CN110491090B - Mobile phone terminal-based middle-aged and elderly people group monitoring method - Google Patents
Mobile phone terminal-based middle-aged and elderly people group monitoring method Download PDFInfo
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/02—Alarms for ensuring the safety of persons
- G08B21/04—Alarms for ensuring the safety of persons responsive to non-activity, e.g. of elderly persons
- G08B21/0407—Alarms for ensuring the safety of persons responsive to non-activity, e.g. of elderly persons based on behaviour analysis
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/02—Alarms for ensuring the safety of persons
- G08B21/04—Alarms for ensuring the safety of persons responsive to non-activity, e.g. of elderly persons
- G08B21/0438—Sensor means for detecting
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04M—TELEPHONIC COMMUNICATION
- H04M1/00—Substation equipment, e.g. for use by subscribers
- H04M1/72—Mobile telephones; Cordless telephones, i.e. devices for establishing wireless links to base stations without route selection
- H04M1/724—User interfaces specially adapted for cordless or mobile telephones
- H04M1/72403—User interfaces specially adapted for cordless or mobile telephones with means for local support of applications that increase the functionality
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/024—Guidance services
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/025—Services making use of location information using location based information parameters
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/90—Services for handling of emergency or hazardous situations, e.g. earthquake and tsunami warning systems [ETWS]
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W64/00—Locating users or terminals or network equipment for network management purposes, e.g. mobility management
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L2101/00—Indexing scheme associated with group H04L61/00
- H04L2101/60—Types of network addresses
- H04L2101/618—Details of network addresses
- H04L2101/622—Layer-2 addresses, e.g. medium access control [MAC] addresses
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L2101/00—Indexing scheme associated with group H04L61/00
- H04L2101/60—Types of network addresses
- H04L2101/69—Types of network addresses using geographic information, e.g. room number
Abstract
The invention provides a middle-aged and elderly people group monitoring method based on a mobile phone terminal, which comprises the following steps: a monitoring step of residential housing and a monitoring step of active area. The invention identifies the normal and abnormal walking speeds of the middle-aged and elderly people through the mobile phone terminal. And real-time monitoring and analysis are carried out, and according to the activity prediction model of the middle-aged and old people and the activity historical database of the middle-aged and old people. The safety monitoring of the outgoing distance and range behavior detection and identification of the middle-aged and old people and the health degree of the middle-aged and old people by the mobile phone terminal is realized. When abnormal conditions occur, the alarm for the indoor activity time abnormity of the middle-aged and the old people and the alarm for the outdoor activity time abnormity of the middle-aged and the old people are realized. And the abnormal information and the monitoring result of the middle-aged and old people are transmitted to a 5G edge data center, so that the middle-aged and old people are informed of the relatives and community medical staff of the residence to take corresponding treatment measures as soon as possible in the shortest time, and the personal safety of the middle-aged and old people is ensured.
Description
Technical Field
The invention relates to the technical field of communication, in particular to a middle-aged and old people group monitoring method based on a mobile phone terminal.
Background
At present, the problem of aging of the population is increasingly serious, the population proportion of the elderly is continuously increased, but the corresponding social service level is difficult to meet the existing monitoring requirement of the elderly, and as the proportion of the elderly is higher, a plurality of empty nesters or seriously ill elderly need to be monitored for 24 hours. In the rapidly developing economic society, if there is not enough time and energy to monitor the elderly, a series of social problems may arise. The existing indoor monitoring technology for the old people is mainly established on the basis of monitoring by video equipment, but the privacy of the old people is easily invaded by adopting the video equipment to carry out the indoor monitoring of the old people, and the indoor monitoring technology is not accepted by most of the old people, so that the indoor monitoring technology cannot be widely popularized and applied.
Because the living habits, life styles and health conditions of each old person are different, in order to obtain an activity prediction model of a certain old person, a prediction model learning stage is arranged at the system operation starting stage, in addition, the life patterns of the old persons are not invariable, and the life patterns of the old persons are also changed along with the change of time and seasons. The magnitude level and distribution of the activity level are also constantly changing, as reflected in the activity level.
Most of the current video monitoring systems are completed by human real-time monitoring, and the defects are as follows: the monitoring staff is required to find the abnormal condition by continuously watching the monitoring screen, and the specific monitoring process is a delicate, continuous and long-term boring process. Especially when there are many monitoring points, monitoring staff often face a large television wall, which is easy to cause careless omission and cannot find abnormal conditions occurring in the monitored points in time. Moreover, the continuous monitoring of the picture inevitably involves the problem of personal privacy, and the monitoring mode is not easy to be accepted by the old. Therefore, it is necessary to provide a further solution to the above problems.
Disclosure of Invention
The invention aims to provide a mobile phone terminal-based middle-aged and elderly people group monitoring method to overcome the defects in the prior art.
In order to solve the technical problems, the technical scheme of the invention is as follows:
a middle-aged and elderly people group monitoring method based on a mobile phone terminal comprises the following steps: a residential monitoring step and an activity area monitoring step;
the residential housing monitoring step comprises the following steps:
scanning MAC addresses of Wi-Fi routers around through a Wi-Fi chip of a mobile phone of a user, or determining the actual geographic position of the user through a periodic MR (magnetic resonance) of a wireless side when the user surfs the internet;
judging whether the actual geographical position exceeds a preset movement range within a specified time period according to the determined actual geographical position, if so, indicating that the user activities normally, and otherwise, entering the calculation of a judgment mode of the health degree;
the monitoring step of the active area comprises:
and (3) partitioning road monitoring and time point identification for the motion state of the user through a dynamic analysis algorithm, distinguishing the activity state of the user according to a set place and a set time window, and calculating and analyzing the health condition change of the user.
As an improvement of the middle-aged and elderly people group monitoring method based on the mobile phone terminal, the step of determining the actual geographic position of the user through the MAC address comprises the following steps:
and transmitting the MAC address to a background server through an internet network, acquiring the actual longitude and latitude position information of the Wi-Fi router stored in the background server, and calculating the actual geographic position of the mobile phone of the user according to the wifi signal intensity.
As an improvement of the middle-aged and elderly people group monitoring method based on the mobile phone terminal, determining the actual geographic position of the user through the MAC address further comprises:
and correcting the MAC address calculation error of the router, and simultaneously, directly positioning to the GPS coordinate of the residential residence of the user by using IP positioning of the used app of the mobile phone through OTT mobile phone app or hundred-degree big data service, and correcting the MAC address calculation error of the router again.
As an improvement of the middle-aged and elderly people group monitoring method based on the mobile phone terminal, the step of determining the actual geographic position of the user through the MR comprises the following steps:
and extracting parameters of a user main service cell in the MR signaling through periodical MR analysis of a wireless side when the user surfs the internet, and if the user main service cell is an indoor cell at the moment, taking the longitude and latitude of the cell as the longitude and latitude of the current position of the user.
As an improvement of the monitoring method for the middle-aged and the elderly people based on the mobile phone terminal, the monitoring step of the activity area comprises the following steps:
selecting a preset time period, finely dividing spontaneous activity walking of middle-aged and elderly people groups, dynamic body-building activity of the middle-aged and elderly people groups, high-speed movement of the middle-aged and elderly people groups, hospitalizing and shopping activity of the middle-aged and elderly people groups, spontaneous activity sun exposure of the middle-aged and elderly people groups, static sampling characteristics of the middle-aged and elderly people groups, and taking a threshold value sampling point as dynamic analysis algorithm data;
based on the selected scene of the middle-aged and elderly people group, dividing sampling points of the healthy middle-aged and elderly people group, which move at a high speed, move at a low speed and are static;
and according to the operation data of the first sampling point base station cell replacement threshold value to the second sampling point base station cell replacement threshold value of the healthy middle-aged and old people group, the dynamic analysis algorithm gives out the health condition information.
As an improvement of the middle-aged and old people group monitoring method based on the mobile phone terminal, the middle-aged and old people group monitoring method based on the mobile phone terminal comprises the steps of high-speed and middle-aged mobile judgment, low-speed mobile judgment and static state user judgment; the judgment conditions of the middle-aged and old people group moving at high and medium speed are as follows: in the site time window, the cell replacement times are more than or equal to the specified times, and the cell replacement distance is more than the threshold distance; the low-speed mobile middle-aged and elderly people group judgment conditions are as follows: in the time window, the cell replacement times are more than the specified times or the distance between the first cell and the last cell is less than the threshold distance; the static state user judgment conditions are as follows: within the time window, the cell change number is equal to 0.
As an improvement of the middle-aged and elderly people group monitoring method based on the mobile phone terminal, the calculation process for calculating and analyzing the health condition change of the user comprises the following steps:
and (3) mixing the following components: 00-7:30, 7: 00-9:30, 10: 00-10:30, 11: 00-12:00, 12: 00-14:00, 15: 00-17:00, 18: seven time periods 00-21:00 are positioned at a starting point, the activity of the middle-aged and elderly people in each time period is switched from one health degree state to another health degree state to finish a feasible solution of an activity area, and when all the middle-aged and elderly people finish respective activity areas according to different time periods, different routes and different speeds, the obtained data is used for updating and calculating, and a dynamic analysis algorithm is guided to obtain a final solution of the health degree.
As an improvement of the middle-aged and elderly people group monitoring method based on the mobile phone terminal, a calculation formula (1) for calculating and analyzing the health condition change of the user is as follows:
different time periods l, different speeds rho, health degree deviation omega, middle-aged and elderly people group activity area
G number of middle aged and elderly people, BkThe health degree value, k is the value of abnormal judgment of the health degree, epsilon is the updating value of the health degree, and a represents the starting position b represents the ending position.
As an improvement of the monitoring method for the middle-aged and elderly people based on the mobile phone terminal, aiming at different routes and different speeds, the health degree index of the middle-aged and elderly people is calculated by a dynamic weighting method through aggregation analysis:
acquiring a dynamic health index function W of the aggregate analysis of the middle-aged and elderly people:
in the formula, L represents the length of a regional site target of the middle-aged and elderly people; x is the number oftRepresenting the normal time value of the line of the middle-aged and the elderly; x is the number offRepresenting the actual time value of the line of the middle-aged and elderly people; coefficient of performance
Representing a preferential transaction selection made based on one day activity, coefficient
The time value of the line of the middle-aged and old people can be 0.9, and the actual time value of the line of the middle-aged and old people is a function of the health index; the normal time value of the middle-aged and old people group line is associated with the aggregation analysis dynamic health index of the middle-aged and old people group;
calculating the dynamic health value of each route aggregation analysis in the area graph connecting the starting point and the target point formed by dividing the communication network according to a formula, taking the nth edge as an example:
the method is characterized in that the daily activity area site targets of the middle-aged and old people are set to be the same and are not mutually connected, and the health degree index model of the middle-aged and old people is simplified, so that when the middle-aged and old people move along the (n + 1) th route of an activity area, the health degree index can divide the activity area site targets into seven sections to be calculated to obtain the following formula:
in the formula, s represents the distance of the activity area of the nth middle-aged and old people group every day; n represents the number of levels of the health indicator;
the distance of the 1 st to 7 th path health index test is shown, and the middle-aged and elderly people groupsIn the case where the speed of the moving area location is the same every day, let us say χiWhen S, then X∫i＝Sn。
Compared with the prior art, the invention has the beneficial effects that: the invention identifies the normal and abnormal walking speeds of the middle-aged and elderly people through the mobile phone terminal. And real-time monitoring and analysis are carried out, and according to the activity prediction model of the middle-aged and old people and the activity historical database of the middle-aged and old people. The safety monitoring of the outgoing distance and range behavior detection and identification of the middle-aged and old people and the health degree of the middle-aged and old people by the mobile phone terminal is realized. When abnormal conditions occur, the alarm for the indoor activity time abnormity of the middle-aged and the old people and the alarm for the outdoor activity time abnormity of the middle-aged and the old people are realized. And the abnormal information and the monitoring result of the middle-aged and old people are transmitted to a 5G edge data center, so that the middle-aged and old people are informed of the relatives and community medical staff of the residence to take corresponding treatment measures as soon as possible in the shortest time, and the personal safety of the middle-aged and old people is ensured.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments described in the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic flow chart of a method for monitoring middle-aged and elderly people based on a mobile phone terminal 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, the present invention provides a middle-aged and elderly people group monitoring method based on a mobile phone terminal, which includes: a monitoring step of residential housing and a monitoring step of active area.
The residential monitoring step is used for monitoring the residential of the middle-aged and the elderly.
The residential housing monitoring step comprises the following steps: and scanning the MAC addresses of the surrounding Wi-Fi routers through the Wi-Fi chip of the mobile phone of the user.
Specifically, the principle of the above steps is: and scanning MAC (Media/Media Access Control) addresses of surrounding Wi-Fi routers (used for representing identifiers and signal strength of each site on the Internet) by using a Wi-Fi chip of the user mobile phone, transmitting the addresses to a background server through an internet network, wherein the background server is provided with actual longitude and latitude position information of the Wi-Fi routers, and calculating the actual geographic position of the user mobile phone according to the wifi signal strength.
Specifically, since the strength of the signal is in dBm, the closer to 0 the signal is, the better the signal is, using a negative number, e.g., -40 the strength of the a signal and-60 the strength of the B signal, the stronger the a signal is than the B signal; the value of dBm is generally between-90 and 0: the range of the signal is stronger is-50 dbm to 0dbm, the range of the signal is better is-75 to-50, and the range of the signal is weaker is less than-75; the relationship between the signal strength and the wireless router power, and the formula dbm is 10 × lg (power/1 mw).
Meanwhile, each WiFi hotspot (router) has a unique address, so when the mobile phone starts WiFi, the mobile phone can scan and collect WiFi signals of surrounding routers, and meanwhile, scanned position information is uploaded to a server to form a hotspot position database. The server retrieves the geographical position of each wifi hotspot, and then calculates the geographical position of the mobile phone according to different strengths of the signals.
In addition, the calculation error of the MAC address of the router is corrected, and meanwhile, by means of IP positioning of the OTT mobile phone app or hundredth-degree big data service through the app used by the mobile phone, the GPS coordinate of the residential house of the user is directly positioned, and the calculation error of the MAC address of the router is corrected again, so that the recognition with the error of 5-10 meters or less is realized.
When the user does not surf the internet based on the Wi-Fi chip, the actual geographic position of the user is determined through the periodical MR on the wireless side when the user surfs the internet. The principle is as follows: through periodic MR (Measurement Report) analysis of a wireless side when a user of middle-aged and old people surfs the internet, parameters of a user main service cell in MR/signaling are extracted, and if the user main service cell is an indoor cell at the moment, the longitude and the latitude of the cell are taken as the longitude and the latitude of the current position of the user.
If the positioning calculation is only based on the currently connected Wi-Fi access point, the Wi-Fi positioning is easy to have errors (such as floor positioning errors). Wi-Fi access points usually only can cover the range with the radius of about 70 meters, and are easily interfered by other signals, so that the accuracy of the Wi-Fi access points is influenced.
And judging whether the determined actual geographical position exceeds a preset movement range within a specified time period, and if so, indicating that the user activities normally.
For example, if the middle-aged and old people are identified not to go out in 3-7 days of residence, the static activity 0m,5G edge data center enters the calculation of the judging mode of the health degree of the old people for judgment.
The monitoring step of the active area is used for monitoring the middle-aged and the elderly during the activity in one area, and comprises the following steps: the residential neighborhood courtyard green land, residential quarter, urban pedestrian area, bicycle or public transit operation area, etc. Generally, the radius of a green area of a courtyard surrounding a residence is generally not more than 200m, the radius of a bicycle or a bus is generally not more than 500m, and the radius of a bicycle or a bus is generally not more than 1000 m-10000 m.
MR (measurement report) refers to information being sent once every 480ms (470 ms on a signaling channel) on a traffic channel, and these data can be used for network evaluation and optimization.
The MR measurement report is completed by MS and BTS, the MS executes and reports the downlink level intensity, quality and TA of GSM cell, and BTS executes and reports the measurement of the receiving level intensity and quality of uplink MS. The processing of the measurement report is usually done at the BSC (when the preprocessing mode of the BTS is used, the measurement report processing can be done by moving down to the BTS), which provides basic filtering, interpolation, etc., and provides basic input for the subsequent handover decision algorithm, which is the basis of the handover decision algorithm and the power control algorithm, etc.
Based on the traditional network optimization method, user experience information such as network coverage conditions, call quality conditions and the like can be obtained only through drive tests and fixed point tests, the drive tests and the fixed point tests can only be used for testing some main roads and key places, and the obtained sampling point data is much less than the user information of the MR, so that the analysis result is one-sidedness.
The MR tool processes the acquired measurement data for evaluation of the whole network wireless environment, replaces a large amount of routine drive tests and fixed point tests, and saves the operation and maintenance cost; the network is evaluated by the measurement report when the user actually has a call, the network is more targeted than the road measurement and the fixed point measurement, the collected data can be mined, the information such as the behavior pattern of the user, the distribution in a cell and the like can be analyzed, and the network optimization strategy can be conveniently formulated.
An example of a typical application of MR is: and (3) analyzing the traffic distribution of the cell: the periodic measurement report in the conversation process is analyzed to obtain the conversation position of the user, the distribution condition of telephone traffic in a cell can be obtained, and a basis is provided for network optimization work (cell power adjustment, carrier frequency increase, station address distribution adjustment and the like). Real-time assessment of wireless coverage: and a measurement report is collected, the wireless coverage condition in the cell is obtained, and the daily drive test expense of an operator is saved. Switching analysis: collecting measurement reports before/after switching to obtain the geographical distribution and wireless environment information of a switching area; analyzing the resources used in the switching process, positioning the fault of the specific resources and improving the success rate of switching; and analyzing the signaling of the switching process, and counting the switching reason and the switching failure reason. Malicious use network troubleshooting: checking the signaling process of the mobile phone, and judging whether a large number of calls are not connected; counting paging messages and finding out frequently called original numbers; and counting the number, the area and the time distribution of the short messages to be sent, and assisting in judging the sources of the spam short messages.
The monitoring step of the active area comprises:
and (3) partitioning road monitoring and time point identification for the motion state of the user through a dynamic analysis algorithm, distinguishing the activity state of the user according to a set place and a set time window, and calculating and analyzing the health condition change of the user.
The technical idea of the monitoring step of the activity area is as follows: when the middle-aged and old people walk, 60% -70% of muscle groups of a human body participate in activities, a large amount of body energy is consumed, and the support and coordination of a plurality of organ systems including a respiratory system, a circulatory system, a nervous system and a musculoskeletal system are needed. The middle-aged and elderly people walk fast, the heart and lung function is good, the conditions of all joints, particularly knee joints and hip joints, are good, the muscle condition of legs is good, the brain function and the cognitive function of the elderly people can be proved to be good, and in addition, the vision and hearing conditions can be reflected to a certain degree. Thus, the elderly population that walks quickly is relatively healthier. The walking speed of the ordinary people is 0.9 meter per second; for example, the middle-aged and old people with walking speed lower than 0.6 m/s are in poor health condition, and the walking speed is slow, which reflects that the body system of the old people is damaged, and also indicates that the old people needs to consume more energy when walking, so the walking speed can play a role in predicting the health condition.
Based on the pace as an important index for the health judgment of the middle-aged and the elderly, the monitoring step of the activity area comprises the following steps:
selecting a preset time period, finely dividing spontaneous activity walking of middle-aged and elderly people groups, dynamic body-building activity of the middle-aged and elderly people groups, high-speed movement of the middle-aged and elderly people groups, hospitalizing and shopping activity of the middle-aged and elderly people groups, spontaneous activity sun exposure of the middle-aged and elderly people groups, static sampling characteristics of the middle-aged and elderly people groups, and taking a threshold value sampling point as dynamic analysis algorithm data;
based on the selected scene of the middle-aged and elderly people group, dividing sampling points of the healthy middle-aged and elderly people group, which move at a high speed, move at a low speed and are static;
and according to the operation data of the first sampling point base station cell replacement threshold value to the second sampling point base station cell replacement threshold value of the healthy middle-aged and old people group, the dynamic analysis algorithm gives out the health condition information.
The system comprises a high-speed and medium-speed mobile middle-aged and elderly people group judgment, a low-speed mobile middle-aged and elderly people group judgment and a static state user judgment; the judgment conditions of the middle-aged and old people group moving at high and medium speed are as follows: in the site time window, the cell replacement times are more than or equal to the specified times, and the cell replacement distance is more than the threshold distance; the low-speed mobile middle-aged and elderly people group judgment conditions are as follows: in the time window, the cell replacement times are more than the specified times or the distance between the first cell and the last cell is less than the threshold distance; the static state user judgment conditions are as follows: within the time window, the cell change number is equal to 0.
In a specific embodiment, the monitoring of the activity area comprises:
s1, selecting specific time 6: 00-22:00, selecting WLAN/mobile phone app and signaling positioning data for dotting and identifying sampling points, finely dividing sampling points of spontaneous activities and walking of middle-aged and elderly people groups, dynamic body-building activities of the middle-aged and elderly people groups, high-speed movement of the middle-aged and elderly people groups, hospitalizing and shopping activities of the middle-aged and elderly people groups, spontaneous activities and sun exposure of the middle-aged and elderly people groups, static sampling characteristics and threshold values of the middle-aged and elderly people groups as dynamic analysis algorithm data.
And S2, dividing the sampling points of the healthy middle-aged and elderly people group into high-speed moving, low-speed moving and static sampling points based on the selected scenes of the middle-aged and elderly people group.
S3, computing data of the first sampling point base station cell replacement threshold value to the second sampling point base station cell replacement threshold value of the healthy middle-aged and old people group, and giving out good health condition prompt information by a dynamic analysis algorithm if the step speed of the healthy middle-aged and old people group is about 1.3 to 1.4 meters per second.
S4, the walking speed of the middle-aged and elderly people in sub-health state is about 0.8 meter per second along with the decline of physical condition. If the first sampling point base station cell replacement threshold of the middle-aged and old people group reaches the operation data of the second sampling point base station cell replacement threshold, if the step speed of the middle-aged and old people group in sub-health is lower than 0.6 m/s, the middle-aged and old people group can be said to be slow; the dynamic analysis algorithm gives prompt information of poor health condition.
S5, judging whether the spontaneous activity of the middle-aged and elderly people group is in walking movement, wherein the spontaneous activity of the middle-aged and elderly people group meets the non-static characteristic, and the ratio is 7: in a time window of 00-7:30, on the premise that users of middle-aged and elderly people in the mobile phone do not perform position switching, the specific position change pair degree of the position information and the GSI positioning sent to the 2G/4G communication network by frequent conversation or short message APP is greater than a set threshold value. And the dynamic analysis algorithm starts to calculate the pace of the middle-aged and old people according to a set threshold value.
S6, judging whether the middle-aged and old people are in the non-static state or not by sampling and judging whether the middle-aged and old people are in the static state or not, wherein the ratio of (7): in the time window of 00-9:30, the scheme deletes the active mode data and only keeps the passive mode data. The period of the passive mode is about 40-50min, the passive mode has the advantage of complete and stable acquired data, and the acquisition period can meet the precision requirement of a dynamic analysis algorithm during dynamic body-building activities of middle-aged and elderly people. And when the specific position change degree of the GSI positioning is lower than a set threshold, the dynamic analysis algorithm starts to calculate the dynamic body-building activity pace of the middle-aged and the elderly according to the set threshold. The key monitoring of the dynamic fitness activity and health condition of the middle-aged and the elderly is realized.
S7, dynamically moving the middle-aged and elderly people group at a high speed, movably sampling and judging the hospitalizing and shopping activities of the middle-aged and elderly people group, wherein the non-static characteristics of the middle-aged and elderly people group are met, and the ratio of the sampling rate to the sampling rate is 10: 00-10:30, 11: in a time window of 00-12:00, the mobile phone app and signaling positioning data geographic information are mapped to the hospitalizing shopping activity areas of the middle-aged and old people, a mathematical model relation is established according to historical wireless measurement information and known position information contained in the MR/CQT of the mobile phone signaling positioning data areas of the middle-aged and old people, the specific position of each hospitalizing shopping activity point is determined, and the specific position change degree of GSI positioning is lower than a set threshold value. And calculating and analyzing the health condition change monitoring of traffic outgoing of the middle-aged and old people by using a dynamic analysis algorithm.
S8, the middle-aged and old people group is static dynamically, the middle-aged and old people group is sunned spontaneously, the activity is sampled and judged movably, the static characteristic of the middle-aged and old people group is met, and the ratio of the activity to the activity is 12: 00-14:00, 15: 00-17:00, 18: 00-21:00 time window. The signaling monitoring obtains the communication characteristics of the middle-aged and elderly people group, and analyzes the behaviors of the middle-aged and elderly people group according to the following periodic MR data:
time window 12: 00-14:00, 18: 00-21:00 stay time in the same main service cell or adjacent cell exceeds 2-5 hours;
time window 12: 00-14:00, 18: 00-21:00 has a range of motion less than 10 meters and a speed less than 0.6 meters per second during this period;
time window 12: 00-14:00, 18: 00-21:00 continuous monitoring time length in the same main service cell or adjacent cell exceeds 0-30 minutes of communication, internet surfing and short message communication behaviors;
and the dynamic analysis algorithm starts to calculate and analyze the health condition change monitoring of the stationary middle-aged and old people and the spontaneous activity of the sun-sunning activity of the middle-aged and old people.
The technical solution of the monitoring step of the activity area is explained in the following from the perspective of model calculation.
The calculation process for calculating and analyzing the health condition change of the user comprises the following steps:
and (3) mixing the following components: 00-7:30, 7: 00-9:30, 10: 00-10:30, 11: 00-12:00, 12: 00-14:00, 15: 00-17:00, 18: seven time periods 00-21:00 are positioned at a starting point, the activity of the middle-aged and elderly people in each time period is switched from one health degree state to another health degree state to finish a feasible solution of an activity area, and when all the middle-aged and elderly people finish respective activity areas according to different time periods, different routes and different speeds, the obtained data is used for updating and calculating, and a dynamic analysis algorithm is guided to obtain a final solution of the health degree.
The calculation formula (1) related to the final solution of the health degree obtained by calculation is as follows:
different time periods l, different speeds rho, health degree deviation omega, middle-aged and elderly people group activity area
G number of middle aged and elderly people, BkThe health degree value, k is the value of abnormal judgment of the health degree, epsilon is the updating value of the health degree, and a represents the starting position b represents the ending position.
Aiming at different routes and different speeds, the health degree index of the middle-aged and elderly people is calculated by a dynamic weighting method through aggregation analysis:
acquiring a dynamic health index function W of the aggregate analysis of the middle-aged and elderly people:
in the formula, L represents the length of a regional site target of the middle-aged and elderly people; x is the number oftRepresenting the normal time value of the line of the middle-aged and the elderly; x is the number offRepresenting the actual time value of the line of the middle-aged and elderly people; coefficient of performance
Representing a preferential transaction selection made based on one day activity, coefficient
The time value of the line of the middle-aged and old people can be 0.9, and the actual time value of the line of the middle-aged and old people is a function of the health index; the normal time value of the middle-aged and old people group line is associated with the aggregation analysis dynamic health index of the middle-aged and old people group;
calculating the dynamic health value of each route aggregation analysis in the area graph connecting the starting point and the target point formed by dividing the communication network according to a formula, taking the nth edge as an example:
the method is characterized in that the daily activity area site targets of the middle-aged and old people are set to be the same and are not mutually connected, and the health degree index model of the middle-aged and old people is simplified, so that when the middle-aged and old people move along the (n + 1) th route of an activity area, the health degree index can divide the activity area site targets into seven sections to be calculated to obtain the following formula:
in the formula, s represents the distance of the activity area of the nth middle-aged and old people group every day; n represents the number of levels of the health indicator;
the distance of the 1 st-7 th path health index test is shown, and the chi is considered under the condition that the speeds of the moving area and the place of the middle-aged and old people every day are the sameiWhen S, then X∫i＝Sn。
In a specific embodiment, the calculation process for calculating and analyzing the change in the health condition of the user specifically includes the following steps:
in this embodiment, the statistical time of the dynamic activities of the middle-aged and elderly people in one day is designed to be 7 intervals, 7: 00-7:30, 7: 00-9:30, 10: 00-10:30, 11: 00-12:00, 12: 00-14:00, 15: 00-17:00, 18: 00-21:00, taking the position of a residential area of a middle-aged and elderly people group as a starting point, setting the position of a solar area target in different time periods, in which spontaneous activities of the middle-aged and elderly people group are scattered, dynamic fitness activities of the middle-aged and elderly people group, high-speed movement of the middle-aged and elderly people group, hospitalizing and shopping activities of the middle-aged and elderly people group, and spontaneous activities of the middle-aged and elderly people group shine on the sun, as a target point, and dividing a communication network to form an area map connecting the starting point and the target point by dotting identification on a GSI positioning WLAN/mobile phone app and signaling positioning data. And calculating the health index of the middle-aged and elderly people by a dynamic weighting method of aggregation analysis at different routes and different speeds.
In the formula, L represents the length of a regional site target of the middle-aged and elderly people; w represents a dynamic health index function of the aggregate analysis of the middle-aged and the elderly; x is the number oftRepresenting the normal time value of the line of the middle-aged and the elderly; x is the number offRepresenting the actual time value of the line of the middle-aged and elderly people; coefficient of performance
Representing a biased transaction selection made based on one day activity. Coefficient of performance
The actual time value of the circuit of the middle-aged and old people group is a function of the health index; and the normal time value of the line of the middle-aged and old people is associated with the aggregation analysis dynamic health index of the middle-aged and old people.
Calculating the dynamic health value of each route aggregation analysis in the area graph connecting the starting point and the target point formed by dividing the communication network according to a formula, taking the nth edge as an example, the method comprises the following steps:
in this embodiment, the target of the daily activity area of the middle-aged and elderly people is the same and is not linked to each other, and the health index model of the middle-aged and elderly people is simplified, so that when the middle-aged and elderly people move along the (n + 1) th route of the activity area, the health index can simply divide the activity area target into seven segments for calculation, and the formula is as follows:
in the formula, s represents the distance of the activity area of the nth middle-aged and old people group every day; n represents the number of levels of the health indicator;
and the like, the distance of the 1 st path to the 7 th path health index test is shown, and the chi can be simply considered to be that the speed of the middle-aged and old people in the moving area every day is the sameiWhen S, then X∫i＝Sn。
In the embodiment, the activity health degree prediction model of the middle-aged and elderly people can be obtained by an aggregation analysis dynamic calculation method. The health degree of the activity area of the middle-aged and old people group has certain regularity and random uncertainty in time, the health degree is divided into different levels according to the reduction condition of the activity area time, the higher the relative reduction amount is, the higher the health degree abnormal level is, and the value of health degree abnormal judgment of the middle-aged and old people group is continuously corrected according to dynamic data of aggregation analysis to identify the individual difference of the middle-aged and old people group and the health degree deviation generated by seasonal variation.
When the dynamic health degree activity behaviors are analyzed by carrying out aggregate analysis on the old people, 7: 00-7:30, 7: 00-9:30, 10: 00-10:30, 11: 00-12:00, 12: 00-14:00, 15: 00-17:00, 18: seven time periods of 00-21:00 are positioned at the starting point, and the activities of the middle-aged and elderly people in each time period are converted from one health degree state to another health degree state by using a certain health degree state conversion rule to finish a feasible solution of an activity area. When all the middle-aged and elderly people are in different time periods. After the respective activity areas are finished in different routes and at different speeds, the obtained data are used for updating the calculation rules, and the data updating process can guide the dynamic analysis algorithm to obtain the final health degree solution.
The data updating rule of the dynamic analysis algorithm of the activity area of the old people is as follows.
Updating rules
Different time periods l, different speeds rho, health degree deviation omega, middle-aged and elderly people group activity area
G number of middle aged and elderly people, BkHealth value, k value for abnormal health determination. The value of ε health update, a represents the starting location and b represents the location of the termination.
In conclusion, the invention identifies the normal and abnormal walking speeds of the middle-aged and elderly people through the mobile phone terminal. And real-time monitoring and analysis are carried out, and according to the activity prediction model of the middle-aged and old people and the activity historical database of the middle-aged and old people. The safety monitoring of the outgoing distance and range behavior detection and identification of the middle-aged and old people and the health degree of the middle-aged and old people by the mobile phone terminal is realized. When abnormal conditions occur, the alarm for the indoor activity time abnormity of the middle-aged and the old people and the alarm for the outdoor activity time abnormity of the middle-aged and the old people are realized. And the abnormal information and the monitoring result of the middle-aged and old people are transmitted to a 5G edge data center, so that the middle-aged and old people are informed of the relatives and community medical staff of the residence to take corresponding treatment measures as soon as possible in the shortest time, and the personal safety of the middle-aged and old people is ensured.
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.
Furthermore, it should be understood that although the present description refers to embodiments, not every embodiment may contain only a single embodiment, and such description is for clarity only, and those skilled in the art should integrate the description, and the embodiments may be combined as appropriate to form other embodiments understood by those skilled in the art.
Claims (7)
1. A monitoring method for middle-aged and elderly people based on a mobile phone terminal is characterized by comprising the following steps: a residential monitoring step and an activity area monitoring step;
the residential housing monitoring step comprises the following steps:
scanning MAC addresses of Wi-Fi routers around through a Wi-Fi chip of a mobile phone of a user, or determining the actual geographic position of the user through a periodic MR (magnetic resonance) of a wireless side when the user surfs the internet;
judging whether the actual geographical position exceeds a preset movement range within a specified time period according to the determined actual geographical position, and if so, indicating that the user activity is normal;
the monitoring step of the active area comprises:
road monitoring and time point identification are carried out on the user motion state in a partitioning mode through a dynamic analysis algorithm, the activity state of the user is distinguished according to a set place and a set time window, and the health condition change of the user is calculated and analyzed;
the calculation process for calculating and analyzing the health condition change of the user comprises the following steps:
and (3) mixing the following components: 00-7:30, 7: 00-9:30, 10: 00-10:30, 11: 00-12:00, 12: 00-14:00, 15: 00-17:00, 18: seven time periods 00-21:00 are positioned at a starting point, the activity of the middle-aged and elderly people in each time period is switched from one health degree state to another health degree state to finish a feasible solution of an activity area, and when all the middle-aged and elderly people finish respective activity areas according to different time periods, different routes and different speeds, the obtained data is used for updating and calculating, and a dynamic analysis algorithm is guided to obtain a final solution of the health degree;
the calculation formula (1) for calculating and analyzing the change of the health condition of the user is as follows:
different time periods l, different speeds rho, health degree deviation omega, middle-aged and elderly people group activity area
G number of middle aged and elderly people, BkThe health degree value, k, the abnormal health degree judgment value and epsilon, s represents the distance of the activity area of the middle-aged and old people, and a represents the starting position and b represents the ending position.
2. The middle-aged and elderly people group monitoring method based on mobile phone terminal as claimed in claim 1, wherein determining the actual geographical location of the user by the MAC address comprises:
and transmitting the MAC address to a background server through an internet network, acquiring the actual longitude and latitude position information of the Wi-Fi router stored in the background server, and calculating the actual geographic position of the mobile phone of the user according to the wifi signal intensity.
3. The middle-aged and elderly people group monitoring method based on mobile phone terminal as claimed in claim 2, wherein determining the actual geographical location of the user by the MAC address further comprises:
and correcting the MAC address calculation error of the router, and simultaneously, directly positioning to the GPS coordinate of the residential residence of the user by using IP positioning of the used app of the mobile phone through OTT mobile phone app or hundred-degree big data service, and correcting the MAC address calculation error of the router again.
4. The middle-aged and elderly people group monitoring method based on mobile phone terminal as claimed in claim 1, wherein determining the actual geographical location of the user through the MR comprises:
and extracting parameters of a user main service cell in the MR signaling through periodical MR analysis of a wireless side when the user surfs the internet, and if the user main service cell is an indoor cell at the moment, taking the longitude and latitude of the cell as the longitude and latitude of the current position of the user.
5. The middle-aged and elderly people group monitoring method based on mobile phone terminal as claimed in claim 1, wherein the monitoring step of the active area comprises:
selecting a preset time period, finely dividing spontaneous activity walking of middle-aged and elderly people groups, dynamic body-building activity of the middle-aged and elderly people groups, high-speed movement of the middle-aged and elderly people groups, hospitalizing and shopping activity of the middle-aged and elderly people groups, spontaneous activity sun exposure of the middle-aged and elderly people groups, static sampling characteristics of the middle-aged and elderly people groups, and taking a threshold value sampling point as dynamic analysis algorithm data;
based on the selected scene of the middle-aged and elderly people group, dividing sampling points of the healthy middle-aged and elderly people group, which move at a high speed, move at a low speed and are static;
and according to the operation data of the first sampling point base station cell replacement threshold value to the second sampling point base station cell replacement threshold value of the healthy middle-aged and old people group, the dynamic analysis algorithm gives out the health condition information.
6. The middle-aged and elderly people group monitoring method based on mobile phone terminal as claimed in claim 5, wherein the high-speed and middle-aged people group determination, the low-speed and middle-aged people group determination, and the user determination in stationary state; the judgment conditions of the middle-aged and old people group moving at high and medium speed are as follows: in the site time window, the cell replacement times are more than or equal to the specified times, and the cell replacement distance is more than the threshold distance; the low-speed mobile middle-aged and elderly people group judgment conditions are as follows: in the time window, the cell replacement times are more than the specified times or the distance between the first cell and the last cell is less than the threshold distance; the static state user judgment conditions are as follows: within the time window, the cell change number is equal to 0.
7. The middle-aged and elderly people group monitoring method based on mobile phone terminal as claimed in claim 1, wherein for different routes and different speeds, the health degree index of the middle-aged and elderly people group is calculated by aggregation analysis dynamic weighting method:
acquiring a dynamic health index function W of the aggregate analysis of the middle-aged and elderly people:
in the formula, L represents the length of a regional site target of the middle-aged and elderly people; x is the number oftRepresenting the normal time value of the line of the middle-aged and the elderly; x is the number offRepresenting the actual time value of the line of the middle-aged and elderly people; coefficient of performance
Representing a preferential transaction selection made based on one day activity, coefficient
Taking the actual time value of the circuit of the middle-aged and old people as 0.9, wherein the actual time value is a function of the health index; the normal time value of the middle-aged and old people group line is associated with the aggregation analysis dynamic health index of the middle-aged and old people group;
calculating the dynamic health value of each route aggregation analysis in the area graph connecting the starting point and the target point formed by dividing the communication network according to a formula, taking the nth edge as an example:
the method comprises the following steps that the daily activity area location targets of middle-aged and old people are set to be the same and are not mutually connected, and health degree index models of the middle-aged and old people are simplified, so that when the middle-aged and old people move along the (n + 1) th route of an activity area, the activity area location targets are divided into seven sections by the health degree indexes to be calculated, and the following formula is obtained:
in the formula, s represents the distance of the activity area of the nth middle-aged and old people group every day; n represents the number of levels of the health indicator;
the distance of the 1 st-7 th path health index test is shown, and the chi is considered under the condition that the speeds of the moving area and the place of the middle-aged and old people every day are the sameiWhen S, then X∫i＝Sn。
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