CN113298577A - Abnormal state alarm monitoring method for solitary old people based on intelligent monitoring terminal - Google Patents
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Abstract
The invention discloses an abnormal state alarm monitoring method for solitary old people based on an intelligent monitoring terminal, which belongs to the technical field of power utilization alarm monitoring. The method has simple principle, convenient use and objective and credible result, and can be used for monitoring the life of the solitary old people for a long time. Before the device is installed on a household appliance meter of a second user, the electricity utilization burden of the solitary old man does not need to be increased, and the device is more economical and has higher popularization and application values.
Description
Technical Field
The invention relates to the technical field of electricity utilization alarm monitoring, in particular to a method for monitoring abnormal state alarm of solitary old people based on an intelligent monitoring terminal.
Background
The seventh national census data shows that the population of 60 years old and over is 2.64 hundred million in China, which accounts for 18.70 percent of the total population, the aging process of the population is irreversible, and the number of solitary old people is increased. The elderly are in the home alone and face many safety risks, for example, accidents happen at home without being aware of the accidents, or the elderly do not return home for a long time when going out, or abnormal operation of home appliances can cause serious consequences. The installation monitoring can realize the acquisition of the condition at home, but is limited to economic reasons, the privacy of old people's life and the monitoring range of a camera, and the large-area all-round monitoring installation can not be realized. The household electricity consumption condition can comprehensively reflect the life track and the life characteristics of the old people, and the electricity consumption data implies that the old people use each electric appliance and the working condition of each electric appliance at home. The power consumption data of the solitary old people are monitored and deeply excavated, the household power consumption behavior of the old people is analyzed, the alarm can be effectively and timely sent out for the abnormal conditions of the old people, and the independent household safety of the old people is guaranteed.
Currently, the following technical defects exist in the problem:
1. at present, the intelligent electric meter has large data acquisition time interval, less data, poor granularity of characterization power consumption behavior and poor real-time property of data application, and is difficult to meet the abnormal alarm requirement of the solitary old people.
2. At present, the living electricity utilization habit of the solitary old man does not have a sufficient sample, the electricity utilization condition and the living track of the old man are difficult to be directly analyzed from the electricity utilization monitoring data, and the data need to be continuously mined.
3. At present, no detailed label for dividing the household electricity consumption of the solitary old people exists, and the alarm can not be sent out accurately in a targeted manner.
Based on the above, the invention designs an abnormal state alarm monitoring method for solitary old people based on an intelligent monitoring terminal, so as to solve the problems.
Disclosure of Invention
The invention aims to provide an abnormal state alarm monitoring method for solitary old people based on an intelligent monitoring terminal, so as to solve the technical problems.
In order to realize the purpose, the invention provides the following technical scheme: an abnormal state alarm monitoring method for solitary old people based on an intelligent monitoring terminal comprises the following steps:
step S1: acquiring user information in a power supply jurisdiction, screening out solitary old people users according to the user information, installing an intelligent detection terminal on a user power utilization inlet, and setting a background intelligent terminal which is in communication connection with the intelligent detection terminal, wherein the intelligent detection terminal acquires power utilization data of each minute of the users and sends the data to the background intelligent terminal for storage;
step S2: presetting early warning types and power utilization behavior labels according to the investigation result and the power utilization habits of the old people, and judging the corresponding user condition;
step S3: after the stored data is subjected to data processing, analyzing the data in a certain period of time, matching the data with judgment conditions to obtain the power utilization condition of the user in the period of time, and determining whether to take early warning or warning action;
step S4: and sending the abnormal power utilization condition and the corresponding old people condition to relevant departments for timely processing.
Preferably, in step S2, first, three types of the early warning types, namely normal user, early warning required, and warning required, are determined;
dividing one day into four time periods of late night, morning, noon and evening by referring to the working and rest and electricity utilization habits of the old, sequentially judging whether the electricity consumption of each time period of each user per day is increased or decreased to judge whether the household electricity consumption of the user is abnormal or not, and then setting the household condition of the corresponding solitary old;
when the power consumption is increased at night, the abnormal sleep state of the old is corresponded; when the electricity consumption is increased in the morning, the noon and the evening, the suspected discomfort of the body of the old can be judged, and the old can be kept at home; when the electricity consumption is reduced in the morning, the noon and the evening, the body of the old is judged to be suspected to be uncomfortable, and the old is kept in bed.
Preferably, step S3 specifically includes:
step S31: reading and analyzing whether the acquired data has missing items, and if so, filling up missing values according to actual needs;
step S32: setting a proper time window length, taking the power consumption every day as a node, and dividing one day into four time periods of late night, morning, afternoon and evening; calculating the average value DP and the variance sigma of the power consumption of the solitary old man in each time period2Maximum value and information entropy, wherein:
wherein n represents the number of sampling days, represents the total power consumption sampled by each user at the zero point of the jth day, represents the total power consumption sampled by the ith user at the zero point of the jth-1 day, and is the average value of all the power consumptions of the users;
step S33: dividing the selected time window into two parts, and calculating a part of historical data to obtain a dynamic threshold;
step S34: obtaining a dynamic threshold value in a selected time window, and if the power consumption of a user exceeds 1.7 times of the threshold value and lasts for a period of time, rapidly increasing the corresponding label for a short time and needing early warning processing;
step S35: in a selected time window, carrying out background stripping on the acquired data, judging whether people use electricity or not, and if no people use electricity or no electricity is used in two days, carrying out early warning processing;
step S36: if the voltage is zero continuously in normal current in a selected time period, or if the power consumption deviates from a normal value and is not recovered for a long time; an alarm needs to be made.
Compared with the prior art, the invention has the beneficial effects that:
the method fully excavates the value of the acquired power consumption data under the conditions of simple equipment installation and low cost, calculates the power consumption of each user at each time period every day through analysis, deduces the living solitary old with abnormal living conditions through the power consumption condition of the users, and determines whether to carry out alarm or early warning treatment. The method has simple principle, convenient use and objective and credible result, and can be used for monitoring the life of the solitary old people for a long time. Before the device is installed on a household appliance meter of a second user, the electricity utilization burden of the solitary old man does not need to be increased, and the device is more economical and has higher popularization and application values.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained based on these drawings without creative efforts.
FIG. 1 is a flow chart of an abnormal state alarm analysis method for solitary old people.
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.
The invention is further explained below with reference to the figures and the specific embodiments.
The invention provides an abnormal state alarm analysis method for solitary old people based on an intelligent power consumption monitoring terminal, which mainly comprises the following steps:
(1) acquiring user information in a power supply jurisdiction, screening out solitary old people users according to the user information, installing an intelligent detection terminal on a user power utilization inlet, and setting a background intelligent terminal which is in communication connection with the intelligent detection terminal, wherein the intelligent detection terminal acquires power utilization data of each minute of the users and sends the data to the background intelligent terminal for storage;
(2) and presetting early warning categories and power utilization behavior labels according to the investigation result and the power utilization habits of the old people, and judging the corresponding user condition.
(3) And after the stored data is subjected to data preprocessing, analyzing the data in a certain period of time, matching the data with the judgment condition to obtain the power utilization condition of the user in the period of time, and determining whether to take early warning or alarming action.
(4) And sending the abnormal power utilization condition and the corresponding old people condition to relevant departments for timely processing.
As shown in fig. 1, after contacting with community service personnel, acquiring user information in a power supply district, and screening out solitary old people users according to the user information. The intelligent detection terminal is installed on the electricity utilization entrance of the user, the background intelligent terminal which is in communication connection with the intelligent detection terminal is arranged, the intelligent terminal acquires and stores the acquired data, the time interval of the data acquired by the electricity utilization condition is 1 minute, and all the started electrical appliances of background electricity noise and artificial electricity utilization of non-artificial electricity utilization are included in each day and each time period.
And step two, firstly, determining three types of the early warning types, namely normal user types, early warning types and warning types.
For the category needing early warning, starting from power data, referring to the daily work and rest and electricity utilization habits of the old, dividing one day into four time periods of late night, morning, noon and evening, taking the increase or decrease of electricity consumption in a certain time period of two or more continuous days as a judgment condition to judge whether the electricity consumption of the user at home is abnormal or not, and setting the home condition corresponding to the solitary old.
When the power consumption is increased at night, the method corresponds to the situations that the old people are abnormal in sleeping state or do not work continuously, and the like; when the electricity consumption is increased in the morning, the noon and the evening, the suspected discomfort of the body of the old can be judged, and the old can be kept at home; when the electricity consumption is reduced in the morning, the noon and the evening, the body of the old is judged to be suspected to be uncomfortable, and the old is kept in bed.
And (3) checking the outliers in the detected data by using a 4d checking method, wherein the outliers are determined by the formula:
the mean value of the remaining data after the power outlier is removed is shown, and the mean deviation of the remaining data after the outlier is removed is shown. If the detected outlier greatly deviates from the normal value and the outliers of the continuous time points appear, the power utilization short-time surge overhigh label is given to the situation.
The time interval for acquiring data by the power consumption monitoring system for the solitary old people is 1 minute, and the data acquired by each test point simultaneously comprise background power consumption noise of non-artificial power consumption and the sum of power consumption of all started electrical appliances of artificial power consumption. When the artificial electricity consumption in the monitoring period is far lower than a normal value and the duration is long, the state of extreme discomfort and long-term bed rest of the old is corresponded; when the non-artificial electricity consumption in the detection period is lower than a normal value and the duration is long, the body of the old is extremely uncomfortable. And (5) going out to seek medical treatment.
For the alarm category, from the current and power, the following alarm categories can be classified: if the electricity consumption greatly deviates from the normal state and lasts for a period of time, the label that the electricity consumption is continuously too high can be given to the user, and the situation that the electricity consumption is unsafe corresponds to the user and the like; if the voltage is normal and the current is zero, the trip alarm is given to the circuit breaker, and the situations of safety problem, closing of the main brake when going out for a long time and the like are correspondingly solved.
The power utilization abnormal condition of the user is informed to relevant power departments, the abnormal power condition is checked and maintained in time, the abnormal condition of the solitary old people is informed to the community in time, community personnel can check the abnormal condition in time, and the home safety of the old people is guaranteed.
For step three, the patent selects data with a time sliding window length of 15 days for analysis, each household has 15 × 24 × 60 data per day, and power time sequence data of N users can be represented as P1＝<p11,…,p1n>，P2＝<p21,…,p2n>，……PN＝<pN1,…,pNn>. Preparing for subsequent data analysis and calculation ifWhen the device is off-line due to external device reasons, the missing items are filled according to actual requirements, and the filled data can be represented as P1’＝<p11’,…,p1n’>、P2’＝<p21’,…,p2n’>、……PN’＝<pN1’,…,pNn’>。
The monitoring data after being preprocessed by a certain user is Pi’＝<pi1’,…,pin’>Dividing one day into four time periods according to time, and respectively using Pia’＝<pia1’,…,piam’>、Pib’＝<pib1’,…,pibm’>、Pic’＝<pic1’,…,picm’>、Pid’＝<pid1’,…,pidm’>And the average value DP and the variance sigma of the power of the four time segments are respectively obtained2Maximum, entropy, etc.
Wherein n represents the number of sampling days, represents the total power consumption sampled by each user at the zero point of the jth day, represents the total power consumption sampled by the ith user at the zero point of the jth-1 day, and is the average value of all the power consumptions of the users.
Selecting the average value of the previous part of historical electricity consumption in the time window as a dynamic threshold value, judging the electricity consumption state of the user, if the electricity consumption of the user is more than 1.5 times of the dynamic threshold value, judging that the electricity consumption is increased in a certain period, and if the electricity consumption is increased for two or more consecutive days in the same period, judging that the electricity consumption is abnormal, and performing early warning.
And (3) calculating the average value of the maximum power consumption values of each user in the time window to serve as a dynamic threshold for judging whether the power consumption is increased rapidly, and if the power consumption is more than 1.7 times of the dynamic threshold and the duration time reaches five minutes, judging that the power consumption is increased rapidly in a short time, the power consumption is abnormal and early warning is needed.
In the selected time window, if the data is far smaller than the normal value in the time interval, whether the electricity is used by people is judged, and the electricity background quantity and the artificial electricity consumption quantity of the electrical equipment can be distinguished through bidirectional pulse filtering.
Firstly, the fluctuation of the power consumption caused by the operation of the electric appliance is removed. Comparing the electricity consumption of the whole day, and covering the data in the period of time by the average value of the data when the fluctuation value of the electricity consumption is less than a certain value.
Second, the change in electricity usage throughout the day is recorded. And extracting and recording the data characteristics of the pulse width and the height of the power consumption all day, and selecting the pulse width and the pulse height of the power consumption change caused by the work of the background electric appliance as reference values. The data records the magnitude of the change in power consumption and the duration of the change due to the turning on and off of the appliance throughout the day.
Thirdly, the background quantity stripping is carried out on the data by turning on the electrical equipment. When some electric appliance starts to work, the change value of the current power consumption and the on duration of the electric appliance are compared with the reference value, if the difference is not large, the power data change is judged to be caused by the background quantity of the electric appliance, and the background quantity is removed.
Fourthly, removing the background quantity of the data for the second time by closing the electrical equipment. When the electric appliance stops working, the change of the power consumption and the opening time before closing are compared with the reference value, if the difference is not large, the power data change is judged to be caused by the background quantity of the electric appliance at the moment, and the power data change is removed. So far, the purpose of removing the background quantity of electricity consumption of the first layer of electrical equipment is achieved.
Fifthly, in order to remove the large background quantity appearing in late night when the cars are irregular in other appearing periods, only deep mining is carried out on late night data, the background quantity of the second layer of electric appliances is determined, and the steps of removing the background quantity in other periods are consistent with the steps.
After the background component of the non-artificial electricity consumption of the home of the user and the power consumed by each electrical appliance for artificial electricity consumption are separated, whether the electricity is consumed by people or not can be judged, and if the electricity is not consumed by people within two days, the bed can be suitable for the solitary old people with extreme discomfort for long-term lying; if no electricity is used within two days, the solitary old people can be treated correspondingly due to physical discomfort outside; an early warning process is required.
If the normal voltage and current are continuously zero in the selected time period, a trip alarm can be given; if the electricity consumption deviates from the normal value and is not recovered for a long time, the electricity consumption is continuously too high, and abnormal electricity consumption phenomena such as unsafe electricity consumption, electricity stealing and the like exist; an alarm needs to be made.
The above embodiments are provided only for illustrating the present invention, and those skilled in the art can make various changes or modifications without departing from the spirit and scope of the present invention, and therefore, all equivalent technical solutions should also fall within the scope of the present invention.
Claims (3)
1. An abnormal state alarm monitoring method for solitary old people based on an intelligent monitoring terminal is characterized in that: the method comprises the following steps:
step S1: acquiring user information in a power supply jurisdiction, screening out solitary old people users according to the user information, installing an intelligent detection terminal on a user power utilization inlet, and setting a background intelligent terminal which is in communication connection with the intelligent detection terminal, wherein the intelligent detection terminal acquires power utilization data of each minute of the users and sends the data to the background intelligent terminal for storage;
step S2: presetting early warning types and power utilization behavior labels according to the investigation result and the power utilization habits of the old people, and judging the corresponding user condition;
step S3: after the stored data is subjected to data processing, analyzing the data in a certain period of time, matching the data with judgment conditions to obtain the power utilization condition of the user in the period of time, and determining whether to take early warning or warning action;
step S4: and sending the abnormal power utilization condition and the corresponding old people condition to relevant departments for timely processing.
2. The abnormal state alarm monitoring method for solitary old people based on the intelligent monitoring terminal according to claim 1, characterized in that:
in step S2, firstly, three types of early warning types, namely normal user types, early warning types and warning types, are determined;
dividing one day into four time periods of late night, morning, noon and evening by referring to the working and rest and electricity utilization habits of the old, sequentially judging whether the electricity consumption of each time period of each user per day is increased or decreased to judge whether the household electricity consumption of the user is abnormal or not, and then setting the household condition of the corresponding solitary old;
when the power consumption is increased at night, the abnormal sleep state of the old is corresponded; when the electricity consumption is increased in the morning, the noon and the evening, the suspected discomfort of the body of the old can be judged, and the old can be kept at home; when the electricity consumption is reduced in the morning, the noon and the evening, the body of the old is judged to be suspected to be uncomfortable, and the old is kept in bed.
3. The method for monitoring abnormal state of solitary old people based on intelligent monitoring terminal as claimed in claim 1, wherein step S3 specifically comprises:
step S31: reading and analyzing whether the acquired data has missing items, and if so, filling up missing values according to actual needs;
step S32: setting a proper time window length, taking the power consumption every day as a node, and dividing one day into four time periods of late night, morning, afternoon and evening; calculating the average value DP and the variance sigma of the power consumption of the solitary old man in each time period2Maximum value and information entropy, wherein:
wherein n represents the number of sampling days, represents the total power consumption sampled by each user at the zero point of the jth day, represents the total power consumption sampled by the ith user at the zero point of the jth-1 day, and is the average value of all the power consumptions of the users;
step S33: dividing the selected time window into two parts, and calculating a part of historical data to obtain a dynamic threshold;
step S34: obtaining a dynamic threshold value in a selected time window, and if the power consumption of a user exceeds 1.7 times of the threshold value and lasts for a period of time, rapidly increasing the corresponding label for a short time and needing early warning processing;
step S35: in a selected time window, carrying out background stripping on the acquired data, judging whether people use electricity or not, and if no people use electricity or no electricity is used in two days, carrying out early warning processing;
step S36: if the voltage is zero continuously in normal current in a selected time period, or if the power consumption deviates from a normal value and is not recovered for a long time; an alarm needs to be made.
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| CN111179109A (en) * | 2019-11-29 | 2020-05-19 | 国网浙江省电力有限公司杭州供电公司 | Electricity consumption data processing method for detecting elderly people living alone |
| CN112396087A (en) * | 2020-09-28 | 2021-02-23 | 国网浙江省电力有限公司杭州供电公司 | Smart electric meter based method and device for analyzing electricity consumption data of elderly people living alone |
| CN112750276A (en) * | 2020-12-29 | 2021-05-04 | 杭州拓深科技有限公司 | Method and system for nursing old people living alone based on electric equipment identification |
| CN112801154A (en) * | 2021-01-19 | 2021-05-14 | 城云科技（中国）有限公司 | Behavior analysis method and system for solitary old people |
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