CN113284606A - Home-based aged care intelligent management method and system based on remote monitoring data analysis and computer storage medium - Google Patents
Home-based aged care intelligent management method and system based on remote monitoring data analysis and computer storage medium Download PDFInfo
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- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
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Abstract
The invention discloses a home-based and old-age care intelligent management method and system based on remote monitoring data analysis and a computer storage medium. The intelligent management method for home care based on remote monitoring data analysis comprises the following steps: acquiring the number of family care personnel corresponding to the area; acquiring basic information corresponding to each family senior citizen in the area; acquiring historical health detection information, historical movement detection information and historical service information corresponding to each family senior citizen; analyzing the acquired historical health detection information, historical movement detection information and historical service information corresponding to each family senior citizen; the method effectively solves the problem that the existing management method for the home-based care workers does not analyze the real-time dynamic information corresponding to each home-based care worker, greatly improves the management efficiency of each home-based care worker, and effectively ensures the real-time safety of each home-based care worker.
Description
Technical Field
The invention belongs to the technical field of endowment management, and relates to a home endowment intelligent management method and system based on remote monitoring data analysis and a computer storage medium.
Background
With the increasingly prominent aging problem of population, the number of endowment modes is gradually increased, and in the numerous endowment modes, the best endowment mode for the old people is when the old people live at home for endowment, and in order to guarantee the health and safety of the home-based endowment people, the home-based endowment people need to be managed;
the existing management method for home-based care personnel mainly comprises the steps that the home-based care personnel are located in a community service center for regular home service and management, and it is obvious that the existing management method for home-based care personnel cannot acquire real-time dynamic information of each home-based care personnel, so that the existing management method for home-based care personnel still has certain disadvantages.
Disclosure of Invention
In view of the above, in order to solve the problems in the background art, a method, a system and a computer storage medium for intelligent management of home care based on remote monitoring data analysis are provided, so as to realize intelligent management of home care personnel;
the purpose of the invention can be realized by the following technical scheme:
the invention provides a home-based aged care intelligent management method based on remote monitoring data analysis, which comprises the following steps:
s1, acquiring the number of the aged: counting the number of the home-based care workers in the area through a personnel number counting module, further acquiring the number corresponding to the home-based care workers in the area, and further numbering the home-based care workers in the area according to a preset sequence, wherein the numbers are sequentially marked as 1, 2,. j,. m;
s2, acquiring basic information of personnel: basic information corresponding to each family senior citizen in the area is acquired through a personnel basic information acquisition module, wherein the basic information comprises names, household position information and area service contact ways, and then a basic information set B of each family senior citizen is constructedw(Bw1,Bw2,...Bwj,...Bwm)，Bwj represents the w-th basic information corresponding to the j-th family senior citizen, w represents the familyBasic information corresponding to domestic elders, wherein w is a1, a2, a3, a1, a2 and a3 respectively represent names, resident position information and contact addresses of regional service centers;
s3, acquiring historical health detection information: acquiring historical health detection information corresponding to each home-based elderly person through a historical health detection information acquisition module, further counting the historical health detection times of each home-based elderly person, numbering the historical health detection times corresponding to each home-based elderly person according to a preset sequence, and sequentially marking the historical health detection times as 1, 2,. i,. n;
s4, obtaining historical motion detection information: historical movement detection information corresponding to each home-based elderly person in the area is obtained through a historical movement detection information obtaining module, so that the historical movement detection times of each home-based elderly person in the area are obtained, the historical movement detection times of each home-based elderly person in the area are numbered according to a preset sequence, and the numbers are marked as 1, 2,. f,. h in sequence;
s5, obtaining historical service information: acquiring historical service information corresponding to each family senior citizen in the region through a historical service information acquisition module, wherein the historical service information comprises service categories, service time points and service times;
s6, data processing and analysis: and analyzing historical health detection information, historical movement detection information and historical service information corresponding to each family senior citizen in the region through the cloud platform processing center.
Further, the historical health detection information comprises a plurality of basic health detection parameters, the basic health detection parameters are numbered according to a preset sequence and are sequentially marked as 1, 2, 1.. x, y, and then the numerical values corresponding to the basic health detection parameters are obtained, and then each basic health detection parameter set J of each historical health detection of each home-based elderly person is constructedr t(Jr t1,Jr t2,...,Jr tj,...Jr tm)，Jr tj represents a numerical value corresponding to the r-th basic health detection parameter of the jth historical health detection of the jth family senior citizen, r represents a basic health detection parameter number, and r is 1, 2.x,. y, t represents the number of the historical health check times, and t is 1, 2,. i,. n.
Further, the historical motion detection information comprises the motion step number and the outgoing duration, and then each historical motion detection information set Y of each family senior citizen is constructede v(Ye v1,Ye v2,...,Ye vj,...Ye vm)，Ye vj represents the e-th movement information corresponding to the j-th home-based elderly person during the v-th historical movement detection, e represents movement, e is b1, b2, b1 and b2 respectively represent the movement step number and the outgoing time length, v represents the historical movement detection number, and v is 1, 2.
Further, the data processing and analysis are used for analyzing historical health detection information corresponding to each family care worker in the area, and the specific analysis process comprises the following steps:
a1, acquiring a basic health detection parameter set of each historical health detection of each home-based care worker, and further acquiring a numerical value corresponding to each basic health detection parameter of each historical health detection of each home-based care worker;
a2, comparing the corresponding value of each basic health detection parameter of each historical health detection of each family old man with the corresponding standard value of each basic health detection parameter, if the corresponding value of a basic health detection parameter of a certain family old man does not belong to the corresponding standard value of the basic health detection parameter during a certain historical health detection, marking the basic health parameter as an abnormal basic health parameter, marking the health detection as abnormal health detection, and further counting the number of times of the historical abnormal health detection of each family old man and the number of the abnormal basic health detection parameters;
a3, according to the counted times of the historical abnormal health detection of each family senior citizen, further counting the influence coefficient of the abnormal detection times of each family senior citizen in the area
αdIndicates the d-th family member of the areaInfluence coefficient of abnormality detection frequency, p, for old persondIndicates the number of times of historical abnormal health detection corresponding to the d-th family senior citizen in the area, ndRepresenting the historical health detection times corresponding to the d-th family senior citizen in the area, wherein d represents the serial number of the family senior citizen, and d is 1, 2,. j,. m;
a4, comparing the abnormal basic health detection parameter quantity of each home-based elderly care person with the healthy basic parameter quantity of each home-based elderly care person according to the counted abnormal basic health detection parameter quantity of each home-based elderly care person, and counting the quantity influence coefficient of the abnormal healthy basic detection parameter quantity of each home-based elderly care person in the area, wherein the calculation formula is
δdAn influence coefficient q representing the number of abnormal basic health detection parameters of the d-th family elderly person in the areadIndicates the number of abnormal basic health detection parameters of the d-th family aged-care personnel in the area, ydThe number of basic health detection parameters corresponding to the d-th family care personnel in the area is represented;
a5, according to the influence coefficient of the abnormal detection times of the home-aged people in the area and the influence coefficient of the abnormal health basic detection parameter quantity of the home-aged people in the area, further counting the comprehensive health influence coefficient of the home-aged people in the area, wherein the calculation formula is
λdAnd the comprehensive health influence coefficient corresponding to the d-th family care worker in the region is shown.
Further, the data processing and analysis are used for analyzing historical movement detection information corresponding to each family senior citizen in the area, and the specific analysis process comprises the following steps:
b1, acquiring a motion detection information set of each historical motion detection of each home-based elderly person, and further acquiring the motion step number and the outgoing time length corresponding to each historical motion detection of each home-based elderly person in the area;
b2, comparing the motion step number corresponding to each historical motion detection of each home-based elderly person with the average motion step number corresponding to the elderly person according to the motion step number corresponding to each historical motion detection of each home-based elderly person, and counting the motion step number influence coefficient of each home-based elderly person in the area, wherein the calculation formula is
φdB1 representing the influence coefficient of the number of steps of exercise corresponding to the d-th family member in the aread vRepresents the motion step number corresponding to the v-th historical motion detection of the d-th family senior citizen in the area,
the average movement step number corresponding to the aged-care personnel is represented, and h represents the historical movement detection times;
b3, according to the corresponding outgoing time length of each time of historical motion detection of each home-based elderly person, comparing the corresponding outgoing time length of each time of historical motion detection of each home-based elderly person with the average outgoing time length corresponding to the elderly person, and further counting the outgoing time length influence coefficient of each home-based elderly person in the area, wherein the calculation formula is
B2, which represents the influence coefficient of the length of time of the person who is at home and the old in the aread vRepresents the outgoing time corresponding to the v-th historical motion detection of the d-th family senior citizen in the area,
representing the average outgoing time corresponding to the senior citizens;
b4, further counting the influence coefficients of the number of steps of the movement of each family care person in the area and the outgoing time length of each family care person in the area according to the counted influence coefficientsThe comprehensive motion influence coefficient of each family senior citizen in each domain has a calculation formula of
γdAnd the comprehensive motion influence coefficient corresponding to the d-th family elderly person in the area is shown.
Further, the data processing and analysis are used for analyzing historical service information corresponding to each family senior citizen in the area, and the specific analysis process comprises the following steps:
c1, acquiring historical service categories, historical service time points and historical service times corresponding to each home-based elderly person in the area, numbering the historical service times corresponding to each home-based elderly person in the area according to a preset sequence, and sequentially marking the historical service times as 1, 2,. k,. g;
c2, according to the service type corresponding to each historical service of each home-based senior citizen in the area, matching and comparing the service type corresponding to each historical service of each home-based senior citizen with the service type corresponding to each service level stored in the database, and further acquiring the service level corresponding to each historical service of each home-based senior citizen in the area;
c3, comparing and screening service levels corresponding to each historical service of the regional home-based elderly people, further counting the historical service times corresponding to each service level of each home-based elderly people in the region, according to the historical service times corresponding to each service level of each home-based elderly people in the region, further taking the service level with the most service times of each home-based elderly people in the region as the preferred service level, according to the preferred service level corresponding to each home-based elderly people in the region, further extracting the service demand influence coefficient corresponding to each service level from the database, further acquiring the service demand influence coefficient corresponding to the preferred service level of each home-based elderly people in the region, and recording the service demand influence coefficient as mu;
c4, according to the service time point corresponding to each historical service of each home care provider in the area, further acquiring the average service time interval corresponding to each home care provider in the area, and dividing the average service time interval corresponding to each home care provider in the areaComparing the standard service time intervals corresponding to the aged-care personnel, and then counting the service demand influence coefficients corresponding to the service time intervals of the home aged-care personnel in the region, wherein the calculation formula is
ηdRepresents the service demand influence coefficient, T, corresponding to the service time interval of the d-th family senior citizenStandard of meritIndicating the standard service interval, T, corresponding to the elderlydRepresenting the average service time interval corresponding to the d-th family senior citizen;
c5, further according to the service demand influence coefficient corresponding to the service time interval of each home-based care provider in the area and the service demand influence coefficient corresponding to the preferred service level of each home-based care provider in the area, further making statistics on the comprehensive service demand influence coefficient of each home-based care provider in the area, wherein the calculation formula is
And the comprehensive service demand influence coefficient corresponding to the d-th family care personnel in the region is shown.
Further, the data processing and analysis is also used for comprehensively analyzing historical health detection information, historical movement detection information and historical service information corresponding to each family care person in the area, and further counting comprehensive attention-required influence coefficients of each family care person in the area, wherein the calculation formula is
GdThe comprehensive attention-required influence coefficient that shows that this regional d family endowment person corresponds synthesizes according to this regional each family endowment person and needs attention-required influence coefficient, and then with this regional each family endowment person synthesize need attention-required influence coefficient and sort according to order from big to little, and then extract the first family endowment person who ranks, mark this family endowment person as attention-required endowment person, extract this closeAnd annotating the number corresponding to the aged person, and further acquiring the name, the resident position information and the regional service center contact way corresponding to the concerned aged person.
Further, the method further comprises the step of sending information, wherein the obtained name and resident position information corresponding to the career concerned are sent to a manager of the regional service center corresponding to the career concerned through a remote control center.
The invention provides a home-based old-age care intelligent management system based on remote monitoring data analysis, which comprises a personnel quantity counting module, a personnel basic information acquisition module, a historical health detection information acquisition module, a historical motion detection information acquisition module, a historical service information acquisition module, a cloud platform processing center, a database and a remote control center, wherein the cloud platform processing center is respectively connected with the personnel basic information acquisition module, the historical health detection information acquisition module, the historical motion detection information acquisition module, the historical service information acquisition module and the remote control center, and the personnel basic information acquisition module is connected with the personnel quantity counting module.
A third aspect of the present invention provides a computer storage medium, in which a computer program is burned, and when the computer program runs in a memory of a server, the computer program implements the method according to any one of the above-mentioned embodiments.
The invention has the beneficial effects that:
(1) according to the intelligent management method for home-based care of the old people based on remote monitoring data analysis, the historical health detection information, the historical motion detection information and the historical service information of each home-based care of the old people are comprehensively analyzed, so that the problem that the existing management method for the home-based care of the old people cannot analyze the real-time dynamic information corresponding to each home-based care of the old people and further cannot acquire the service demand degree and the health information corresponding to each home-based care of the old people is effectively solved, the management efficiency of each home-based care of the old people is greatly improved, and meanwhile, the real-time safety of each home-based care of the old people is effectively guaranteed.
(2) When historical movement monitoring information corresponding to each family senior citizen is analyzed, the mental states corresponding to each family senior citizen are effectively obtained by obtaining the movement step number and the outgoing time length corresponding to each family senior citizen, and a powerful data basis is provided for the follow-up comprehensive attention-needing analysis of the family senior citizen in the area;
(3) according to the method and the system, the acquired name and resident position information corresponding to the concerned aged-care person are sent to the regional service center corresponding to the concerned aged-care person, so that the management efficiency of the service center of the region where each family aged-care person is located on each family aged-care person is greatly improved, the occurrence probability of accidental potential safety hazard accidents of the concerned aged-care person at home is effectively reduced, the service effect on the family aged-care person is greatly improved, and the accurate service on each family aged-care person is realized.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a diagram of the steps of the method of the present invention;
FIG. 2 is a schematic diagram of the system connection of the present invention.
Detailed Description
While the foregoing is directed to embodiments of the present invention, other and further embodiments of the invention may be devised without departing from the basic scope thereof, and the scope thereof is determined by the claims that follow.
Referring to fig. 1, in a first aspect, the present invention provides a home-based intelligent management method for caring for the aged based on remote monitoring data analysis, including the following steps:
s1, acquiring the number of the aged: counting the number of the home-based care workers in the area through a personnel number counting module, further acquiring the number corresponding to the home-based care workers in the area, and further numbering the home-based care workers in the area according to a preset sequence, wherein the numbers are sequentially marked as 1, 2,. j,. m;
s2, acquiring basic information of personnel: basic information corresponding to each family senior citizen in the area is acquired through a personnel basic information acquisition module, wherein the basic information comprises names, household position information and area service contact ways, and then a basic information set B of each family senior citizen is constructedw(Bw1,Bw2,...Bwj,...Bwm)，Bwj represents the w-th basic information corresponding to the j-th home senior citizen, w represents the basic information corresponding to the home senior citizen, and w is a1, a2, a3, a1, a2 and a3 respectively represent name, resident location information and contact information of the regional service center;
s3, acquiring historical health detection information: acquiring historical health detection information corresponding to each home-based elderly person through a historical health detection information acquisition module, further counting the historical health detection times of each home-based elderly person, numbering the historical health detection times corresponding to each home-based elderly person according to a preset sequence, and sequentially marking the historical health detection times as 1, 2,. i,. n;
specifically, the historical health detection information comprises a plurality of basic health detection parameters, the basic health detection parameters are numbered according to a preset sequence and are sequentially marked as 1, 2,.. x,.. y, so that a numerical value corresponding to each basic health detection parameter is obtained, and then each basic health detection parameter set J of each historical health detection of each home-based elderly person is constructedr t(Jr t1,Jr t2,...,Jr tj,...Jr tm)，Jr tj represents a numerical value corresponding to the r-th basic health detection parameter of the jth home-based elderly people in the historical health detection, r represents a basic health detection parameter number, r is 1, 2,. x,. y, t represents a historical health detection frequency number, and t is 1, 2,. i,. n.
S4, obtaining historical motion detection information: historical movement detection information corresponding to each home-based elderly person in the area is obtained through a historical movement detection information obtaining module, so that the historical movement detection times of each home-based elderly person in the area are obtained, the historical movement detection times of each home-based elderly person in the area are numbered according to a preset sequence, and the numbers are marked as 1, 2,. f,. h in sequence;
specifically, the historical motion detection information comprises the number of motion steps and the length of outgoing time, and then each historical motion detection information set Y of each family senior citizen is constructede v(Ye v1,Ye v2,...,Ye vj,...Ye vm)，Ye vj represents the e-th movement information corresponding to the j-th home-based elderly person during the v-th historical movement detection, e represents movement, e is b1, b2, b1 and b2 respectively represent the movement step number and the outgoing time length, v represents the historical movement detection number, and v is 1, 2.
S5, obtaining historical service information: acquiring historical service information corresponding to each family senior citizen in the region through a historical service information acquisition module, wherein the historical service information comprises service categories, service time points and service times;
s6, data processing and analysis: analyzing historical health detection information, historical movement detection information and historical service information corresponding to each family senior citizen in the region through a cloud platform processing center;
specifically, the data processing and analyzing are used for analyzing historical health detection information corresponding to each family member in the area, and the specific analyzing process includes the following steps:
a1, acquiring a basic health detection parameter set of each historical health detection of each home-based care worker, and further acquiring a numerical value corresponding to each basic health detection parameter of each historical health detection of each home-based care worker;
a2, comparing the corresponding value of each basic health detection parameter of each historical health detection of each family old man with the corresponding standard value of each basic health detection parameter, if the corresponding value of a basic health detection parameter of a certain family old man does not belong to the corresponding standard value of the basic health detection parameter during a certain historical health detection, marking the basic health parameter as an abnormal basic health parameter, marking the health detection as abnormal health detection, and further counting the number of times of the historical abnormal health detection of each family old man and the number of the abnormal basic health detection parameters;
a3, according to the counted times of the historical abnormal health detection of each family senior citizen, further counting the influence coefficient of the abnormal detection times of each family senior citizen in the area
αdAn influence coefficient, p, of the number of abnormal detections corresponding to the d-th family member in the areadIndicates the number of times of historical abnormal health detection corresponding to the d-th family senior citizen in the area, ndRepresenting the historical health detection times corresponding to the d-th family senior citizen in the area, wherein d represents the serial number of the family senior citizen, and d is 1, 2,. j,. m;
a4, comparing the abnormal basic health detection parameter quantity of each home-based elderly care person with the healthy basic parameter quantity of each home-based elderly care person according to the counted abnormal basic health detection parameter quantity of each home-based elderly care person, and counting the quantity influence coefficient of the abnormal healthy basic detection parameter quantity of each home-based elderly care person in the area, wherein the calculation formula is
δdAn influence coefficient q representing the number of abnormal basic health detection parameters of the d-th family elderly person in the areadIndicates the number of abnormal basic health detection parameters of the d-th family aged-care personnel in the area, ydThe number of basic health detection parameters corresponding to the d-th family care personnel in the area is represented;
a5, calculating the influence coefficient of the abnormal detection times of the home-aged people in the area and the influence coefficient of the abnormal health basic detection parameter number of the home-aged people in the areaCounting, and further counting the comprehensive health influence coefficient of each family elderly care worker in the area, wherein the calculation formula is
λdAnd the comprehensive health influence coefficient corresponding to the d-th family care worker in the region is shown.
Specifically, the data processing and analyzing are used for analyzing historical movement detection information corresponding to each family senior citizen in the area, and the specific analyzing process includes the following steps:
b1, acquiring a motion detection information set of each historical motion detection of each home-based elderly person, and further acquiring the motion step number and the outgoing time length corresponding to each historical motion detection of each home-based elderly person in the area;
b2, comparing the motion step number corresponding to each historical motion detection of each home-based elderly person with the average motion step number corresponding to the elderly person according to the motion step number corresponding to each historical motion detection of each home-based elderly person, and counting the motion step number influence coefficient of each home-based elderly person in the area, wherein the calculation formula is
φdB1 representing the influence coefficient of the number of steps of exercise corresponding to the d-th family member in the aread vRepresents the motion step number corresponding to the v-th historical motion detection of the d-th family senior citizen in the area,
the average movement step number corresponding to the aged-care personnel is represented, and h represents the historical movement detection times;
b3, according to the corresponding outgoing time length of each time of historical motion detection of each home-based elderly person, comparing the corresponding outgoing time length of each time of historical motion detection of each home-based elderly person with the average outgoing time length corresponding to the elderly person, and further counting the outgoing time length influence coefficient of each home-based elderly person in the area, wherein the calculation formula is
B2, which represents the influence coefficient of the length of time of the person who is at home and the old in the aread vRepresents the outgoing time corresponding to the v-th historical motion detection of the d-th family senior citizen in the area,
representing the average outgoing time corresponding to the senior citizens;
b4, further carrying out statistics on the comprehensive motion influence coefficient of each home-based care person in the area according to the statistical influence coefficient of the motion step number of each home-based care person in the area and the statistical influence coefficient of the outgoing time length of each home-based care person in the area, wherein the calculation formula is
γdAnd the comprehensive motion influence coefficient corresponding to the d-th family elderly person in the area is shown.
When the embodiment of the invention is used for analyzing the historical movement monitoring information corresponding to each family elder, the mental states corresponding to each family elder are effectively obtained by obtaining the movement steps and the outgoing time length corresponding to each family elder, and a powerful data basis is provided for the follow-up comprehensive attention-needing analysis of the family elder in the area.
Specifically, the data processing and analysis are used for analyzing historical service information corresponding to each family senior citizen in the area, and the specific analysis process comprises the following steps:
c1, acquiring historical service categories, historical service time points and historical service times corresponding to each home-based elderly person in the area, numbering the historical service times corresponding to each home-based elderly person in the area according to a preset sequence, and sequentially marking the historical service times as 1, 2,. k,. g;
c2, according to the service type corresponding to each historical service of each home-based senior citizen in the area, matching and comparing the service type corresponding to each historical service of each home-based senior citizen with the service type corresponding to each service level stored in the database, and further acquiring the service level corresponding to each historical service of each home-based senior citizen in the area;
c3, comparing and screening service levels corresponding to each historical service of the regional home-based elderly people, further counting the historical service times corresponding to each service level of each home-based elderly people in the region, according to the historical service times corresponding to each service level of each home-based elderly people in the region, further taking the service level with the most service times of each home-based elderly people in the region as the preferred service level, according to the preferred service level corresponding to each home-based elderly people in the region, further extracting the service demand influence coefficient corresponding to each service level from the database, further acquiring the service demand influence coefficient corresponding to the preferred service level of each home-based elderly people in the region, and recording the service demand influence coefficient as mu;
c4, according to the service time point corresponding to each historical service of each home-based care provider in the area, further acquiring the average service time interval corresponding to each home-based care provider in the area, comparing the average service time interval corresponding to each home-based care provider in the area with the standard service time interval corresponding to the care provider, and further counting the service demand influence coefficient corresponding to each home-based care provider in the area, wherein the calculation formula is
ηdRepresents the service demand influence coefficient, T, corresponding to the service time interval of the d-th family senior citizenStandard of meritIndicating the standard service interval, T, corresponding to the elderlydRepresenting the average service time interval corresponding to the d-th family senior citizen;
c5, further according to the service demand influence coefficient corresponding to the service time interval of each home-based care provider in the area and the service demand influence coefficient corresponding to the preferred service level of each home-based care provider in the area, further making statistics on the comprehensive service demand influence coefficient of each home-based care provider in the area, wherein the calculation formula is
And the comprehensive service demand influence coefficient corresponding to the d-th family care personnel in the region is shown.
The data processing and analysis are also used for comprehensively analyzing historical health detection information, historical movement detection information and historical service information corresponding to each family care person in the area, and further counting comprehensive attention-required influence coefficients of each family care person in the area, wherein the calculation formula is
GdThe comprehensive attention-required influence coefficient that shows this regional d family endowment person corresponds, according to this regional each family endowment person synthesizes and needs to pay attention to influence coefficient, and then with this regional each family endowment person synthesize and need to pay attention to influence coefficient and order from big to small, and then extract the first family endowment person of rank, mark this family endowment person as the attention-required endowment person, extract the serial number that this attention-required endowment person corresponds, and then acquire the name that this attention-required endowment person corresponds, resident positional information and regional service center contact mode.
According to the embodiment of the invention, the historical health detection information, the historical motion detection information and the historical service information of each family senior citizen are comprehensively analyzed, so that the problem that the service demand degree and the health information corresponding to each family senior citizen cannot be acquired because the existing management method for the family senior citizen does not analyze the real-time dynamic information corresponding to each family senior citizen is effectively solved, the management efficiency of each family senior citizen is greatly improved, and the real-time safety of each family senior citizen is effectively ensured.
S7, information sending: and sending the acquired name and resident position information corresponding to the concerned elderly person to a manager of the regional service center corresponding to the concerned elderly person through a remote control center.
According to the embodiment of the invention, the acquired name and resident position information corresponding to the concerned aged-care person are sent to the regional service center corresponding to the concerned aged-care person, so that the management efficiency of the service center of the region where each family aged-care person is located on each family aged-care person is greatly improved, meanwhile, the occurrence probability of the accident potential safety hazard accident that the concerned aged-care person is independent at home is effectively reduced, the service effect on the family aged-care person is greatly improved, and the accurate service on each family aged-care person is realized.
Referring to fig. 2, a second aspect of the present invention provides a home-based care-of-the-elderly intelligent management system based on remote monitoring data analysis, including a staff number statistics module, a staff basic information acquisition module, a historical health detection information acquisition module, a historical motion detection information acquisition module, a historical service information acquisition module, a cloud platform processing center, a database and a remote control center, where the cloud platform processing center is respectively connected with the staff basic information acquisition module, the historical health detection information acquisition module, the historical motion detection information acquisition module, the historical service information acquisition module database and the remote control center, and the staff basic information acquisition module is connected with the staff number statistics module.
The database is used for storing standard numerical values corresponding to the basic health detection parameters, average movement steps corresponding to the senior citizens, average outgoing time corresponding to the senior citizens, service categories corresponding to the service levels, service demand influence coefficients corresponding to the service levels and standard service time intervals corresponding to the senior citizens.
A third aspect of the present invention provides a computer storage medium, in which a computer program is burned, and when the computer program runs in a memory of a server, the computer program implements the method according to any one of the above-mentioned embodiments.
The foregoing is merely exemplary and illustrative of the principles of the present invention and various modifications, additions and substitutions of the specific embodiments described herein may be made by those skilled in the art without departing from the principles of the present invention or exceeding the scope of the claims set forth herein.
Claims (10)
1. A home-based aged-care intelligent management method based on remote monitoring data analysis is characterized by comprising the following steps: the method comprises the following steps:
s1, acquiring the number of the aged: counting the number of the home-based care workers in the area through a personnel number counting module, further acquiring the number corresponding to the home-based care workers in the area, and further numbering the home-based care workers in the area according to a preset sequence, wherein the numbers are sequentially marked as 1, 2,. j,. m;
s2, acquiring basic information of personnel: basic information corresponding to each family senior citizen in the area is acquired through a personnel basic information acquisition module, wherein the basic information comprises names, household position information and area service contact ways, and then a basic information set B of each family senior citizen is constructedw(Bw1,Bw2,...Bwj,...Bwm)，Bwj represents the w-th basic information corresponding to the j-th home senior citizen, w represents the basic information corresponding to the home senior citizen, and w is a1, a2, a3, a1, a2 and a3 respectively represent name, resident location information and contact information of the regional service center;
s3, acquiring historical health detection information: acquiring historical health detection information corresponding to each home-based elderly person through a historical health detection information acquisition module, further counting the historical health detection times of each home-based elderly person, numbering the historical health detection times corresponding to each home-based elderly person according to a preset sequence, and sequentially marking the historical health detection times as 1, 2,. i,. n;
s4, obtaining historical motion detection information: historical movement detection information corresponding to each home-based elderly person in the area is obtained through a historical movement detection information obtaining module, so that the historical movement detection times of each home-based elderly person in the area are obtained, the historical movement detection times of each home-based elderly person in the area are numbered according to a preset sequence, and the numbers are marked as 1, 2,. f,. h in sequence;
s5, obtaining historical service information: acquiring historical service information corresponding to each family senior citizen in the region through a historical service information acquisition module, wherein the historical service information comprises service categories, service time points and service times;
s6, data processing and analysis: and analyzing historical health detection information, historical movement detection information and historical service information corresponding to each family senior citizen in the region through the cloud platform processing center.
2. The intelligent management method for home care based on remote monitoring data analysis according to claim 1, characterized in that: the historical health detection information comprises a plurality of basic health detection parameters, the basic health detection parameters are numbered according to a preset sequence and are marked as 1, 2, 1.. x.. y in sequence, then the numerical values corresponding to the basic health detection parameters are obtained, and then each basic health detection parameter set J of each historical health detection of each family senior citizen is constructedr t(Jr t1,Jr t2,...,Jr tj,...Jr tm)，Jr tj represents a numerical value corresponding to the r-th basic health detection parameter of the jth home-based elderly people in the historical health detection, r represents a basic health detection parameter number, r is 1, 2,. x,. y, t represents a historical health detection frequency number, and t is 1, 2,. i,. n.
3. The intelligent management method for home care based on remote monitoring data analysis according to claim 1, characterized in that: the historical motion detection information comprises the number of motion steps and the length of outgoing time, and then each historical motion detection information set Y of each family senior citizen is constructede v(Ye v1,Ye v2,...,Ye vj,...Ye vm)，Ye vj represents the e-th movement information corresponding to the jth home-based elderly person during the v-th historical movement detection, e represents movement, e is b1, b2, b1 and b2 respectively represent the movement step number and the outgoing time length, v represents the historical movement detection number of times, and v is 1, 2..h。
4. The intelligent management method for home care based on remote monitoring data analysis according to claim 1, characterized in that: the data processing and analysis are used for analyzing historical health detection information corresponding to each family care worker in the region, and the specific analysis process comprises the following steps:
a1, acquiring a basic health detection parameter set of each historical health detection of each home-based care worker, and further acquiring a numerical value corresponding to each basic health detection parameter of each historical health detection of each home-based care worker;
a2, comparing the corresponding value of each basic health detection parameter of each historical health detection of each family old man with the corresponding standard value of each basic health detection parameter, if the corresponding value of a basic health detection parameter of a certain family old man does not belong to the corresponding standard value of the basic health detection parameter during a certain historical health detection, marking the basic health parameter as an abnormal basic health parameter, marking the health detection as abnormal health detection, and further counting the number of times of the historical abnormal health detection of each family old man and the number of the abnormal basic health detection parameters;
a3, according to the counted times of the historical abnormal health detection of each family senior citizen, further counting the influence coefficient of the abnormal detection times of each family senior citizen in the area
αdAn influence coefficient, p, of the number of abnormal detections corresponding to the d-th family member in the areadIndicates the number of times of historical abnormal health detection corresponding to the d-th family senior citizen in the area, ndRepresenting the historical health detection times corresponding to the d-th family senior citizen in the area, wherein d represents the serial number of the family senior citizen, and d is 1, 2,. j,. m;
a4, further according to the counted number of the abnormal basic health detection parameters of each family senior citizen, the number of the abnormal basic health detection parameters of each family senior citizen and each family senior citizen are comparedThe quantity of the basic health parameters is compared, and then the quantity influence coefficient of the basic abnormal health detection parameters of each family elderly care worker in the area is counted, wherein the calculation formula is
δdAn influence coefficient q representing the number of abnormal basic health detection parameters of the d-th family elderly person in the areadIndicates the number of abnormal basic health detection parameters of the d-th family aged-care personnel in the area, ydThe number of basic health detection parameters corresponding to the d-th family care personnel in the area is represented;
a5, according to the influence coefficient of the abnormal detection times of the home-aged people in the area and the influence coefficient of the abnormal health basic detection parameter quantity of the home-aged people in the area, further counting the comprehensive health influence coefficient of the home-aged people in the area, wherein the calculation formula is
λdAnd the comprehensive health influence coefficient corresponding to the d-th family care worker in the region is shown.
5. The intelligent management method for home care based on remote monitoring data analysis according to claim 1, characterized in that: the data processing and analysis are used for analyzing historical movement detection information corresponding to each family senior citizen in the area, and the specific analysis process comprises the following steps:
b1, acquiring a motion detection information set of each historical motion detection of each home-based elderly person, and further acquiring the motion step number and the outgoing time length corresponding to each historical motion detection of each home-based elderly person in the area;
b2, comparing the motion step number corresponding to each historical motion detection of each home-based elderly person with the average motion step number corresponding to the elderly person according to the motion step number corresponding to each historical motion detection of each home-based elderly person, and counting the motion step number influence coefficient of each home-based elderly person in the area, wherein the calculation formula is
φdB1 representing the influence coefficient of the number of steps of exercise corresponding to the d-th family member in the aread vRepresents the motion step number corresponding to the v-th historical motion detection of the d-th family senior citizen in the area,
the average movement step number corresponding to the aged-care personnel is represented, and h represents the historical movement detection times;
b3, according to the corresponding outgoing time length of each time of historical motion detection of each home-based elderly person, comparing the corresponding outgoing time length of each time of historical motion detection of each home-based elderly person with the average outgoing time length corresponding to the elderly person, and further counting the outgoing time length influence coefficient of each home-based elderly person in the area, wherein the calculation formula is
B2, which represents the influence coefficient of the length of time of the person who is at home and the old in the aread vRepresents the outgoing time corresponding to the v-th historical motion detection of the d-th family senior citizen in the area,
representing the average outgoing time corresponding to the senior citizens;
b4, further carrying out statistics on the comprehensive motion influence coefficient of each home-based care person in the area according to the statistical influence coefficient of the motion step number of each home-based care person in the area and the statistical influence coefficient of the outgoing time length of each home-based care person in the area, wherein the calculation formula is
γdIndicates that the d-th family member in the area corresponds toThe overall motion influence coefficient of (2).
6. The intelligent management method for home care based on remote monitoring data analysis according to claim 1, characterized in that: the data processing and analysis are used for analyzing historical service information corresponding to each family senior citizen in the region, and the specific analysis process comprises the following steps:
c1, acquiring historical service categories, historical service time points and historical service times corresponding to each home-based elderly person in the area, numbering the historical service times corresponding to each home-based elderly person in the area according to a preset sequence, and sequentially marking the historical service times as 1, 2,. k,. g;
c2, according to the service type corresponding to each historical service of each home-based senior citizen in the area, matching and comparing the service type corresponding to each historical service of each home-based senior citizen with the service type corresponding to each service level stored in the database, and further acquiring the service level corresponding to each historical service of each home-based senior citizen in the area;
c3, comparing and screening service levels corresponding to each historical service of the regional home-based elderly people, further counting the historical service times corresponding to each service level of each home-based elderly people in the region, according to the historical service times corresponding to each service level of each home-based elderly people in the region, further taking the service level with the most service times of each home-based elderly people in the region as the preferred service level, according to the preferred service level corresponding to each home-based elderly people in the region, further extracting the service demand influence coefficient corresponding to each service level from the database, further acquiring the service demand influence coefficient corresponding to the preferred service level of each home-based elderly people in the region, and recording the service demand influence coefficient as mu;
c4, according to the service time point corresponding to each historical service of each home-based care provider in the area, further acquiring the average service time interval corresponding to each home-based care provider in the area, comparing the average service time interval corresponding to each home-based care provider in the area with the standard service time interval corresponding to the care provider, and further counting the service time of each home-based care provider in the areaThe service demand influence coefficient corresponding to the interval is calculated by the formula
ηdRepresents the service demand influence coefficient, T, corresponding to the service time interval of the d-th family senior citizenStandard of meritIndicating the standard service interval, T, corresponding to the elderlydRepresenting the average service time interval corresponding to the d-th family senior citizen;
c5, further according to the service demand influence coefficient corresponding to the service time interval of each home-based care provider in the area and the service demand influence coefficient corresponding to the preferred service level of each home-based care provider in the area, further making statistics on the comprehensive service demand influence coefficient of each home-based care provider in the area, wherein the calculation formula is
And the comprehensive service demand influence coefficient corresponding to the d-th family care personnel in the region is shown.
7. The intelligent management method for home care based on remote monitoring data analysis according to claim 1, characterized in that: the data processing and analysis is also used for comprehensively analyzing historical health detection information, historical movement detection information and historical service information corresponding to each family care person in the area, and further counting comprehensive attention-required influence coefficients of each family care person in the area, wherein the calculation formula is
GdThe comprehensive attention-required influence coefficients corresponding to the d-th home-based care personnel in the region are represented, the comprehensive attention-required influence coefficients of the home-based care personnel in the region are obtained, the comprehensive attention-required influence coefficients of the home-based care personnel in the region are sorted from large to small, and then the ranking is extractedThe first family endowment person records this family endowment person as the attention endowment person, extracts the serial number that this attention endowment person corresponds, and then acquires the name, resident positional information and the regional service center contact way that this attention endowment person corresponds.
8. The intelligent management method for home care based on remote monitoring data analysis according to claim 1, characterized in that: and sending the information, namely sending the acquired name and resident position information corresponding to the concerned pension aged-care person to a manager of the regional service center corresponding to the concerned pension aged-care person through a remote control center.
9. The utility model provides a house endowment intelligent management system based on remote monitoring data analysis which characterized in that: the system comprises a personnel number counting module, a personnel basic information acquisition module, a historical health detection information acquisition module, a historical movement detection information acquisition module, a historical service information acquisition module, a cloud platform processing center, a database and a remote control center, wherein the cloud platform processing center is respectively connected with the personnel basic information acquisition module, the historical movement detection information acquisition module, the historical service information acquisition module database and the remote control center, and the personnel basic information acquisition module is connected with the personnel number counting module.
10. A computer storage medium, wherein a computer program is burned into the computer storage medium, and when the computer program runs in a memory of a server, the computer program implements the method according to any one of claims 1 to 8.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114023037A (en) * | 2021-10-19 | 2022-02-08 | 深圳市中博科创信息技术有限公司 | User safety early warning method and device, electronic equipment and readable storage medium |
| CN114723597A (en) * | 2022-04-08 | 2022-07-08 | 江苏中科西北星信息科技有限公司 | Smart home old-age care method and system |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114023037A (en) * | 2021-10-19 | 2022-02-08 | 深圳市中博科创信息技术有限公司 | User safety early warning method and device, electronic equipment and readable storage medium |
| CN114723597A (en) * | 2022-04-08 | 2022-07-08 | 江苏中科西北星信息科技有限公司 | Smart home old-age care method and system |
| CN114723597B (en) * | 2022-04-08 | 2023-09-15 | 江苏中科西北星信息科技有限公司 | Intelligent home-based care method and system |
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