Method and system for evaluating neighbourhood aging suitability based on multi-source data fusion

A method for evaluating neighbourhood aging suitability based on multi-source data fusion, comprising:

• S1, detecting a quantity of people entering and leaving a target neighbourhood by face recognition technology of each housing estate of the target neighbourhood, and detecting a quantity of elderly people leaving each housing estate of the target neighbourhood and a quantity of elderly people entering each housing estate of the target neighbourhood in a set period;
• S2, analyzing traffic suitability of the target neighbourhood:
• analyzing a mobility suitability coefficient of the elderly people corresponding to each housing estate of the target neighbourhood, and then analyzing a traffic convenience coefficient JB corresponding to the target neighbourhood accordingly;
• S3, evaluating perfection of leisure facilities of the target neighbourhood:
• obtaining an occupied region of each housing estate of the target neighbourhood, obtaining an area of the occupied region of each housing estate of the target neighbourhood, and analyzing a perfection coefficient ω of the leisure facilities corresponding to the target neighbourhood accordingly;
• S4, analyzing microenvironment suitability of the target neighbourhood:
• obtaining environmental parameters of each housing estate of the target neighbourhood, and then analyzing a microenvironment suitability coefficient HJ corresponding to the target neighbourhood accordingly;
• S5, evaluating aging suitability of the target neighbourhood:
• evaluating an evaluation coefficient of aging residential suitability corresponding to the target neighbourhood;
• and
• S6, processing the target neighbourhood:
• displaying the evaluation coefficient of aging residential suitability corresponding to the target neighbourhood.

The method for evaluating neighbourhood aging suitability based on multi-source data fusion according to claim 1, wherein the step of detecting a quantity of elderly people leaving each housing estate of the target neighbourhood and a quantity of elderly people entering each housing estate of the target neighbourhood in a set period comprises:

• obtaining a face image of each elderly people in each housing estate of the target neighbourhood;
• obtaining a face image collected by each exit of each housing estate of the target neighbourhood in the set period from a target neighbourhood management office, and analyzing a face image of each elderly people leaving each housing estate of the target neighbourhood;
• counting a quantity of the face images of the elderly people leaving each housing estate of the target neighbourhood, and taking the quantity of the face images as a quantity SLi of the elderly people leaving each housing estate of the target neighbourhood in the set period, wherein i is a serial number of each housing estate, and i=1, 2, . . . , n;
• and
• in a same way, obtaining a quantity JLi of the elderly people entering each housing estate of the target neighbourhood in the set period.

The method for evaluating neighbourhood aging suitability based on multi-source data fusion according to claim 3, wherein the step of analyzing a mobility suitability coefficient of elderly people corresponding to each housing estate of the target neighbourhood comprises:

• obtaining a quantity αi of residents in each housing estate of the target neighbourhood,
• obtaining a quantity βi of the elderly people in each housing estate of the target neighbourhood from the target neighbourhood management office, and then analyzing a proportion
• BP
• i
• =
• β
• i
• α
• i
• of the quantity of the elderly people in each housing estate of the target neighbourhood;
• comparing the proportion of the quantity of the elderly people in each housing estate of the target neighbourhood with a proportion range of a quantity of elderly people suitable for leaving in each unit time stored in a cloud database, and selecting a quantity of the elderly people suitable for leaving in each unit time corresponding to each housing estate of the target neighbourhood;
• multiplying the quantity of the elderly people suitable for leaving in each unit time corresponding to each housing estate with a duration corresponding to the set period to obtain a quantity SYi of the elderly people suitable for leaving corresponding to each housing estate;
• analyzing a suitability coefficient
• ε
• i
• =
• (
• e
• +
• 1
• )
• (
• SY
• i
• 1
• +
• ❘
• "\[LeftBracketingBar]"
• SL
• i
• -
• SY
• i
• ❘
• "\[RightBracketingBar]"
• )
• of the quantity of the elderly people suitable for leaving corresponding to each housing estate of the target neighbourhood, wherein e is a natural constant;
• in a same way, analyzing a suitability coefficient ηi of a quantity of elderly people suitable for entering corresponding to each housing estate of the target neighbourhood;
• and
• comprehensively analyzing the mobility suitability coefficient μi=√{square root over (εi*λ1+ηi*λ2)} of the elderly people suitable for leaving corresponding to each housing estate of the target neighbourhood, wherein λ1 and λ2 are preset influence weight factors respectively corresponding to the suitability coefficient of the quantity of the elderly people suitable for entering and the suitability coefficient of the quantity of the elderly people suitable for leaving.

The method for evaluating neighbourhood aging suitability based on multi-source data fusion according to claim 1, wherein the step of analyzing a traffic convenience coefficient corresponding to the target neighbourhood comprises:

• obtaining each bus station and each subway station corresponding to the target neighbourhood from a traffic management center to obtain a center point of the occupied area of each bus station corresponding to the target neighbourhood and a reference point of each subway station corresponding to the target neighbourhood, taking a serial number of each bus station as 1, 2 . . . , m, . . . , l, and taking a serial number of each subway station as 1, 2 . . . , p, . . . , q;
• analyzing a traffic distance suitability coefficient ωi corresponding to each housing estate of the target neighbourhood;
• and
• comprehensively analyzing the traffic convenience coefficient
• JB
• =
• ln
• ⁢
• (
• 1
• +
• 1
• n
• ⁢
• ∑
• i
• =
• 1
• n
• μ
• i
• *
• γ
• 1
• +
• 1
• n
• ⁢
• ∑
• i
• =
• 1
• n
• ω
• _
• i
• *
• γ
• 2
• +
• σ
• *
• γ
• 3
• )
• corresponding to the target neighbourhood, wherein σ is a traffic line patency coefficient of the target neighbourhood, and γ1, γ2 and γ3 are preset proportion factors respectively corresponding to mobility suitability of elderly people, traffic distance suitability of elderly people, and traffic line patency of elderly people.

The method for evaluating neighbourhood aging suitability based on multi-source data fusion according to claim 5, wherein a method for analyzing the traffic line patency coefficient σ of the target neighbourhood comprises:

• obtaining a quantity TImk of nodes of each bus line corresponding to each bus station of the target neighbourhood from the target neighbourhood, wherein k is a serial number of each bus line, k=1, 2, . . . , j;
• according to the quantity of the nodes corresponding to each bus line of each bus station corresponding to the target neighbourhood, extracting a quantity
• TI
• m
• max
• of maximum nodes and a quantity
• TI
• m
• min
• of minimum nodes of each bus station of the target neighbourhood;
• counting a quantity DIm of the bus lines of each bus station of the target neighbourhood;
• obtaining a quantity DYp of nodes of each subway station corresponding to the target neighbourhood;
• analyzing the traffic line patency coefficient
• σ
• =
• χ
• 1
• *
• 1
• l
• ⁢
• ∑
• m
• =
• 1
• l
• (
• 1
• j
• ⁢
• ∑
• m
• =
• 1
• j
• TI
• k
• TY
• )
• +
• χ
• 2
• *
• ∑
• m
• =
• 1
• l
• (
• TI
• ′
• TI
• m
• max
• -
• TI
• m
• min
• )
• +
• χ
• 3
• *
• DI
• m
• 1
• +
• DG
• ′
• +
• χ
• 4
• *
• DY
• p
• 1
• +
• DR
• ′
• of the target neighbourhood, wherein TI′ is a preset allowable error between the quantity of maximum nodes and the quantity of minimum nodes of the bus station, j is a quantity of the bus lines, l is a quantity of bus stations, TY′ is an average value of the quantity of nodes of the bus station corresponding to the target neighbourhood, DG′ is an average value of the quantity of nodes of the bus line corresponding to the target neighbourhood, DR′ an average value of the quantity of nodes of the subway station corresponding to the target neighbourhood, and χ1, χ2, χ3, and χ4 are preset proportion factors respectively corresponding to the quantity of nodes of the bus line, the quantity of maximum nodes and the quantity of minimum nodes, the quantity of bus lines, and the quantity of nodes of the subway station.

The method for evaluating neighbourhood aging suitability based on multi-source data fusion according to claim 1, wherein a method for analyzing the leisure facility perfection coefficient corresponding to the target neighbourhood comprises:

• obtaining an area of each leisure facility region corresponding to the target neighbourhood, and then summarizing the area to obtain a total area S′ of the leisure facility region of the target neighbourhood;
• counting a quantity U of the leisure facility regions corresponding to the target neighbourhood;
• counting an area of the occupied region of each housing estate of the target neighbourhood, and summarizing the area to obtain a total area S′ of the occupied region of the housing estate of the target neighbourhood;
• extracting a total area SF of the leisure facility regions, a total area SF′ of the occupied regions of the housing estate, and a quantity U′ of the leisure facility regions in a standard aging suitable neighbourhood from a cloud database;
• and
• analyzing the leisure facility perfection coefficient
• ω
• =
• (
• S
• ⁢
• F
• ″
• 1
• +
• ❘
• "\[LeftBracketingBar]"
• S
• S
• ′
• -
• SF
• SF
• ′
• ❘
• "\[RightBracketingBar]"
• *
• δ
• 1
• +
• U
• ′
• 1
• +
• ❘
• "\[LeftBracketingBar]"
• U
• -
• U
• ′
• ❘
• "\[RightBracketingBar]"
• *
• δ
• 2
• )
• 1
• 2
• corresponding to the target neighbourhood, wherein SF″ is a preset allowable error of an area ratio of the leisure facility regions, and δ1 and δ2 are preset weight coefficients respectively corresponding to the area ratio of the leisure facility regions and the quantity of the leisure facility regions.

The method for evaluating neighbourhood aging suitability based on multi-source data fusion according to claim 2, wherein a method for analyzing the microenvironment suitability coefficient corresponding to the target neighbourhood comprises:

• extracting the carbon dioxide concentration, the sound decibel, and the PM2.5 value corresponding to each layout point at each detection time point from the environmental parameters of each housing estate of the target neighbourhood;
• according to a predefined range of carbon dioxide concentration, a predefined upper limit of sound decibel, and a predefined range of PM2.5 value corresponding to the standard aging suitable neighbourhood;
• according to the sound decibel corresponding to each layout point of each housing estate of the target neighbourhood at each detection time point, analyzing a noise pollution index Zi corresponding to each housing estate of the target neighbourhood;
• according to the carbon dioxide concentration of each layout point of each housing estate of the target neighbourhood at each detection time point and the range of carbon dioxide concentration corresponding to the standard aging suitable neighbourhood, analyzing a carbon dioxide concentration suitability coefficient ϑi corresponding to the each housing estate of the target neighbourhood;
• in a same way, according to the PM2.5 value of each layout point of each housing estate of the target neighbourhood at each detection time point, analyzing an air quality index Qi corresponding to each housing estate of the target neighbourhood;
• and
• analyzing the microenvironment suitability coefficient
• HJ
• =
• 1
• n
• ⁢
• ∑
• i
• =
• 1
• n
• (
• e
• +
• 1
• )
• (
• 1
• Z
• i
• +
• ϑ
• i
• +
• Q
• i
• )
• corresponding to the target neighbourhood.

The method for evaluating neighbourhood aging suitability based on multi-source data fusion according to claim 1, wherein the evaluation coefficient of the aging residential suitability corresponding to the target neighbourhood is calculated by a equation:

• ψ
• =
• (
• e
• -
• 1
• )
• (
• JB
• *
• ρ
• 1
• +
• ω
• *
• ρ
• 2
• +
• HJ
• *
• ρ
• 3
• )
• ,
• wherein ρ1, ρ2, and ρ3 are preset weight factors respectively corresponding to the traffic suitability, the leisure facility perfection, and the microenvironment suitability.

A system for evaluating neighbourhood aging suitability based on multi-source data fusion, comprising:

• a target neighbourhood detecting module of a quantity of people entering and leaving, used for detecting a quantity of elderly people leaving each housing estate of a target neighbourhood and a quantity of elderly people entering each housing estate of the target neighbourhood in a set period, by face recognition technology of each housing estate of the target neighbourhood;
• a target neighbourhood analyzing module of neighbourhood traffic suitability, used for analyzing a mobility suitability coefficient of elderly people corresponding to each housing estate of the target neighbourhood, and then analyzing a traffic convenience coefficient JB corresponding to the target neighbourhood accordingly;
• a target neighbourhood evaluating module of leisure facility perfection, used for obtaining an occupied region of each housing estate of the target neighbourhood, obtaining an occupied area of each leisure district of the target neighbourhood, and analyzing a leisure facility perfection coefficient ω corresponding to the target neighbourhood accordingly;
• a target neighbourhood analyzing module of microenvironment suitability, used for obtaining environmental parameters of each housing estate of the target neighbourhood, and then analyzing a microenvironment suitability coefficient HJ corresponding to the target neighbourhood accordingly;
• a target neighbourhood evaluating module of aging suitability, used for evaluating an evaluation coefficient of aging residential suitability corresponding to the target neighbourhood;
• a target neighbourhood processing module, used for displaying the evaluation coefficient of aging residential suitability corresponding to the target neighbourhood;
• and
• a cloud database, used for storing a proportion range of a quantity of elderly people suitable for leaving in each unit time, and storing a total area of leisure facility regions of a standard aging suitable neighbourhood, a total area of the occupied regions of the housing estate of the standard aging suitable neighbourhood, and a quantity of the leisure facility regions of the standard aging suitable neighbourhood.