CN111753909A - Residence information monitoring method, device, equipment and storage medium - Google Patents
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Abstract
The invention discloses a residence information monitoring method, a residence information monitoring device, residence information monitoring equipment and a residence information monitoring storage medium. The method comprises the following steps: periodically acquiring daily electricity and daily electricity mutation rates within preset time of at least two users; clustering according to the daily electric quantity and the daily electric quantity mutation rate, and classifying the users; according to the classification result, the residence information of the user in the preset time is monitored, and through the technical scheme of the invention, the problems of large workload, long period and poor effect in monitoring in the prior art are solved.
Description
Technical Field
The embodiment of the invention relates to computer technology, in particular to a residence information monitoring method, a residence information monitoring device, residence information monitoring equipment and a residence information monitoring storage medium.
Background
Personnel monitoring and troubleshooting are important means when carrying out work such as safety monitoring, epidemic situation prevention and the like. Currently, there are 2 main techniques for monitoring personnel:
monitoring the person entering the house: the staff checks one by going to the door next to the door, and the method has the problems of large workload, long period and the like.
Manual remote monitoring: the monitoring is carried out by the staff in a mode of making a call and the like, the method also has the problems of large workload, long period and the like, and the monitoring effect is inferior to that of the monitoring of the home-entry due to insufficient information, unreal information fed back by the object and the like.
The monitoring of entering a house needs to be carried out by going to the house one by one, a large amount of manpower and time are consumed, the situation of the site for examination of entering the house is complex, and a plurality of uncertain factors exist on the site, so that the monitoring effect is influenced. The manual remote monitoring is to collect information by means of information such as telephone call, the total workload is smaller than that of home monitoring, but the monitoring quality is inferior to that of home monitoring due to the influence of incomplete collected information, unrealistic feedback information of a monitoring object and other factors.
Disclosure of Invention
The embodiment of the invention provides a residence information monitoring method, a residence information monitoring device, residence information monitoring equipment and a residence information monitoring storage medium, and aims to solve the problems of large workload, long period and poor effect in monitoring in the prior art.
In a first aspect, an embodiment of the present invention provides a method for monitoring occupancy information, including:
periodically acquiring daily electricity and daily electricity mutation rates within preset time of at least two users;
clustering according to the daily electric quantity and the daily electric quantity mutation rate, and classifying the users;
and monitoring the residence information of the user within the preset time according to the classification result.
In a second aspect, an embodiment of the present invention further provides a living information monitoring apparatus, where the apparatus includes:
the acquisition module is used for periodically acquiring daily electric quantity and daily electric quantity mutation rate within preset time of at least two users;
the clustering module is used for clustering according to the daily electric quantity and the daily electric quantity mutation rate and classifying the users;
and the monitoring module is used for monitoring the living information of the user within the preset time according to the classification result.
In a third aspect, an embodiment of the present invention further provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the occupancy information monitoring method according to any one of the embodiments of the present invention is implemented.
In a fourth aspect, the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the occupancy information monitoring method according to any one of the embodiments of the present invention.
The embodiment of the invention periodically obtains the daily electricity consumption and the daily electricity consumption mutation rate within the preset time of at least two users; clustering according to the daily electric quantity and the daily electric quantity mutation rate, and classifying the users; and monitoring the residence information of the user within the preset time according to the classification result so as to solve the problems of large workload, long period and poor effect in the monitoring in the prior art.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a flowchart of a housing information monitoring method according to a first embodiment of the present invention;
fig. 2 is a schematic structural diagram of a residence information monitoring apparatus according to a second embodiment of the present invention;
fig. 3 is a schematic structural diagram of a computer device in a third embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures. Meanwhile, in the description of the present invention, the terms "first", "second", and the like are used only for distinguishing the description, and are not to be construed as indicating or implying relative importance.
Example one
Fig. 1 is a flowchart of a residence information monitoring method according to an embodiment of the present invention, where this embodiment is applicable to a residence information monitoring situation, and the method may be executed by a residence information monitoring device according to an embodiment of the present invention, where the residence information monitoring device may be implemented in a software and/or hardware manner, as shown in fig. 1, the method specifically includes the following steps:
and S110, periodically acquiring daily electric quantity and daily electric quantity mutation rate within preset time of at least two users.
The period may be one month, and may also be set as required, which is not limited in this embodiment of the present invention.
The preset time may be one month, or 3 days, and may also be set as required, which is not limited in the embodiment of the present invention.
The at least two users may be predetermined target users or predetermined target area users, for example, target users or target area users that satisfy a predetermined condition may be obtained in advance according to a set condition.
And S120, clustering according to the daily electric quantity and the daily electric quantity mutation rate, and classifying the users.
The mode of clustering the daily electricity consumption and the daily electricity quantity mutation rate can be K-Means clustering by using the daily electricity consumption and the daily electricity quantity mutation rate of a historical period of time.
Specifically, the daily electricity consumption and the daily electricity consumption mutation rate within the preset time of at least two users are periodically obtained, for example, the daily electricity consumption and the daily electricity consumption mutation rate within a period of historical time are used for performing K-Means clustering, so that user classification is realized. Firstly, performing K-Means cluster analysis by utilizing daily electricity consumption to obtain a small electricity consumption user with low electricity consumption level and a non-small electricity consumption user with high electricity consumption level; and then, performing K-Means clustering on the daily electricity quantity mutation rate of the non-small electricity quantity users to obtain normal electricity quantity users with normal daily electricity quantity mutation rate, sudden increase electricity quantity users with large daily electricity quantity mutation rate and sudden decrease electricity quantity users with small daily electricity quantity mutation rate.
And S130, monitoring the residence information of the user in the preset time according to the classification result.
Wherein the classification result may include: the users are divided into normal electricity quantity users with normal daily electricity quantity mutation rate, sudden increase electricity quantity users with large daily electricity quantity mutation rate and sudden decrease electricity quantity users with small daily electricity quantity mutation rate.
Wherein the occupancy information may include: at least one of a person at home, no person at home, a person out during holidays returning to home, a person out during holidays not returning, a constant number of persons, an increased number of persons, and a decreased number of persons.
Specifically, the residence information of the user within the preset time is monitored according to the classification result, for example, the classification result may be that the user is classified into a normal electricity user with a normal daily electricity mutation rate, a sudden increase electricity user with a large daily electricity mutation rate, and a sudden decrease electricity user with a small daily electricity mutation rate, and whether people in the house, nobody in the house, and people out of the house return to the house is determined according to the classification result.
Optionally, clustering according to the daily electricity consumption and the daily electricity consumption mutation rate, and classifying the users includes:
if the daily electricity consumption of the user in the preset time is smaller than or equal to a first threshold value, determining that the user is a low-electricity-quantity user;
if the daily electric quantity of the user is larger than a first threshold value within preset time, the daily electric quantity mutation rate is larger than or equal to a second threshold value and smaller than or equal to a third threshold value, determining that the user is a normal electric quantity user;
if the daily electric quantity of the user is larger than a first threshold value within the preset time and the daily electric quantity mutation rate is larger than a third threshold value, determining that the user is a sudden increase electric quantity user;
if the daily electric quantity of the user is larger than a first threshold value within the preset time and the daily electric quantity mutation rate is smaller than a second threshold value, determining that the user is a sudden power reduction user;
the first threshold value is a daily electric quantity reference value, the second threshold value is a daily electric quantity mutation rate lower limit value, and the third threshold value is a daily electric quantity mutation rate upper limit value.
The preset time may be a historical period of time, for example, one month, or may be set according to needs, which is not limited in this embodiment of the present invention.
Specifically, the user is in a low power utilization level or is not powered in the statistical period, namely, the daily power monitoring value k is not more than s in the statistical period, and the user is the low power user. And in the statistical period, the daily power monitoring value k of the user is more than s, and the daily power mutation rate r is not less than x and not more than t, so that the user is the normal power. And the daily electric quantity monitoring value k of the user is more than s in the statistical period, and the daily electric quantity mutation rate x is more than t, so that the user with the sudden increase of the electric quantity is obtained. And the daily power monitoring value k of the user in the statistical period is greater than s, and the daily power mutation rate x is less than r, so that the user can reduce the power suddenly. Wherein k is daily electric quantity, x is daily electric quantity mutation rate, s is daily electric quantity reference value, t is daily electric quantity mutation rate upper limit value, and r is daily electric quantity mutation rate lower limit value.
Optionally, the monitoring of the residence information of the user within the preset time according to the classification result includes:
if the daily electricity consumption of the monitored normal electricity consumption user on the current day is larger than a first threshold value, monitoring that the average daily electricity consumption of the previous period of the current day is larger than the first threshold value, and the daily electricity consumption mutation rate is larger than or equal to a second threshold value and smaller than or equal to a third threshold value, determining that people are at home and the number of people at home is unchanged;
if the daily electricity quantity of the user monitoring the sudden electricity quantity increase on the current day is larger than a first threshold value, the average daily electricity quantity of the user monitoring the previous period of the current day is larger than the first threshold value, and the daily electricity quantity mutation rate is larger than a third threshold value, it is determined that people are in the house and the number of people in the house is increased;
and if the average daily electric quantity of the previous period of the sudden power reduction user monitoring current day is larger than a first threshold value, and the daily electric quantity mutation rate is smaller than a second threshold value, determining that the family is occupied, and reducing the number of the family members.
Optionally, the monitoring of the residence information of the user within the preset time according to the classification result includes:
extracting at least one low-power user;
and if the daily electricity consumption of the user with small electricity consumption extracted on the current day is monitored to be smaller than or equal to the first threshold value, and the average daily electricity consumption in the previous period is smaller than or equal to the first threshold value, determining that no person is at home.
Optionally, the monitoring of the residence information of the user within the preset time according to the classification result includes:
counting a power consumption curve during holidays;
if the power consumption curve during the holiday period is in a first preset shape, the average daily power consumption of the previous period of the period in which the holiday period is located is larger than a first threshold, the average daily power consumption in the preset time before the holiday period is larger than the first threshold, and the average value of the power consumption during the holiday period is smaller than or equal to the first threshold, determining that the person going out during the holiday period returns to home;
and if the holiday electricity consumption curve is in a second preset shape, the average daily electricity consumption of the previous period of the holiday period is larger than a first threshold, the average daily electricity consumption in the preset time before the holiday period is smaller than or equal to the first threshold, and the average value of the electricity consumption in the holiday period is smaller than or equal to the first threshold, determining that the person who goes out does not return in the holiday period.
Wherein the holiday can be a legal holiday.
The first preset shape may be a V-shape, and the second preset shape may be an L-shape. The first threshold is a daily electric quantity reference value.
In a specific example, in the embodiment of the present invention, an electric energy indicating value of a user is acquired based on an electric energy meter, and assuming that k is a monitoring value of the daily electricity consumption data of a residential user, a daily electricity consumption mutation rate x of the user is defined as follows:
wherein k is0Average daily charge for the user over the past month.
And performing K-Means clustering by using the daily electricity consumption K and the daily electricity mutation rate x of a historical period of time to realize user classification. Firstly, carrying out K-Means cluster analysis by utilizing daily electricity K to obtain a small electricity user with low electricity consumption level and a non-small electricity user with high electricity consumption level; and then, carrying out K-Means clustering on the daily electric quantity mutation rate x of the non-small electric quantity users to obtain normal electric quantity users with normal daily electric quantity mutation rate, sudden increase electric quantity users with large daily electric quantity mutation rate and sudden decrease electric quantity users with small daily electric quantity mutation rate. Therefore, the electric energy meter is used for collecting the electric energy indication value of the user, so that the user can be divided into four types of users, namely a small electric quantity user, a normal electric quantity user, a sudden increase electric quantity user and a sudden decrease electric quantity user. At this time, the average daily electricity consumption value of the low electricity consumption user is a daily electricity consumption reference value s, and the minimum daily electricity consumption mutation rate value of the sudden increase electricity consumption user and the maximum daily electricity consumption mutation rate value of the sudden decrease electricity consumption user are a daily electricity consumption mutation rate upper limit value t and a daily electricity consumption mutation rate lower limit value r.
1. Defining a low battery user based on a threshold rule: the power utilization characteristics are represented as that the user is in a lower power utilization level or is not powered in the statistical period, namely the daily power monitoring value k in the statistical period is less than or equal to s.
2. Defining normal electricity quantity users based on threshold rules: and in the statistical period, the daily power monitoring value k of the user is more than s, and the daily power mutation rate r is less than or equal to x and less than or equal to t.
3. Defining burst power users based on threshold rules: and the daily electric quantity monitoring value k of the user is more than s in the statistical period, and the daily electric quantity mutation rate x is more than t.
4. Defining a sudden power reduction user based on a threshold rule: and the daily power monitoring value k of the user in the statistical period is larger than s, and the daily power mutation rate x is smaller than r.
Defining the daily electricity consumption data of the residential user as a monitoring value, and recording the monitoring value as k; the average daily electric quantity of the user in one month in history is an upper-period monitoring value, and the upper-period monitoring value is recorded as k0(ii) a Defining the daily electricity quantity mutation rate of the user as a mutation value, and recording the mutation value as x; defining the average daily electricity consumption in the spring festival as a holiday value, and recording the holiday value as k1(ii) a Defining the current 3 balance average electricity consumption monitored by the resident user as a reference value, and recording the reference value as k2. The daily electric quantity reference value is s, and the daily electric quantity mutation rate upper limit value and the daily electric quantity mutation rate lower limit value are an upper limit value t and a lower limit value r respectively. According to the user classification result, monitoring and troubleshooting of the personnel condition change of the resident users are carried out under the condition that the resident users do not enter the house, and the monitoring and troubleshooting are divided into the following four monitoring scenes.
1. Nobody at home
The part of the electricity consumption during the user statisticsIf the quantity is small and the user is a low-power user, the monitoring value k and the previous monitoring value k0Are all less than or equal to the daily electricity reference value s. The scenes do not need to be checked, and the users with small electric quantity can be appropriately spot-checked according to the urban and rural area conditions of various provinces. Algorithm rules are as follows: k is less than or equal to s and k0≤s。
2. Someone in home
For the users at home, the network-based investigation can be carried out in a targeted manner, and the distribution condition of the people in the area is mainly known; the method can be subdivided into three cases according to the supporting application scene and purpose.
(1) The number of the persons is not changed
If the electricity consumption is quite stable during the statistics of the partial users, and the users are normal electricity users, the monitoring value k and the previous monitoring value k0Are all larger than the daily electric quantity reference value s, and the mutation value r is not less than x and not more than t. Algorithm rules are as follows: k > s, k0Is more than s and r is more than or equal to x and less than or equal to t.
(2) Increase in the number of persons
The electricity consumption is greatly increased during the counting period of the part of users, and if the users are users with sudden increase of electricity, the monitoring value k and the previous monitoring value k0Are all larger than the daily electric quantity reference value s, and the mutation value x is larger than t. The scenes need to be mainly checked and analyzed; meanwhile, the monitoring value is focused on changing, and if the monitoring value falls back or approaches to the reference value, the fact that the user has a visit or leaves a vacation staff is indicated. Algorithm rules are as follows: k > s, k0S and x > t.
(3) Reduction of the number of persons
The electricity consumption is greatly reduced during the counting period of the part of users, and if the users are users with suddenly reduced electricity, the monitoring value k is up to the previous period0Is larger than the daily electric quantity reference value s, and the mutation value x is smaller than r; such users need to focus on troubleshooting and analysts are moving. Algorithm rules are as follows: k is a radical of0S and x < r.
3. The out-going person returns to home during spring festival
During the statistical period of the part of users, the power consumption curve is similar to a V shape, a person in the house before the spring festival and a person returning to the house recently exist, and no person in the house during the spring festival, the previous monitoring value k is obtained0And a reference value k2Are all greater than s, and the holiday value k1Less than or equal to s; such users need to be intensively checked, and the return date of the users is determined based on the change situation of the power consumption. Algorithm rules are as follows: k is a radical of0＞s、k2Is > s and k1≤s。
4. The out-going person does not return during the spring festival
The electricity consumption curve of the part of users during the statistics period is similar to an L shape, people are at home before the spring festival, and people do not return during the spring festival, and the previous monitoring value k is0Greater than s, and a holiday value of k1And a reference value k2Are all less than or equal to s; such users need to incorporate a monitoring list to monitor the future return date of the user based on changes in electricity usage. Algorithm rules are as follows: k is a radical of0＞s、k2Is less than or equal to s and k1≤s。
The specific algorithm rules are shown in table 2;
TABLE 2
According to the technical scheme of the embodiment, daily electric quantity and daily electric quantity mutation rate within preset time of at least two users are periodically obtained; clustering according to the daily electric quantity and the daily electric quantity mutation rate, and classifying the users; and monitoring the residence information of the user within the preset time according to the classification result so as to solve the problems of large workload, long period and poor effect in the monitoring in the prior art.
Example two
Fig. 2 is a schematic structural diagram of a residence information monitoring device according to a second embodiment of the present invention. The present embodiment can be applied to the situation of occupancy information monitoring, and the apparatus can be implemented in a software and/or hardware manner, and the apparatus can be integrated into any device providing occupancy information monitoring function, as shown in fig. 3, where the occupancy information monitoring apparatus specifically includes: an acquisition module 210, a clustering module 220, and a monitoring module 230.
The obtaining module 210 is configured to periodically obtain daily electricity consumption and a daily electricity consumption mutation rate within at least two user preset times;
the clustering module 220 is used for clustering according to the daily electricity consumption and the daily electricity consumption mutation rate, and classifying the users;
and a monitoring module 230, configured to monitor the living information of the user within a preset time according to the classification result.
Optionally, the clustering module is specifically configured to:
if the daily electricity consumption of the user in the preset time is smaller than or equal to a first threshold value, determining that the user is a low-electricity-quantity user;
if the daily electric quantity of the user is larger than a first threshold value within preset time, the daily electric quantity mutation rate is larger than or equal to a second threshold value and smaller than or equal to a third threshold value, determining that the user is a normal electric quantity user;
if the daily electric quantity of the user is larger than a first threshold value within the preset time and the daily electric quantity mutation rate is larger than a second threshold value, determining that the user is a sudden increase electric quantity user;
if the daily electric quantity of the user is larger than a first threshold value within the preset time and the daily electric quantity mutation rate is smaller than a second threshold value, determining that the user is a sudden power reduction user;
the first threshold value is the average value of daily electricity consumption of the users with small electricity consumption, and the second threshold value is smaller than or equal to the third threshold value.
Optionally, the monitoring module is specifically configured to:
if the daily electricity consumption of the monitored normal electricity consumption user on the current day is larger than a first threshold value, monitoring that the average daily electricity consumption of the previous period of the current day is larger than the first threshold value, and the daily electricity consumption mutation rate is larger than or equal to a second threshold value and smaller than or equal to a third threshold value, determining that people are at home and the number of people at home is unchanged;
if the daily electricity quantity of the user monitoring the sudden electricity quantity increase on the current day is larger than a first threshold value, the average daily electricity quantity of the user monitoring the previous period of the current day is larger than the first threshold value, and the daily electricity quantity mutation rate is larger than a third threshold value, it is determined that people are in the house and the number of people in the house is increased;
and if the average daily electric quantity of the previous period of the sudden power reduction user monitoring current day is larger than a first threshold value, and the daily electric quantity mutation rate is smaller than a second threshold value, determining that the family is occupied, and reducing the number of the family members.
The product can execute the method provided by any embodiment of the invention, and has corresponding functional modules and beneficial effects of the execution method.
According to the technical scheme of the embodiment, daily electric quantity and daily electric quantity mutation rate within preset time of at least two users are periodically obtained; clustering according to the daily electric quantity and the daily electric quantity mutation rate, and classifying the users; and monitoring the residence information of the user within the preset time according to the classification result so as to solve the problems of large workload, long period and poor effect in the monitoring in the prior art.
EXAMPLE III
Fig. 3 is a schematic structural diagram of a computer device in a third embodiment of the present invention. FIG. 3 illustrates a block diagram of an exemplary computer device 12 suitable for use in implementing embodiments of the present invention. The computer device 12 shown in FIG. 3 is only an example and should not impose any limitation on the scope of use or functionality of embodiments of the present invention.
As shown in FIG. 3, computer device 12 is in the form of a general purpose computing device. The components of computer device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that couples various system components including the system memory 28 and the processing unit 16.
The system memory 28 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM)30 and/or cache memory 32. Computer device 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 3, and commonly referred to as a "hard drive"). Although not shown in FIG. 3, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 by one or more data media interfaces. Memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention.
A program/utility 40 having a set (at least one) of program modules 42 may be stored, for example, in memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. Program modules 42 generally carry out the functions and/or methodologies of the described embodiments of the invention.
The processing unit 16 executes various functional applications and data processing by executing programs stored in the system memory 28, for example, implementing the occupancy information monitoring method provided by the embodiment of the present invention:
periodically acquiring daily electricity and daily electricity mutation rates within preset time of at least two users;
clustering according to the daily electric quantity and the daily electric quantity mutation rate, and classifying the users;
and monitoring the residence information of the user within the preset time according to the classification result.
Example four
A fourth embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the occupancy information monitoring method provided in all the inventive embodiments of the present application: periodically acquiring daily electricity and daily electricity mutation rates within preset time of at least two users;
clustering according to the daily electric quantity and the daily electric quantity mutation rate, and classifying the users;
and monitoring the residence information of the user within the preset time according to the classification result.
Any combination of one or more computer-readable media may be employed. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (10)
1. A method for monitoring occupancy information, comprising:
periodically acquiring daily electricity and daily electricity mutation rates within preset time of at least two users;
clustering according to the daily electric quantity and the daily electric quantity mutation rate, and classifying the users;
and monitoring the residence information of the user within the preset time according to the classification result.
2. The method of claim 1, wherein clustering according to the daily charge and the daily charge mutation rate, and classifying the users comprises:
if the daily electricity consumption of the user in the preset time is smaller than or equal to a first threshold value, determining that the user is a low-electricity-quantity user;
if the daily electric quantity of the user is larger than a first threshold value within preset time, the daily electric quantity mutation rate is larger than or equal to a second threshold value and smaller than or equal to a third threshold value, determining that the user is a normal electric quantity user;
if the daily electric quantity of the user is larger than a first threshold value within the preset time and the daily electric quantity mutation rate is larger than a third threshold value, determining that the user is a sudden increase electric quantity user;
if the daily electric quantity of the user is larger than a first threshold value within the preset time and the daily electric quantity mutation rate is smaller than a second threshold value, determining that the user is a sudden power reduction user;
the first threshold value is a daily electric quantity reference value, the second threshold value is a daily electric quantity mutation rate lower limit value, and the third threshold value is a daily electric quantity mutation rate upper limit value.
3. The method of claim 2, wherein monitoring the occupancy information of the user for a preset time according to the classification result comprises:
if the daily electricity consumption of the monitored normal electricity consumption user on the current day is larger than a first threshold value, monitoring that the average daily electricity consumption of the previous period of the current day is larger than the first threshold value, and the daily electricity consumption mutation rate is larger than or equal to a second threshold value and smaller than or equal to a third threshold value, determining that people are at home and the number of people at home is unchanged;
if the daily electricity quantity of the user monitoring the sudden electricity quantity increase on the current day is larger than a first threshold value, the average daily electricity quantity of the user monitoring the previous period of the current day is larger than the first threshold value, and the daily electricity quantity mutation rate is larger than a third threshold value, it is determined that people are in the house and the number of people in the house is increased;
and if the average daily electric quantity of the previous period of the sudden power reduction user monitoring current day is larger than a first threshold value, and the daily electric quantity mutation rate is smaller than a second threshold value, determining that the family is occupied, and reducing the number of the family members.
4. The method of claim 2, wherein monitoring the occupancy information of the user for a preset time according to the classification result comprises:
extracting at least one low-power user;
and if the daily electricity consumption of the user with small electricity consumption extracted on the current day is monitored to be smaller than or equal to the first threshold value, and the average daily electricity consumption in the previous period is smaller than or equal to the first threshold value, determining that no person is at home.
5. The method of claim 2, wherein monitoring the occupancy information of the user for a preset time according to the classification result comprises:
counting a power consumption curve during holidays;
if the power consumption curve during the holiday period is in a first preset shape, the average daily power consumption of the previous period of the period in which the holiday period is located is larger than a first threshold, the average daily power consumption in the preset time before the holiday period is larger than the first threshold, and the average value of the power consumption during the holiday period is smaller than or equal to the first threshold, determining that the person going out during the holiday period returns to home;
and if the holiday electricity consumption curve is in a second preset shape, the average daily electricity consumption of the previous period of the holiday period is larger than a first threshold, the average daily electricity consumption in the preset time before the holiday period is smaller than or equal to the first threshold, and the average value of the electricity consumption in the holiday period is smaller than or equal to the first threshold, determining that the person who goes out does not return in the holiday period.
6. A occupancy information monitoring apparatus, comprising:
the acquisition module is used for periodically acquiring daily electric quantity and daily electric quantity mutation rate within preset time of at least two users;
the clustering module is used for clustering according to the daily electric quantity and the daily electric quantity mutation rate and classifying the users;
and the monitoring module is used for monitoring the living information of the user within the preset time according to the classification result.
7. The apparatus of claim 6, wherein the clustering module is specifically configured to:
if the daily electricity consumption of the user in the preset time is smaller than or equal to a first threshold value, determining that the user is a low-electricity-quantity user;
if the daily electric quantity of the user is larger than a first threshold value within preset time, the daily electric quantity mutation rate is larger than or equal to a second threshold value and smaller than or equal to a third threshold value, determining that the user is a normal electric quantity user;
if the daily electric quantity of the user is larger than a first threshold value within the preset time and the daily electric quantity mutation rate is larger than a third threshold value, determining that the user is a sudden increase electric quantity user;
if the daily electric quantity of the user is larger than a first threshold value within the preset time and the daily electric quantity mutation rate is smaller than a second threshold value, determining that the user is a sudden power reduction user;
the first threshold value is a daily electric quantity reference value, the second threshold value is a daily electric quantity mutation rate lower limit value, and the third threshold value is a daily electric quantity mutation rate upper limit value.
8. The apparatus of claim 7, wherein the monitoring module is specifically configured to:
if the daily electricity consumption of the monitored normal electricity consumption user on the current day is larger than a first threshold value, monitoring that the average daily electricity consumption of the previous period of the current day is larger than the first threshold value, and the daily electricity consumption mutation rate is larger than or equal to a second threshold value and smaller than or equal to a third threshold value, determining that people are at home and the number of people at home is unchanged;
if the daily electricity quantity of the user monitoring the sudden electricity quantity increase on the current day is larger than a first threshold value, the average daily electricity quantity of the user monitoring the previous period of the current day is larger than the first threshold value, and the daily electricity quantity mutation rate is larger than a third threshold value, it is determined that people are in the house and the number of people in the house is increased;
and if the average daily electric quantity of the previous period of the sudden power reduction user monitoring current day is larger than a first threshold value, and the daily electric quantity mutation rate is smaller than a second threshold value, determining that the family is occupied, and reducing the number of the family members.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method according to any of claims 1-5 when executing the program.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1-5.
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