CN111584020A - Personal healthy life big data acquisition and analysis system - Google Patents

Personal healthy life big data acquisition and analysis system Download PDF

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CN111584020A
CN111584020A CN202010364874.0A CN202010364874A CN111584020A CN 111584020 A CN111584020 A CN 111584020A CN 202010364874 A CN202010364874 A CN 202010364874A CN 111584020 A CN111584020 A CN 111584020A
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张建春
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Hubei Lanzhou Health Technology Co ltd
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Abstract

The invention discloses a big data acquisition and analysis system for personal healthy life, belonging to the technical field of big data analysis, comprising a data acquisition module for acquiring life data, a data analysis module for analyzing the acquired data, a central control module for controlling the system, an analysis and verification module for verifying an analysis result and a suggestion reminding module for proposing a relevant life quality improvement suggestion, the invention is scientific and reasonable, is safe and convenient to use, acquires and analyzes diet data, rest data and motion data in personal life through the data analysis module, so that the personal life can be intuitively understood through the form of data, the invention is more beneficial to giving corresponding suggestions and suggestions according to the data display of personal life habits and is beneficial to improving life quality, improving body health.

Description

Personal healthy life big data acquisition and analysis system
Technical Field
The invention relates to the technical field of big data analysis, in particular to a system for acquiring and analyzing big data of personal healthy life.
Background
With the continuous development of social economy, the substance level of people is also continuously improved, and with the continuous improvement of the substance level of people, overeating, irregular work and rest and lack of sports, the body of the current young people is in a sub-health state and harms the body of the current young people, and the current young people are not aware of the harm of the current living habits to the body;
the coming of the big data era can exactly predict and evaluate the physical state of the current young people by collecting the data of the living habits of people, and pushes related advice information to the young people collecting the related data according to the analysis and prediction results of the big data, thereby being beneficial to the current young people to adjust the living habits according to the advice information and improving the physical state;
therefore, a personal health big data collecting and analyzing system is urgently needed to solve the problems.
Disclosure of Invention
The invention aims to provide a personal health life big data acquisition and analysis system to solve the problems in the prior art.
In order to achieve the purpose, the invention provides the following technical scheme: a big data acquisition and analysis system for personal health life comprises a data acquisition module, a data analysis module, a central control module, an analysis and verification module and a suggestion reminding module;
the data acquisition module is used for acquiring various data of personal health life big data analysis, the data analysis module is used for analyzing the personal health life data acquired by the data acquisition module, the central control module is used for controlling the big data acquisition and analysis system, the analysis verification module is used for verifying the analysis result according to the big data analysis result and historical analysis data, so that the current analysis result can be verified according to the historical analysis data, the accuracy of the current big data analysis result is confirmed, and the suggestion reminding module is used for proposing a suggestion for improving life quality to an individual according to the analysis result, so that the life habit of the current young person can be improved on the big data analysis result, and the physical state of the current young person is improved;
the output end of the data acquisition module is connected with the input end of the data analysis module, the output end of the data analysis module is connected with the input end of the central control module, and the output end of the central control module is connected with the input ends of the analysis and verification module and the suggestion reminding module.
According to the technical scheme, the data acquisition module comprises a diet data acquisition unit, a work and rest data acquisition unit and a motion data acquisition unit;
the diet data acquisition unit is used for acquiring individual diet data, including times M of ordering through the ordering platform and time T of ordering through the ordering platform1The work and rest data acquisition unit is used for acquiring personal work and rest data, including the power consumption rate V of the mobile phone, and the motion data acquisition unit is used for acquiring personal motion data including the motion duration T3And miles of exercise L;
the output ends of the diet data acquisition unit, the work and rest data acquisition unit and the exercise data acquisition unit are all connected with the input end of the data analysis module.
According to the technical scheme, the data analysis module comprises a diet data analysis unit, a work and rest data analysis unit and a motion data analysis unit;
the diet data analysis unit is used for analyzing the individual diet data collected by the diet data collection unit, and whether the individual diet habits accord with the normal diet rules or not can be obtained through the analysis of the diet data;
the output end of the diet data acquisition unit is connected with the input end of the diet data analysis unit, the output end of the work and rest data acquisition unit is connected with the input end of the work and rest data analysis unit, and the output end of the motion data acquisition unit is connected with the input end of the motion data analysis unit.
According to the technical scheme, the central control module comprises a central controller, a time recording unit and a storage database;
the central controller is used for intelligently controlling the whole system, the time recording unit is used for recording various times in the data acquisition process of the system, and the storage database is used for storing the acquired and analyzed data, so that the later retrieval and checking are facilitated;
the output end of the central processing unit is connected with the input end of the storage database, and the output end of the time recording unit is connected with the input end of the central controller.
According to the above technical solution, the diet data analysis unit analyzes the diet data as follows:
the diet data analysis unit is used for collecting the time T of the individual ordering through the ordering platform every month1Composing a set of times
Figure BDA0002476222230000041
Figure BDA0002476222230000042
Wherein,
Figure BDA0002476222230000043
respectively representing the time point of each meal ordering;
the average time interval for the individual to order through the ordering platform each month is calculated according to the following formula:
Figure BDA0002476222230000044
wherein,
Figure BDA0002476222230000045
representing the average time interval of the individual to order through the ordering platform each month;
the results of the individual dietary data analysis were calculated according to the following formula:
Figure BDA0002476222230000046
wherein Q is1Represents the individual diet data score, and a represents the diet data score coefficient.
According to the technical scheme, the work and rest data analysis unit analyzes the work and rest data as follows:
the work and rest data analysis unit confirms work and rest time through analysis of power consumption rate V of the mobile phone, and the power consumption rate V of the mobile phone is calculated through the electric quantity P of the mobile phone at intervals of time tiDetecting to form the power set P ═ { P ═ P of the mobile phone1,P2,P3,...,PxIn which P is1,P2,P3,...,PxRespectively representing the mobile phone electric quantity of each time point, recording the time points of detecting the electric quantity, and forming a time set for detecting the mobile phone electric quantity
Figure BDA0002476222230000051
Figure BDA0002476222230000052
Wherein,
Figure BDA0002476222230000053
respectively representing each time point for detecting the electric quantity of the mobile phone;
calculating the power consumption rate of the mobile phone at intervals of time t according to the following formula:
Figure BDA0002476222230000054
wherein, ViIndicating that the mobile phone is
Figure BDA0002476222230000055
The power consumption rate of the mobile phone in the time period;
when V isiWhen the power consumption is more than or equal to A, the mobile phone is in a dynamic power consumption state, wherein the dynamic power consumption state is that the mobile phone is in a use state;
when V isiWhen < A, it indicates the handThe mobile phone is in a static power consumption state, wherein the static power consumption state is that the mobile phone is not in use;
when the static power consumption state is in the working and rest state, the working and rest time analysis unit records the starting time of the static power consumption state
Figure BDA0002476222230000056
When the dynamic power consumption state is in the working and rest state, the working and rest time analysis unit records the starting time of the dynamic power consumption state
Figure BDA0002476222230000057
Calculating the total duration of the static power consumption state according to the following formula;
Figure BDA0002476222230000058
when T isGeneral assemblyWhen B is not less than B, it indicates
Figure BDA0002476222230000059
The time point is the rest starting time point, which indicates
Figure BDA00024762222300000510
The time point is the rest end time point, TGeneral assemblyRepresents the total length of rest;
when in use
Figure BDA00024762222300000511
And TGeneral assemblyIf < D, the work and rest time is unqualified;
when in use
Figure BDA00024762222300000512
And TGeneral assemblyIf < D, the work and rest time is unqualified;
when in use
Figure BDA00024762222300000513
And TGeneral assemblyWhen D is more than or equal to D, the work and rest time is qualified;
when in use
Figure BDA00024762222300000514
And TGeneral assemblyWhen D is more than or equal to D, the work and rest time is excellent;
Figure BDA0002476222230000061
wherein Q is2The score of the personal work and rest data is shown, and b and c both show score coefficients of the work and rest data.
According to the above technical solution, the motion data analysis unit analyzes the motion data as follows:
the motion data acquisition unit acquires motion data through the GPS positioning module, and acquires the length L and the motion time T of a motion track through the GPS positioning module3Will move for a time T3Divided into z time segments, constituting a temporal set of movements
Figure BDA0002476222230000062
Wherein,
Figure BDA0002476222230000063
respectively representing movement time T3Dividing the motion trail L into z lengths at different divided time points to form a motion trail set LCollection＝{L1,L2,L3,…Lz}；
The movement speed of each divided time segment is calculated according to the following formula:
Figure BDA0002476222230000064
wherein, ViRepresenting a speed of movement for a time period;
when V isiWhen < E, it indicates walking movement;
when E is less than or equal to ViIf the number is less than F, the running exercise or the riding exercise is indicated;
when V isiWhen the speed is more than or equal to F, the speed is indicated as the driving speed of the automobile and the automobile does not move;
the motion data analysis unit analyzes ViThe trace and time < E constitute a new set G, respectivelyL＝{L1,L2,L3,…,LpIn which L is1,L2,L3,…,LpRespectively represent V after calculationiPath < E, corresponding time set is TG＝{T1,T2,T3,…,TpIn which T is1,T2,T3,…,TpRespectively represent V after calculationiTime corresponding to the path < E;
the motion data analysis unit analyzes E to be less than or equal to ViTraces and times < F constitute a new set H, respectivelyL＝{L1,L2,L3,…,LqIn which L is1,L2,L3,…,LqRespectively represents E ≦ V after calculationiPath < F, corresponding time set is TH＝{T1,T2,T3,…,TqIn which T is1,T2,T3,…,TqRespectively represents E ≦ V after calculationiTime corresponding to track < F;
the distance and duration of the individual's movements are calculated according to the following formula:
Figure BDA0002476222230000071
Figure BDA0002476222230000072
wherein L isGeneral 1Indicating the distance of the walking movement, TGeneral 1Indicating a length of time of the walking exercise;
Figure BDA0002476222230000073
Figure BDA0002476222230000074
wherein L isGeneral 2Indicating the distance of running movement, TGeneral 2Represents the length of the running exercise;
calculating a sports data score Q according to a formula3：
Q3＝d*LGeneral assembly1+e*TGeneral 1+f*LGeneral 2+g*TGeneral 2；
Where d, e, f, and g respectively represent the motion data score coefficients.
According to the technical scheme, the score Q is given to the health life of the individual according to the following formulaGeneral assemblyAnd (3) calculating:
Qgeneral assembly＝Q1+Q2+Q3；
QGeneral assemblyThe total score is the total score of the healthy life of the individual.
According to the technical scheme, the analysis and verification module comprises a data calling unit, a data comparison unit and an information question-answering unit;
the data retrieval unit is used for retrieving historical analysis data of an individual from a storage database, the data comparison unit is used for comparing the historical analysis data retrieved from the storage database with current analysis data, and the information question-answering unit is used for confirming the physical state of the individual in a question-answering mode;
the output end of the storage database is connected with the input end of the data calling unit, the output ends of the data calling unit and the central controller are connected with the input end of the data comparing unit, the output end of the data comparing unit is connected with the input end of the information question answering unit, and the output end of the information question answering unit is connected with the input end of the central controller.
The analysis and verification module verifies the current analysis data, so that the acquisition and analysis of the big data of the personal healthy life are more accurate, the analysis data can be continuously adjusted, and the prediction and evaluation of the personal healthy life are more facilitated.
According to the technical scheme, the suggestion reminding module comprises an information pushing unit and a click feedback unit;
the information pushing unit is used for pushing related living habit suggestion information to the individual according to the analysis result of the data analysis module, so that living habits are improved, and the continuous improvement of body health is facilitated;
the output end of the central controller is connected with the input end of the information pushing unit, and the output end of the information pushing unit is connected with the input end of the click feedback unit.
Compared with the prior art, the invention has the beneficial effects that:
1. the data analysis module is used for collecting and analyzing diet data, work and rest data and motion data in personal life, so that personal living habits can be visually known in the form of data, corresponding suggestions and opinions can be provided according to data display of the personal living habits, the quality of life can be improved, and the physical health can be improved.
2. The analysis and verification module is arranged, the recent body state change degree of an individual is obtained by comparing the result of the analysis data with the historical data, and the comparison conclusion is confirmed through the information question-answer form, so that the analysis of the data is more accurate, the understanding of the body of the individual is more comprehensive, the data analysis mode can be continuously adjusted, and the analysis system is continuously improved.
3. The system is provided with the suggestion reminding module, corresponding improvement suggestions are given according to the evaluation and analysis of the living habits of the individuals, whether the individuals check the push messages or not is recorded according to the click feedback unit, the adjustment of the time points and the modes of the push messages is facilitated, and the improvement of the living habits of other people can be facilitated.
Drawings
FIG. 1 is a schematic diagram of a module structure of a big data collecting and analyzing system for personal healthy life according to the present invention;
FIG. 2 is a schematic flow chart of a personal health big data collecting and analyzing system according to the present invention;
fig. 3 is a schematic diagram of a connection structure of a personal health life big data acquisition and analysis system according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1-3, a big data collecting and analyzing system for personal health life comprises a data collecting module, a data analyzing module, a central control module, an analyzing and verifying module and a suggestion reminding module;
the data acquisition module is used for acquiring various data of personal health life big data analysis, the data analysis module is used for analyzing the personal health life data acquired by the data acquisition module, the central control module is used for controlling the big data acquisition and analysis system, the analysis verification module is used for verifying the analysis result according to the big data analysis result and historical analysis data, so that the current analysis result can be verified according to the historical analysis data, the accuracy of the current big data analysis result is confirmed, and the suggestion reminding module is used for proposing a suggestion for improving life quality to an individual according to the analysis result, so that the life habit of the current young person can be improved on the big data analysis result, and the physical state of the current young person is improved;
the output end of the data acquisition module is connected with the input end of the data analysis module, the output end of the data analysis module is connected with the input end of the central control module, and the output end of the central control module is connected with the input ends of the analysis and verification module and the suggestion reminding module.
The data acquisition module comprises a diet data acquisition unit, a work and rest data acquisition unit and a motion data acquisition unit;
the diet data acquisition unit is used for acquiring individual diet data, including times M of ordering through the ordering platform and time T of ordering through the ordering platform1The work and rest data acquisition unit is used for acquiring personal work and rest data, including the power consumption rate V of the mobile phone, and the motion data acquisition unit is used for acquiring personal motion data including the motion duration T3And miles of exercise L;
the output ends of the diet data acquisition unit, the work and rest data acquisition unit and the exercise data acquisition unit are all connected with the input end of the data analysis module.
The data analysis module comprises a diet data analysis unit, a work and rest data analysis unit and a motion data analysis unit;
the diet data analysis unit is used for analyzing the individual diet data collected by the diet data collection unit, and whether the individual diet habits accord with the normal diet rules or not can be obtained through the analysis of the diet data;
the output end of the diet data acquisition unit is connected with the input end of the diet data analysis unit, the output end of the work and rest data acquisition unit is connected with the input end of the work and rest data analysis unit, and the output end of the motion data acquisition unit is connected with the input end of the motion data analysis unit.
The central control module comprises a central controller, a time recording unit and a storage database;
the central controller is used for intelligently controlling the whole system, the time recording unit is used for recording various times in the data acquisition process of the system, and the storage database is used for storing the acquired and analyzed data, so that the later retrieval and checking are facilitated;
the output end of the central processing unit is connected with the input end of the storage database, and the output end of the time recording unit is connected with the input end of the central controller.
The diet data analysis unit analyzes the diet data as follows:
the diet data analysis unit is used for collecting the time T of the individual ordering through the ordering platform every month1Composing a set of times
Figure BDA0002476222230000121
Figure BDA0002476222230000122
Wherein,
Figure BDA0002476222230000123
respectively representing the time point of each meal ordering;
the average time interval for the individual to order through the ordering platform each month is calculated according to the following formula:
Figure BDA0002476222230000124
wherein,
Figure BDA0002476222230000125
representing the average time interval of the individual to order through the ordering platform each month;
the results of the individual dietary data analysis were calculated according to the following formula:
Figure BDA0002476222230000126
wherein Q is1Represents the individual diet data score, and a represents the diet data score coefficient.
The work and rest data analysis unit analyzes the work and rest data as follows:
the work and rest data analysis unit confirms work and rest time through analysis of power consumption rate V of the mobile phone, and the power consumption rate V of the mobile phone is calculated through the electric quantity P of the mobile phone at intervals of time tiDetecting to form the power set P ═ { P ═ P of the mobile phone1,P2,P3,...,PxIn which P is1,P2,P3,...,PxRespectively representing the mobile phone electric quantity of each time point, recording the time points of detecting the electric quantity, and forming a time set for detecting the mobile phone electric quantity
Figure BDA0002476222230000131
Figure BDA0002476222230000132
Wherein,
Figure BDA0002476222230000133
respectively representing each time point for detecting the electric quantity of the mobile phone;
calculating the power consumption rate of the mobile phone at intervals of time t according to the following formula:
Figure BDA0002476222230000134
wherein, ViIndicating that the mobile phone is
Figure BDA0002476222230000135
The power consumption rate of the mobile phone in the time period;
when V isiWhen the power consumption is more than or equal to A, the mobile phone is in a dynamic power consumption state, wherein the dynamic power consumption state is that the mobile phone is in a use state;
when V isiIf the current power consumption is less than A, the mobile phone is in a static power consumption state, wherein the static power consumption state is that the mobile phone is not in use;
when the static power consumption state is in the working and rest state, the working and rest time analysis unit records the starting time of the static power consumption state
Figure BDA0002476222230000136
When the dynamic power consumption state is in the working and rest state, the working and rest time analysis unit records the starting time of the dynamic power consumption state
Figure BDA0002476222230000137
Calculating the total duration of the static power consumption state according to the following formula;
Figure BDA0002476222230000138
when T isGeneral assemblyWhen B is not less than B, it indicates
Figure BDA0002476222230000139
The time point is the rest starting time point, which indicates
Figure BDA00024762222300001310
The time point is the rest end time point, TGeneral assemblyRepresents the total length of rest;
when in use
Figure BDA00024762222300001311
And TGeneral assemblyIf < D, the work and rest time is unqualified;
when in use
Figure BDA0002476222230000141
And TGeneral assemblyIf < D, the work and rest time is unqualified;
when in use
Figure BDA0002476222230000142
And TGeneral assemblyWhen D is more than or equal to D, the work and rest time is qualified;
when in use
Figure BDA0002476222230000143
And TGeneral assemblyWhen D is more than or equal to D, the work and rest time is excellent;
Figure BDA0002476222230000144
wherein Q is2The score of the personal work and rest data is shown, and b and c both show score coefficients of the work and rest data.
The motion data analysis unit analyzes the motion data as follows:
the motion data acquisition unit acquires motion data through the GPS positioning module, and acquires the length L and the motion time T of a motion track through the GPS positioning module3Will move for a time T3Divided into z time segments, constituting a temporal set of movements
Figure BDA0002476222230000145
Wherein,
Figure BDA0002476222230000146
respectively representing movement time T3Dividing the motion trail L into z lengths at different divided time points to form a motion trail set LCollection＝{L1,L2,L3,…Lz}；
The movement speed of each divided time segment is calculated according to the following formula:
Figure BDA0002476222230000147
wherein, ViRepresenting a speed of movement for a time period;
when V isiWhen < E, it indicates walking movement;
when E is less than or equal to ViIf the number is less than F, the running exercise or the riding exercise is indicated;
when V isiWhen the speed is more than or equal to F, the speed is indicated as the driving speed of the automobile and the automobile does not move;
the motion data analysis unit analyzes ViThe trace and time < E constitute a new set G, respectivelyL＝{L1,L2,L3,…,LpIn which L is1,L2,L3,…,LpRespectively represent V after calculationiPath < E, corresponding time set is TG＝{T1,T2,T3,…,TpIn which T is1,T2,T3,…,TpRespectively represent V after calculationiTime corresponding to the path < E;
the motion data analysis unit analyzes E to be less than or equal to ViTraces and times < F constitute a new set H, respectivelyL＝{L1,L2,L3,…,LqIn which L is1,L2,L3,…,LqRespectively represents E ≦ V after calculationiPath < F, corresponding time set is TH＝{T1,T2,T3,…,TqIn which T is1,T2,T3,…,TqRespectively represents E ≦ V after calculationiTime corresponding to track < F;
the distance and duration of the individual's movements are calculated according to the following formula:
Figure BDA0002476222230000151
Figure BDA0002476222230000152
wherein L isGeneral 1Indicating the distance of the walking movement, TGeneral 1Indicating a length of time of the walking exercise;
Figure BDA0002476222230000153
Figure BDA0002476222230000154
wherein L isGeneral 2Indicating the distance of running movement, TGeneral 2Represents the length of the running exercise;
calculating a sports data score Q according to a formula3：
Q3＝d*LGeneral 1+e*TGeneral 1+f*LGeneral 2+g*TGeneral 2；
Where d, e, f, and g respectively represent the motion data score coefficients.
Scoring the healthy life of an individual Q according to the following formulaGeneral assemblyAnd (3) calculating:
Qgeneral assembly＝Q1+Q2+Q3；
QGeneral assemblyThe total score is the total score of the healthy life of the individual.
The analysis and verification module comprises a data calling unit, a data comparison unit and an information question and answer unit;
the data retrieval unit is used for retrieving historical analysis data of an individual from a storage database, the data comparison unit is used for comparing the historical analysis data retrieved from the storage database with current analysis data, and the information question-answering unit is used for confirming the physical state of the individual in a question-answering mode;
the output end of the storage database is connected with the input end of the data calling unit, the output ends of the data calling unit and the central controller are connected with the input end of the data comparing unit, the output end of the data comparing unit is connected with the input end of the information question answering unit, and the output end of the information question answering unit is connected with the input end of the central controller.
The analysis and verification module verifies the current analysis data, so that the acquisition and analysis of the big data of the personal healthy life are more accurate, the analysis data can be continuously adjusted, and the prediction and evaluation of the personal healthy life are more facilitated.
The suggestion reminding module comprises an information pushing unit and a click feedback unit;
the information pushing unit is used for pushing related living habit suggestion information to the individual according to the analysis result of the data analysis module, so that living habits are improved, and the continuous improvement of body health is facilitated;
the output end of the central controller is connected with the input end of the information pushing unit, and the output end of the information pushing unit is connected with the input end of the click feedback unit.
The first embodiment is as follows:
the diet data analysis unit analyzes the diet data as follows:
the diet data analysis unit is used for collecting the time T of the individual ordering through the ordering platform every month1Set of composition times T1 set of(11: 03 points on 3/2/2020, 11:15 points on 3/2020, 11:13 points on 3/4/2020/…, 11:20 points on 3/31/2020);
the average time interval for the individual to order through the ordering platform each month is calculated according to the following formula:
Figure BDA0002476222230000171
wherein,
Figure BDA0002476222230000172
representing the average time interval of the person ordering the meal through the ordering platform in the month;
the results of the individual dietary data analysis were calculated according to the following formula:
Figure BDA0002476222230000173
wherein Q is123.5 denotes the score of the individual diet data, and a 1 denotes the score coefficient of the diet data.
The work and rest data analysis unit analyzes the work and rest data as follows:
the work and rest data analysis unit confirms work and rest time through analysis of power consumption rate V of the mobile phone, and the power consumption rate V of the mobile phone is calculated through the electric quantity P of the mobile phone at intervals of time tiDetecting, wherein the electricity quantity set P of the mobile phone is { 86%, 84%, 82%, …, 35%, 45%, 55%, …, 100%, 100%, …, 100%, 99%, 98% }, and recording the detected electricity quantityTime point, forming a time set T for detecting the electric quantity of the mobile phone2 set of＝{18:05,18:15,18:25,…,22:36,22:46,22:56,…,11:46,11:56,…,7:35,7:45,7:55}；
Calculating the power consumption rate of the mobile phone every time period t of 10min according to the following formula:
Figure BDA0002476222230000181
wherein, ViIndicating that the mobile phone is
Figure BDA0002476222230000182
The power consumption rate of the mobile phone in the time period;
Via is more than or equal to A, which indicates that the mobile phone is in a dynamic power consumption state, wherein the dynamic power consumption state is that the mobile phone is in a use state;
Viif the power consumption is less than A, the mobile phone is in a static power consumption state, wherein the static power consumption state is that the mobile phone is not in use;
when the static power consumption state is in the working and rest state, the working and rest time analysis unit records the starting time of the static power consumption state
Figure BDA0002476222230000183
When the dynamic power consumption state is in the working and rest state, the working and rest time analysis unit records the starting time of the dynamic power consumption state
Figure BDA0002476222230000184
Calculating the total duration of the static power consumption state according to the following formula;
Figure BDA0002476222230000185
hours 59 minutes;
Tgeneral assemblyNot less than 8 hours, indicating that
Figure BDA0002476222230000186
The time point is the rest starting time point, which indicates
Figure BDA0002476222230000187
The time point is the rest end time point, TGeneral assembly8 hours 59 minutes represents the total length of rest;
Figure BDA0002476222230000188
and TGeneral assemblyD is more than or equal to 9 hours, which indicates that the work and rest time is qualified;
Figure BDA0002476222230000189
wherein Q is262.8 represents the score of the personal daily data, and b-12 and c-2 each represent the daily data score coefficient.
The motion data analysis unit analyzes the motion data as follows:
the motion data acquisition unit acquires motion data through the GPS positioning module, and acquires the length L and the motion time T of a motion track through the GPS positioning module3Will move for a time T3Divided into z time segments, constituting a time set T of movements3 sets of1, { 8: 30,8: 35,8: 40,...,21: 05, 21: 10, 21: 15, 21: 20, 21: 25, 21: 30, 21: 35, dividing the motion track L into z lengths to form a motion track set LCollection＝{3000,1800,0,…,300,286,856,905,865,795}；
The movement speed of each divided time segment is calculated according to the following formula:
Figure BDA0002476222230000191
wherein, ViRepresenting a speed of movement for a time period;
when V isiWhen < E is 60m/min, the walking exercise is indicated;
when E is 60m/min and V is less than or equal toiWhen F is less than 200m/min, the running exercise or the riding exercise is indicated;
when V isiWhen the F is more than or equal to 200m/min, the automobile running speed is indicated,not in motion;
the motion data analysis unit analyzes ViThe trace and time < E60 m/min constitute a new set GLFor a corresponding time set of T, 300,286G＝{21：05，21：10，21：15}；
The motion data analysis unit analyzes E to be 60m/min and less than or equal to ViThe trace and time < F ═ 200m/min respectively form a new set HLFor a corresponding time set of T, 856,905,865,795H＝{21：15，21：20，21：25，21：30，21：35}；
The distance and duration of the individual's movements are calculated according to the following formula:
Figure BDA0002476222230000192
Figure BDA0002476222230000193
wherein L isGeneral 1586m denotes a distance of walking movement, TGeneral 110min represents the duration of the walking exercise;
Figure BDA0002476222230000201
Figure BDA0002476222230000202
wherein L isGeneral 23421m represents the distance of the running exercise, TGeneral 220min represents the duration of the running exercise;
calculating a sports data score Q according to a formula3：
Q3＝d*LGeneral 1+e*TGeneral 1+f*LGeneral 2+g*TGeneral 2＝10*0.586+2*
10+5*3.421+1*20＝62.965；
Where d-10, e-2, f-5, and g-1 represent motion data score coefficients, respectively.
According toAccording to the technical scheme, the score Q is given to the personal healthy life according to the following formulaGeneral assemblyAnd (3) calculating:
Qgeneral assembly＝Q1+Q2+Q3＝23.5+62.8+62.965＝149.265；
QGeneral assembly149.265 is the total score of the individual's healthy life;
the data retrieval unit retrieves the total personal health life score of the individual in the previous month from the database to be 126.5 points, the information question and answer unit inquires whether the current body state of the individual is improved or not, the body state of the individual is improved, the information pushing unit pushes the personal health life score of the month to the personal mobile phone terminal, and the suggestion that the individual has little taken out of a takeaway restaurant is given.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.

Claims (10)

1. A personal health life big data acquisition and analysis system is characterized in that: the big data acquisition and analysis system comprises a data acquisition module, a data analysis module, a central control module, an analysis and verification module and a suggestion reminding module;
the system comprises a data acquisition module, a data analysis module, a central control module, an analysis and verification module and a suggestion reminding module, wherein the data acquisition module is used for acquiring various data of personal health life big data analysis, the data analysis module is used for analyzing the personal health life data acquired by the data acquisition module, the central control module is used for controlling a big data acquisition and analysis system, the analysis and verification module is used for verifying an analysis result according to a big data analysis result and historical analysis data, and the suggestion reminding module is used for proposing a suggestion for improving life quality to an individual according to the analysis result;
the output end of the data acquisition module is connected with the input end of the data analysis module, the output end of the data analysis module is connected with the input end of the central control module, and the output end of the central control module is connected with the input ends of the analysis and verification module and the suggestion reminding module.
2. The personal health life big data collecting and analyzing system as claimed in claim 1, wherein: the data acquisition module comprises a diet data acquisition unit, a work and rest data acquisition unit and a motion data acquisition unit;
the diet data acquisition unit is used for acquiring individual diet data, including times M of ordering through the ordering platform and time T of ordering through the ordering platform1The work and rest data acquisition unit is used for acquiring personal work and rest data, including the power consumption rate V of the mobile phone, and the motion data acquisition unit is used for acquiring personal motion data including the motion duration T3And miles of exercise L;
the output ends of the diet data acquisition unit, the work and rest data acquisition unit and the exercise data acquisition unit are all connected with the input end of the data analysis module.
3. The personal health life big data collecting and analyzing system as claimed in claim 2, wherein: the data analysis module comprises a diet data analysis unit, a work and rest data analysis unit and a motion data analysis unit;
the diet data analysis unit is used for analyzing the personal diet data collected by the diet data collection unit, the work and rest data analysis unit is used for analyzing the personal work and rest data collected by the work and rest data collection unit, and the motion data analysis unit is used for analyzing the personal motion data collected by the motion data collection unit;
the output end of the diet data acquisition unit is connected with the input end of the diet data analysis unit, the output end of the work and rest data acquisition unit is connected with the input end of the work and rest data analysis unit, and the output end of the motion data acquisition unit is connected with the input end of the motion data analysis unit.
4. The personal health life big data collecting and analyzing system as claimed in claim 3, wherein: the central control module comprises a central controller, a time recording unit and a storage database;
the central controller is used for intelligently controlling the whole system, the time recording unit is used for recording various times in the data acquisition process of the system, and the storage database is used for storing the acquired and analyzed data, so that the later retrieval and checking are facilitated;
the output end of the central processing unit is connected with the input end of the storage database, and the output end of the time recording unit is connected with the input end of the central controller.
5. The personal health life big data collecting and analyzing system as claimed in claim 4, wherein: the diet data analysis unit analyzes the diet data as follows:
the diet data analysis unit is used for collecting the time T of the individual ordering through the ordering platform every month1Composing a set of times
Figure FDA0002476222220000031
Figure FDA0002476222220000032
Wherein,
Figure FDA0002476222220000033
respectively representing the time point of each meal ordering;
the average time interval for the individual to order through the ordering platform each month is calculated according to the following formula:
Figure FDA0002476222220000034
wherein,
Figure FDA0002476222220000035
representing the average time interval of the individual to order through the ordering platform each month;
the results of the individual dietary data analysis were calculated according to the following formula:
Figure FDA0002476222220000036
wherein Q is1Represents the individual diet data score, and a represents the diet data score coefficient.
6. The personal health life big data collecting and analyzing system as claimed in claim 5, wherein: the work and rest data analysis unit analyzes the work and rest data as follows:
the work and rest data analysis unit confirms work and rest time through analysis of power consumption rate V of the mobile phone, and the power consumption rate V of the mobile phone is calculated through the electric quantity P of the mobile phone at intervals of time tiDetecting to form the power set P ═ { P ═ P of the mobile phone1,P2,P3,...,PxIn which P is1,P2,P3,...,PxRespectively representing the mobile phone electric quantity of each time point, recording the time points of detecting the electric quantity, and forming a time set for detecting the mobile phone electric quantity
Figure FDA0002476222220000037
Figure FDA0002476222220000041
Wherein,
Figure FDA0002476222220000042
respectively representing each time point for detecting the electric quantity of the mobile phone;
calculating the power consumption rate of the mobile phone at intervals of time t according to the following formula:
Figure FDA0002476222220000043
wherein, ViIndicating that the mobile phone is
Figure FDA0002476222220000044
The power consumption rate of the mobile phone in the time period;
when V isiWhen the power consumption is more than or equal to A, the mobile phone is in a dynamic power consumption state, wherein the dynamic power consumption state is that the mobile phone is in a use state;
when V isiIf the current power consumption is less than A, the mobile phone is in a static power consumption state, wherein the static power consumption state is that the mobile phone is not in use;
when the static power consumption state is in the working and rest state, the working and rest time analysis unit records the starting time of the static power consumption state
Figure FDA0002476222220000045
When the dynamic power consumption state is in the working and rest state, the working and rest time analysis unit records the starting time of the dynamic power consumption state
Figure FDA0002476222220000046
Calculating the total duration of the static power consumption state according to the following formula;
Figure FDA0002476222220000047
when T isGeneral assemblyWhen B is not less than B, it indicates
Figure FDA0002476222220000048
The time point is the rest starting time point, which indicates
Figure FDA0002476222220000049
The time point is the rest end time point, TGeneral assemblyRepresents the total length of rest;
when in use
Figure FDA00024762222200000410
And TGeneral assemblyIf < D, the work and rest time is unqualified;
when in use
Figure FDA00024762222200000411
And TGeneral assemblyIf < D, the work and rest time is unqualified;
when in use
Figure FDA00024762222200000412
And TGeneral assemblyWhen D is more than or equal to D, the work and rest time is qualified;
when in use
Figure FDA00024762222200000413
And TGeneral assemblyWhen D is more than or equal to D, the work and rest time is excellent;
Figure FDA00024762222200000414
wherein Q is2The score of the personal work and rest data is shown, and b and c both show score coefficients of the work and rest data.
7. The personal healthy life big data acquisition and analysis system according to claim 6, wherein: the motion data analysis unit analyzes the motion data as follows:
the motion data acquisition unit acquires motion data through the GPS positioning module, and acquires the length L and the motion time T of a motion track through the GPS positioning module3Will move for a time T3Divided into z time segments, constituting a temporal set of movements
Figure FDA0002476222220000051
Wherein,
Figure FDA0002476222220000052
respectively representing movement time T3Dividing the motion trail L into z lengths at different divided time points to form a motion trail set LCollection＝{L1,L2,L3,…Lz}；
The movement speed of each divided time segment is calculated according to the following formula:
Figure FDA0002476222220000053
wherein, ViRepresenting a speed of movement for a time period;
when V isiWhen < E, it indicates walking movement;
when E is less than or equal to ViIf the number is less than F, the running exercise or the riding exercise is indicated;
when V isiWhen the speed is more than or equal to F, the speed is indicated as the driving speed of the automobile and the automobile does not move;
the motion data analysis unit analyzes ViThe trace and time < E constitute a new set G, respectivelyL＝{L1,L2,L3,…,LpIn which L is1,L2,L3,…,LpRespectively represent V after calculationiPath < E, corresponding time set is TG＝{T1,T2,T3,…,TpIn which T is1,T2,T3,…,TpRespectively represent V after calculationiTime corresponding to the path < E;
the motion data analysis unit analyzes E to be less than or equal to ViTraces and times < F constitute a new set H, respectivelyL＝{L1,L2,L3,…,LqIn which L is1,L2,L3,…,LqRespectively represents E ≦ V after calculationiPath < F, corresponding time set is TH＝{T1,T2,T3,…,TqIn which T is1,T2,T3,…,TqRespectively represents E ≦ V after calculationiTime corresponding to track < F;
the distance and duration of the individual's movements are calculated according to the following formula:
Figure FDA0002476222220000061
Figure FDA0002476222220000062
wherein L isGeneral 1Indicating the distance of the walking movement, TGeneral 1Indicating a length of time of the walking exercise;
Figure FDA0002476222220000063
Figure FDA0002476222220000064
wherein L isGeneral 2Indicating the distance of running movement, TGeneral 2Represents the length of the running exercise;
calculating a sports data score Q according to a formula3：
Q3＝d*LGeneral 1+e*TGeneral 1+f*LGeneral 2+g*TGeneral 2；
Where d, e, f, and g respectively represent the motion data score coefficients.
8. The personal health life big data collecting and analyzing system as claimed in claim 7, wherein: scoring the healthy life of an individual Q according to the following formulaGeneral assemblyAnd (3) calculating:
Qgeneral assembly＝Q1+Q2+Q3；
QGeneral assemblyThe total score is the total score of the healthy life of the individual.
9. The personal health life big data collecting and analyzing system as claimed in claim 8, wherein: the analysis and verification module comprises a data calling unit, a data comparison unit and an information question and answer unit;
the data retrieval unit is used for retrieving historical analysis data of an individual from a storage database, the data comparison unit is used for comparing the historical analysis data retrieved from the storage database with current analysis data, and the information question-answering unit is used for confirming the physical state of the individual in a question-answering mode;
the output end of the storage database is connected with the input end of the data calling unit, the output ends of the data calling unit and the central controller are connected with the input end of the data comparing unit, the output end of the data comparing unit is connected with the input end of the information question answering unit, and the output end of the information question answering unit is connected with the input end of the central controller.
10. The personal health life big data collecting and analyzing system as claimed in claim 9, wherein: the suggestion reminding module comprises an information pushing unit and a click feedback unit;
the information pushing unit is used for pushing related living habit suggestion information to the individual according to the analysis result of the data analysis module, and the click feedback unit is used for feeding back whether the individual clicks the information pushed by the information pushing unit;
the output end of the central controller is connected with the input end of the information pushing unit, and the output end of the information pushing unit is connected with the input end of the click feedback unit.
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