioned conventional circumstances, and its purpose is to analyze the floating population by region in terms of segmentation of the floating population by region, and to analyze the floating population index through a real estate investment decision-making simulator through the analysis of unstructured data, and a method therefor is to provide

상기한 목적을 달성하기 위해 본 발명의 시스템에 따르면, 공개된 공공데이터의 한 종류인 지자체의 유동인구 데이터와 국토교통부의 공시지가 및 실거래가 정보 및 한국은행의 소득수준정보 데이터와 통계청의 산업계층별 통계데이터를 비롯하여 한국교통연구원의 대중교통 이용정보 데이터등을 포함하는 각종 공공데이터를 활용함과 더불어 cctv기반의 차량 유동 분석데이터등을 활용하여 보다 세밀한 유동인구 지수를 개발하여 지표로서 제시가 가능하다.According to the system of the present invention to achieve the above object, according to the system of the present invention, one type of public data that is public data, floating population data of local governments, official land price and actual transaction price information of the Ministry of Land, Infrastructure and Transport, income level information data of the Bank of Korea, and statistics by industry class of Statistics Korea It is possible to develop a more detailed floating population index and present it as an index by using various public data including data and public transportation usage information data of the Korea Transport Institute as well as cctv-based vehicle flow analysis data.

이상과 같이 본 발명에 따르면, 기존의 상권 분석보다 훨씬 세밀한 공개된 공공데이터를 활용하여 확률성이 높은 통계데이터로서 제공이 가능하고, 차량 통행 분석 데이터까지 더해짐으로서 차별화된 유동인구의 추정을 위한 기본 정보로서 충분히 활용이 가능하다는 효과를 갖게 된다.As described above, according to the present invention, it is possible to provide statistical data with high probability by utilizing public data that is much more detailed than existing commercial area analysis, and by adding vehicle traffic analysis data, it is the basis for estimating the differentiated floating population. It has the effect that it can be used sufficiently as information.

본 발명은 상업용 부동산의 상권 분석을 위해 공개된 공공데이터와 차량 인식 기술을 활용한 유동인구지수를 통하여, 유동인구지수에 근거한 실질적인 단위 지역의 유동인구지수 구축을 가능하게하여 그에 맞는 상권 분석을 위한 시스템 및 그 방법을 제공한다.
이를 위해 본 발명은 차량 인식 기술에 기초하여 특정 지역의 차량 분석을 통하여 차량 유동인구 데이터를 데이터 성격 등에 따라 재분류하고, 공개된 공공데이터를 활용하여 체류 차량 분석과 유동인파분석, 산업분포 및 부동산 지표와 세금의 소득 가중치와 산업별 소득 평균등을 분석하여 지역별 방문자의 소득수준 추정치 산출과 그 지역 거주자의 자산수준 분포 산출 및 해당 지역 근무자의 소득수준 분포 산출등을 생성하여 데이터베이스화를 통하여 세밀하고 계산된 자료로 유동지수를 산출하는 것으로 지역 단위의 유동인구지수 구축을 특징으로 한다.The present invention enables the construction of a floating population index of a practical unit area based on the floating population index through the floating population index using public data and vehicle recognition technology disclosed for the analysis of the commercial area of commercial real estate, so that the appropriate commercial area analysis A system and method are provided.
To this end, the present invention reclassifies vehicle floating population data according to data characteristics, etc. through vehicle analysis in a specific area based on vehicle recognition technology, and utilizes public data to analyze staying vehicles and floating population, industrial distribution and real estate By analyzing the income weight of indicators and taxes and the average income by industry, it is possible to calculate the estimated income level of visitors by region, the distribution of the wealth level of the residents of the region, and the income level distribution of the workers in the region, and make detailed calculations through databaseization. It is characterized by the construction of a floating population index at the regional level by calculating the floating index using the collected data.

이하, 상기한 바와 같이 구성된 본 발명에 대해 첨부도면을 참조하여 상세히 설명한다.Hereinafter, the present invention configured as described above will be described in detail with reference to the accompanying drawings.

Claims (4)

공개된 공공데이터에 기초하여 차량 분석과 부동산 분석 및 산업분석과 산업별 소득분석 및 세금기준 소득 가중치를 통하여 수집된 데이터를 해당 데이터의 종류에 따라 분석하여 각각 분석된 비정형 데이터값을 저장하고 처리하여 유동인구의 인자로서 추출하고, 각 유동인구의 인자에 의한 인구 유동량을 추출하여 분석을 통한 전문가용 데이터셋과;
이를 도식화함에 의해, 각 유동인구 인자별 정보를 각각 분석시스템을 통하여 유동인구지수보고서를 생성하는 비전문가용 리포트와;
상기 유동인구지수를 구축하여 지역별 소득분위와 평균소비여력 및 근무자 소득증감 및 공시지가와 실거래가등을 작성하는 산출부; 및
상기 배후유동규모의 정보와 상기 SND를 계산하여 소지역 단위의 유동인구지수를 구축하는 유동인구지수 구축부;
를 포함하여 구성된 것을 특징으로 하는 비정형 데이터 분석을 위한 부동산 투자 의사 결정 시뮬레이터 시스템.Based on the public data, the data collected through vehicle analysis, real estate analysis, industry analysis, industry-specific income analysis, and tax-based income weighting are analyzed according to the type of data, and the analyzed atypical data value is stored and processed to flow a data set for experts through analysis by extracting as a factor of the population and extracting the flow of the population by the factor of each floating population;
a report for non-experts that generates a floating population index report through an analysis system for each floating population factor information by diagrammatically;
a calculation unit for constructing the floating population index to create regional income deciles, average spending power, increase/decrease in worker income, and official land price and actual transaction price; and
a floating population index construction unit for constructing a floating population index for each sub-region by calculating the information on the background flow scale and the SND;
Real estate investment decision-making simulator system for unstructured data analysis, characterized in that it comprises a. 제 1 항에 있어서,
상기 데이터 저장 및 처리와 관리는
비정형 데이터의 저장으로 통계데이터와 데이터 집계부와,
지역유동 분석과 부동산 분석 및 산업과 소득분석의 처리부와,
유동량 통계와 상권 통계 및 비정형DB통계의 관리부 및;
전문가용 데이터셋부로 구성되는 시스템The method of claim 1,
The data storage, processing and management are
Statistical data and data aggregation unit for storage of unstructured data,
A processing unit of regional flow analysis, real estate analysis, and industry and income analysis;
Management department of flow statistics, commercial district statistics, and unstructured DB statistics;
A system composed of professional datasets 제 1 항에 있어서,
상기 데이터 분석 및 분석시스템은
차량의 움직임과 사람의 움직임으로 유동인구를 분석하는 추출부와,
소득 분위와 평균 소비여력을 통한 소득 분포부와,
근무자 소득증감과 거주 상황을 알수 있는 산업분포와,
공시지가 및 실거래가를 통한 시세부와,
이러한 데이터를 통해 추출한 비전문가용 리포트부로 구성되는 시스템The method of claim 1,
The data analysis and analysis system is
An extraction unit that analyzes the floating population based on the movement of the vehicle and the movement of the person;
Income distribution through income quintile and average spending power,
Industrial distribution that can know the increase in income and residence status of workers,
Market details through the official price and actual transaction price;
A system consisting of a report unit for non-professionals extracted from these data 제 1 항에 있어서,
상기 데이터 활용 분야는
대형 자산 운용사 및 중개법인에 Raw 데이터와 데이터셋을 데이터베이스화 시켜 제공하는 대형화와,
개인 및 기관을 위해 시인성을 높여 도표 및 그래프화를 통한 보고서로 유료 리포트화하는 중형화와,
금융권이나 기업 및 지자체등에 제공하기 위해 유료 분석 툴 및 리포트를 제공하는 확장판,
으로 구성되는 시스템The method of claim 1,
The field of data use is
Large-scale, providing raw data and datasets to large asset managers and brokerage firms as a database;
For individuals and institutions, a medium-sized report that increases visibility and converts it into a paid report through charts and graphs;
An extended version that provides paid analysis tools and reports to provide to the financial sector, corporations, and local governments;
system consisting of
KR2020200004097U 2020-11-12 2020-11-12 Commercial Real Estate Simulator using Public data and Vehicle Analysis KR20220001127U (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR102657597B1 (en) * 2023-11-27 2024-04-15 주식회사 아이큐 Real estate index platform system and real estate search device of interest using the same

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR102657597B1 (en) * 2023-11-27 2024-04-15 주식회사 아이큐 Real estate index platform system and real estate search device of interest using the same

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