CN107608325B - Water treatment prediction method and server - Google Patents
Water treatment prediction method and server Download PDFInfo
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- CN107608325B CN107608325B CN201710915854.6A CN201710915854A CN107608325B CN 107608325 B CN107608325 B CN 107608325B CN 201710915854 A CN201710915854 A CN 201710915854A CN 107608325 B CN107608325 B CN 107608325B
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Abstract
The embodiment of the invention discloses a water treatment prediction method and a server. Wherein, the water treatment prediction method can comprise the following steps: acquiring a history water consumption record; determining target time, and determining target water use data according to the historical water use record, wherein the target water use data is predicted water use data corresponding to the target time; and after generating a control instruction according to the target time and the target water use data, outputting the control instruction. By implementing the embodiment of the invention, the life rule of the user can be intelligently adapted, and the efficiency is improved.
Description
Technical Field
The invention relates to the technical field of smart home, in particular to a water treatment prediction method and a server.
Background
With the development of science and technology, intelligent devices become more and more intelligent, and users also start to use the intelligent devices more and more, such as water treatment intelligent device water heaters, water purifiers and the like.
In actual life, the water of the user has a unique rhythm, and when the user uses the water treatment intelligent device, the water treatment intelligent device can be used in the following way, namely, the water treatment intelligent device is manually turned on or turned off; the other type is that the water treatment intelligent equipment is controlled through the terminal APP, so that the water treatment intelligent equipment is automatically started or closed according to preset time.
However, by adopting the technical scheme, the life rule of the user cannot be effectively and intelligently adapted, and the efficiency is low.
Disclosure of Invention
The technical problem to be solved by the embodiments of the present invention is to provide a water treatment prediction method and a server, which can intelligently adapt to the life law of a user and improve efficiency.
In a first aspect, an embodiment of the present invention provides a water treatment prediction method, including:
acquiring a history water consumption record;
determining target time, and determining target water use data according to the historical water use record, wherein the target water use data is predicted water use data corresponding to the target time;
and after generating a control instruction according to the target time and the target water use data, outputting the control instruction.
In an optional implementation manner, before determining the target time, the method further includes:
acquiring a prediction period and current time;
the determining the target time includes:
and determining the target time according to the current time and the prediction period.
In an optional implementation manner, before determining the target water usage data according to the historical water usage record, the method further includes:
detecting whether the target time is preset time or not, wherein the preset time is time corresponding to holidays;
the determining target water use data according to the historical water use record comprises:
and if the target time is the preset time, determining the target water consumption data according to the historical water consumption record corresponding to the preset time.
In an optional implementation manner, before determining the target time and determining the target water usage data according to the historical water usage record, the method further includes:
constructing a matrix containing a target code, wherein the target code is a code corresponding to the historical water record;
inputting the matrix containing the target code into a full-link neural network model;
determining a target matrix through the full-link neural network model, wherein the target matrix is a matrix corresponding to the target time and the target water consumption data;
the determining the target time and the determining the target water usage data according to the historical water usage record comprise:
and determining the target time according to the target matrix, and determining the target water consumption data according to the target matrix.
In an alternative implementation, the target encoding includes: the water consumption monitoring system comprises a code corresponding to a first time, a code corresponding to a second time, a code corresponding to the first time and a code corresponding to the second time.
In an optional implementation manner, the outputting the control instruction includes:
sending the control instruction to target equipment, wherein the control instruction is used for instructing the target equipment to perform water treatment according to the control instruction;
or sending the control instruction to a terminal, wherein the control instruction is used for instructing the terminal to control target equipment to perform water treatment according to the control instruction.
In a second aspect, an embodiment of the present invention provides a server, including:
the acquisition unit is used for acquiring a historical water record;
the determining unit is used for determining target time and determining target water use data according to the historical water use record, wherein the target water use data is predicted water use data corresponding to the target time;
the generating unit is used for generating a control instruction according to the target time and the target water use data;
and the output unit is used for outputting the control instruction.
In an optional implementation manner, the obtaining unit is further configured to obtain a prediction period and a current time;
the determining unit is specifically configured to determine the target time according to the current time and the prediction period.
In an optional implementation manner, the server further includes:
the detection unit is used for detecting whether the target time is preset time, and the preset time is time corresponding to holidays;
the determining unit is specifically configured to determine the target water usage data according to a historical water usage record corresponding to the predetermined time if the target time is the predetermined time.
In an optional implementation manner, the server further includes:
the construction unit is used for constructing a matrix containing target codes, and the target codes are codes corresponding to the historical water records;
the input unit is used for inputting the matrix containing the target code into a full-link neural network model;
the determining unit is further configured to determine a target matrix through the full-link neural network model, where the target matrix is a matrix corresponding to the target time and the target water usage data;
the determining unit is specifically configured to determine the target time according to the target matrix, and determine the target water usage data according to the target matrix.
In an alternative implementation, the target encoding includes: the water consumption monitoring system comprises a code corresponding to a first time, a code corresponding to a second time, a code corresponding to the first time and a code corresponding to the second time.
In an optional implementation manner, the output unit is specifically configured to send the control instruction to a target device, where the control instruction is used to instruct the target device to perform water treatment according to the control instruction;
or the output unit is specifically configured to send the control instruction to a terminal, where the control instruction is used to instruct the terminal to control a target device to perform water treatment according to the control instruction.
In a third aspect, an embodiment of the present invention further provides a server, including: a processor, an input device, an output device and a memory, the processor, the input device, the output device and the memory being interconnected, wherein the memory is configured to store a computer program that enables a server to perform the above method, the computer program comprising program instructions, the processor being configured to invoke the program instructions to perform the method of the first aspect.
In a fourth aspect, the present invention provides a computer-readable storage medium storing a computer program, the computer program comprising program instructions that, when executed by a processor, cause the processor to perform the method of the first aspect.
By implementing the embodiment of the invention, the server determines the target time and the target water consumption data through the historical user records, so that the water consumption time and the water consumption data of the user are predicted; after the control instruction is generated, the control instruction is output, and the corresponding equipment is controlled to treat water through the control instruction, so that convenience is brought to users to use water, the life law of the users is adapted more intelligently, and the water use efficiency of the users is improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments or the background art of the present invention, the drawings required to be used in the embodiments or the background art of the present invention will be described below.
FIG. 1 is a diagram of a network architecture of a water treatment prediction system according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a water treatment prediction system according to an embodiment of the present invention;
FIG. 3 is a schematic flow chart of a water treatment prediction method according to an embodiment of the present invention;
FIG. 4 is a schematic flow chart of another water treatment prediction method provided by an embodiment of the invention;
FIG. 5 is a schematic flow chart of another water treatment prediction method provided by an embodiment of the present invention;
FIG. 6 is a schematic structural diagram of an input code according to an embodiment of the present invention;
fig. 7 is a schematic structural diagram of a server according to an embodiment of the present invention;
FIG. 8 is a schematic structural diagram of another server provided in the embodiment of the present invention;
fig. 9 is a schematic structural diagram of another server provided in the embodiment of the present invention;
fig. 10 is a schematic structural diagram of another server according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the present invention will be described in further detail with reference to the accompanying drawings, and it is apparent that the described embodiments are only a part of the embodiments of the present invention, 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 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 some, not all, embodiments of the present invention. It should be noted that the detailed description set forth in connection with the appended drawings is intended as a description of various configurations and is not intended to represent the only configurations in which the concepts described herein may be practiced. The apparatus embodiments and method embodiments described herein are described in the following detailed description and illustrated in the accompanying drawings by various blocks, modules, units, components, circuits, steps, processes, algorithms, etc. (collectively referred to as "elements"). These elements may be implemented using electronic hardware, computer software, or any combination thereof. Whether such elements are implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. The terms first, second, etc. in the description and claims of the present invention and in the drawings of the specification, if used in describing various aspects, are used for distinguishing between different objects and not for describing a particular order.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. It is also to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the specification of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should be further understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
It should be noted that, unless otherwise specified, various technical features in the embodiments of the present invention may be regarded as being capable of being combined or coupled with each other as long as the combination or coupling is not technically impossible to implement. While certain exemplary, optional, or preferred features may be described in combination with other features in various embodiments of the invention for a more complete description of the invention, it is not necessary for such combination to be considered, and it is to be understood that the exemplary, optional, or preferred features and the other features may be separable or separable from each other, provided that such separation or separation is not technically impractical. Some functional descriptions of technical features in method embodiments may be understood as performing the function, method, or step, and some functional descriptions of technical features in apparatus embodiments may be understood as performing the function, method, or step using the apparatus.
Referring to fig. 1, fig. 1 is a network architecture diagram of a water treatment prediction system according to an embodiment of the present invention, as shown in fig. 1, the water treatment prediction system includes: a server 101 and a target device 102.
The server 101 and the target device 102 may communicate to enable interaction of data and/or signaling.
Wherein the target device 102 may be a device capable of water treatment, such as a water heater; the embodiment of the invention is not limited, as water purifiers, kettles and other devices are also used. It is to be understood that the target device may also be understood as a water treatment smart device or the like, and in particular implementations, the target device may have other names and therefore should not be construed as limiting the embodiments of the present invention.
The server 101 may store data acquired from the target device, and may also store data uploaded by the target device, and the like. It is to be understood that the server 101 may also be a cloud server, and the like, and the embodiment of the present invention is not limited.
It can be understood that, in the embodiment of the present invention, the server 101 may further perform a communication connection with the terminal, so as to implement interaction of data and/or signaling, for example, the server 101 may send a control instruction to the terminal, so that the terminal controls the target device 102, as shown in fig. 2, where fig. 2 is a specific scenario schematic diagram of a water treatment prediction system provided in the embodiment of the present invention, as shown in fig. 2, the system includes: a server 201, a water purifier 202, and a terminal 203; the server 201 and the terminal 203 are connected through a network to realize interaction of data and/or signaling. The terminal 203 and the water purifier 202 may be communicatively connected, for example, may be connected through bluetooth, or may be connected through Wireless Fidelity (WiFi), and the present embodiment is not limited thereto.
Referring to fig. 3, fig. 3 is a schematic flow chart of a water treatment prediction method according to an embodiment of the present invention, where the water treatment prediction method is applied to a server, as shown in fig. 3, the water treatment prediction method may include the following steps:
301. acquiring a history water consumption record;
in the embodiment of the invention, the server can be directly in communication connection with the target equipment, so that the historical water consumption record stored in the water heater is obtained from the target equipment such as the water heater. Optionally, the terminal may be in communication connection with the target device, so that the terminal acquires the historical water record in the target device; the server is connected with the terminal in a communication mode, so that the server acquires the historical water consumption record from the terminal.
It is understood that the historical water usage record may be a record related to the water usage behavior of the user, such as water usage time and water usage amount. The water consumption may be calculated by a water unit such as ton, or a metering unit in the target device, or may be calculated by water consumption time, or the like, or a calculation method of the water consumption may be set by a user, and the calculation method of the water consumption is not limited in this embodiment. For example, the user water using behavior may be an operation of bathing the water in the water heater by the user.
302. Determining target time, and determining target water use data according to the historical water use record, wherein the target water use data is predicted water use data corresponding to the target time;
in the embodiment of the invention, the server can obtain target water consumption data through big data analysis; the server may also determine target water consumption data and the like through a preset model, which is not limited in this embodiment. It is understood that the pre-set model may be a fully-linked neural network model or the like.
In the embodiment of the present invention, the water consumption data may include a water consumption time, a water consumption amount, and the like, and the specific content of the water consumption data is not limited uniquely in the embodiment of the present invention.
Because the processing capacity of the server is stronger than that of other equipment, the target time and the target water consumption data are determined by the server, and the efficiency and the accuracy of water treatment prediction can be effectively improved.
In this embodiment, the target time may be time corresponding to the next user behavior of the user determined by the server, and optionally, the target time may also be set by the server, or set by the user, and the like, which is not limited in this embodiment.
Optionally, an embodiment of the present invention further provides a method for determining a target time, where before the target time is determined, the method further includes:
acquiring a prediction period and current time;
the determining the target time includes:
and determining the target time according to the current time and the prediction period.
In this embodiment, the prediction period may be a period preset by the server, or may also be a period preset by the user, and the like, and this embodiment is not limited.
If the prediction period is predicted once per day, if the current time is 1/2017, the target time is 1/2/2017, that is, the server may determine a specific time corresponding to the water usage behavior of the user on 1/2/2017 and water usage data corresponding to the specific time. If the target time can be 2017, 1, 2, 08:00, the target water consumption data is corresponding data at the target time.
If the prediction period is predicted once every three days, if the current time is 1/2017, the target time is 1/4/2017, that is, the server may determine the specific time corresponding to the water consumption behavior of the user in 1/4/2017 and the water consumption data corresponding to the time.
In practical application, a user may frequently go on business, and the prediction period is set, so that the life rule of the user can be more met, the life rule of the user can be more flexibly and intelligently adapted, and the satisfaction degree of the user is improved.
303. And generating a control command according to the target time and the target water consumption data, and outputting the control command.
Specifically, the server outputting the control instruction may include the following two ways:
1) sending the control instruction to target equipment, wherein the control instruction is used for instructing the target equipment to perform water treatment according to the control instruction;
2) and sending the control instruction to a terminal, wherein the control instruction is used for instructing the terminal to control target equipment to perform water treatment according to the control instruction.
That is, the server may directly control the target device, or may implement control on the target device through the terminal, and the specific implementation manner is not limited in this embodiment. By sending the control instruction to the target equipment, the target equipment can be controlled to perform water treatment in time, the realization is simple, and the operation of a user is not needed.
By implementing the embodiment, the server determines the target time and the target water consumption data, so that the control instruction is output after the control instruction is generated, the target equipment can perform water treatment according to the control instruction, the target equipment can effectively and intelligently adapt to the life rule of the user, and the efficiency is improved.
Referring to fig. 4, fig. 4 is a schematic flow chart of another water treatment prediction method according to an embodiment of the present invention, where the water treatment prediction method is applicable to a server, as shown in fig. 4, the water treatment prediction method may include the following steps:
401. acquiring a history water consumption record;
402. acquiring a prediction period and current time;
403. determining the target time according to the current time and the prediction period;
404. detecting whether the target time is preset time, and if so, executing 405; otherwise, 406 is executed;
in the embodiment of the invention, the preset time is the time corresponding to the holiday and the festival.
In the embodiment of the present invention, whether the current time is the preset time or not may be detected by the server through the preset time, where the preset time may be determined by the server according to an actual situation, or may be determined by the user, and the like.
405. Determining the target water use data according to the historical water use record corresponding to the preset time;
406. determining target water consumption data according to the historical water consumption record;
the target water consumption data is predicted water consumption data corresponding to the target time;
407. and generating a control command according to the target time and the target water consumption data, and outputting the control command.
The specific implementation manner of the embodiment of the present invention is the same as that of the first embodiment, and is not described herein again.
To better understand the embodiments of the present invention, a specific scenario is taken, for example, a user may be Monday for a holiday, so that a different rhythm occurs than the weekend holiday of the general case; as another example, a legal holiday may be a national uniform rule, and a company/individual may be ahead of time or behind by demand. On the holiday and holiday, the water using behavior of the user is different from the daily working/working time, so that the server can adapt to the life rhythm of the user and judge the holiday mode, thereby being beneficial to improving the use effect of target equipment and meeting the user requirements; on the other hand, better energy-saving and environment-friendly effects are realized, the service life of target equipment is prolonged, and the like.
Referring to fig. 5, fig. 5 is a schematic flow chart of another water treatment prediction method according to an embodiment of the present invention, where the water treatment prediction method is applicable to a server, and as shown in fig. 5, the water treatment prediction method may include:
501. acquiring a history water consumption record;
502. constructing a matrix containing a target code, wherein the target code is a code corresponding to the historical water record;
specifically, the target encoding may include: the water consumption monitoring system comprises a code corresponding to a first time, a code corresponding to a second time, a code corresponding to the first time and a code corresponding to the second time.
In the embodiment of the present invention, the first time and the second time are times corresponding to water using behaviors of the user, and the first time may be the same as or different from the second time.
The target code may include a first time and water usage data corresponding to the first time. Assuming a time of 2017, 7, 17, monday, the water usage data is at 00: 03, using water for 1 minute, the target code can be [ 0207171001000 … ], the first two digits represent year, and for coding convenience and reducing the number of coding bits, the 2015 is subtracted from the year code, namely the 2015 is subtracted from 2017 to obtain 02; the third to sixth digits represent months and days, such as "0717" represents 7 months and 17 days; the seventh bit represents the week, e.g., "1" for Monday; the latter bit represents the water usage condition of each time segment, if the bit corresponding to the target time segment is 1, it represents that there is water usage behavior in the target time segment, if the bit corresponding to the target time segment is 0, it represents that there is no water usage behavior in the target time segment, for example, if the third bit in the latter bit is 1, it represents that there is a ratio of 00: 03, water use behavior is present. The above encoding method is merely an example, and the encoding method is not limited in the embodiment of the present invention.
The historical water records are encoded, so that a matrix is constructed, the historical water records can be converted into an input form which can be accepted by a full-link neural network model, and the implementation is simple.
503. Inputting the matrix containing the target code into a full-link neural network model;
504. determining a target matrix through the full-link neural network model, wherein the target matrix is a matrix corresponding to the target time and the target water consumption data;
505. determining the target time according to the target matrix, and determining the target water use data according to the target matrix, wherein the target water use data is predicted water use data corresponding to the target time;
506. and generating a control command according to the target time and the target water consumption data, and outputting the control command.
In a specific implementation, the objective matrix may include at least one row vector, each row vector representing one predicted water usage data. Each row vector may contain two portions, a first portion indicating a target time for the row vector and a second portion indicating predicted water usage data corresponding to the target time. For example, the first row of the target matrix [ 0207182000000 … ], the first two digits representing the year, can use 02 plus 2015 to obtain 2017, i.e., the row vector corresponds to the year of 2017; the third to sixth digits represent the month and date, such as "0718" for 7 months and 18 days; the seventh bit indicates the week, e.g., "2" for tuesday; the latter bits represent the water consumption condition of each time period, and if the latter bits are all 0, the water consumption behavior does not exist. The water use information corresponding to the row vector [ 0207182000000 … ] is "7/18/2017/tuesday, no water use behavior exists".
It is understood that other variations and names of the fully-linked neural network model may exist in the embodiments of the present invention, and the fully-linked neural network model should not be construed as limiting the present embodiment. For example, the fully-linked neural network model may have other equivalent models, such as a linear matrix model, that is, the matrix including the target code in this embodiment may also be input into the linear matrix model, so as to obtain the target matrix.
Optionally, an embodiment of the present invention further provides a data structure, where the data structure corresponds to the water treatment prediction method provided in the embodiment of the present invention, and is as follows:
before the matrix containing the target code is input into the fully-linked neural network model, the method further includes:
determining water consumption data corresponding to the historical water consumption record;
coding the water consumption data corresponding to the historical water consumption record to obtain an input code;
the inputting the matrix containing the target code into the full-link neural network model includes:
inputting the matrix corresponding to the input code into the full-link neural network model;
the determining the target matrix through the fully-linked neural network model includes:
determining the code corresponding to the target matrix through the full-link neural network model;
the determining the target time according to the target matrix and the determining the target water usage data according to the target matrix include:
and determining the target time according to the code corresponding to the target matrix, and determining the target water consumption data according to the code corresponding to the target matrix.
In this embodiment, the water usage data corresponding to the historical water usage record, such as the determination of the water usage duration, is determined.
Optionally, in this embodiment, a code corresponding to a predetermined time, that is, a code corresponding to a holiday or a festival, may also be added.
The input code may include water usage data corresponding to the current time, the target time, and the historical water usage record. Optionally, it may also include whether the current time is a holiday or not. Assuming that one day corresponds to 1440 time periods, each time period having a duration of 1 minute, 1440 combinations of 0 s and/or 1 s may be used for representation, i.e. the third part of the code may be represented by 1440 combinations of 0 s and/or 1 s. Assuming that the current time is 2017, 7, 17, monday, the water usage data is at 00: 03, using water for 1 minute, wherein the target time determined by the prediction period is 2017, 7, 18, tuesday, the input code can be [ 0207171020718200001000 … ], the first two digits represent the year, and for the convenience of coding and the reduction of the number of coding bits, 2015 is subtracted from the year code, namely, 2015 is subtracted from 2017 to obtain 02; the third to sixth digits represent months and days, such as "0717" represents 7 months and 17 days; the seventh bit represents the week, e.g., "1" for Monday; the eighth to fifteenth bits represent a target time; alternatively, the sixteenth bit may indicate whether it is a holiday, an eighth bit of 1 indicating that the current time is a holiday, and an eighth bit of 0 indicating that the current time is not a holiday; the last 1440 bits indicate the water consumption of each time period, if the bit corresponding to the target time period is 1, it indicates that there is water consumption in the target time period, if the bit corresponding to the target time period is 0, it indicates that there is no water consumption in the target time period, for example, the third bit in the 1440 bits is 1, it indicates that there is a difference between 00: 03, water use behavior is present. The above encoding method is merely an example, and the encoding method is not limited in the embodiment of the present invention.
The target matrix may include at least one row vector, each row vector representing a predicted water usage data. Each row vector may contain two portions, a first portion indicating the time to which the row vector corresponds, i.e., the target time, and a second portion indicating the predicted water usage data corresponding to the target time. For example, the first row of the target matrix [ 02071820000000 … ], the first two digits representing the year, can use 02 plus 2015 to obtain 2017, i.e., the row vector corresponds to the year of 2017; the third to sixth digits represent the month and date, such as "0718" for 7 months and 18 days; the seventh bit indicates the week, e.g., "2" for tuesday; an eighth bit indicates whether the current time is a holiday, an eighth bit of 1 indicates that the current time is a holiday, and an eighth bit of 0 indicates that the current time is not a holiday; the last 1440 bits represent water usage for each time period, and all 1440 bits are 0, indicating that there is no water usage. The water use information corresponding to the row vector [ 02071820000000 … ] is "7/18/2017/Tu20/Tuesday, non-holiday, and no water use behavior".
Optionally, please refer to fig. 6, where fig. 6 is a structure of an input code according to an embodiment of the present invention. As shown in fig. 6, the above structure is a structure of inputting codes, and may include a code corresponding to the current time, a code corresponding to the target time, a reserved code, and a code corresponding to the water consumption data corresponding to the historical water consumption record. The following structure is a coding structure corresponding to the target matrix and can comprise a code corresponding to the target time, a reserved code and a code corresponding to the water consumption data corresponding to the target data. Specifically, the reserved code is used to add a code according to actual needs, for example, the reserved code may be used to indicate whether the day is a holiday, or indicate other information, and the like, and the embodiment is not limited uniquely.
In the embodiment of the invention, the prediction can be accurately realized by expressing the historical water record and the like in a coding mode, and the coding is simple and has high reliability.
The method of embodiments of the present invention is set forth above in detail and the apparatus of embodiments of the present invention is provided below.
Referring to fig. 7, fig. 7 is a schematic structural diagram of a server according to an embodiment of the present invention, and as shown in fig. 7, the server may include:
an acquisition unit 701 for acquiring a history water record;
a determining unit 702, configured to determine a target time and determine target water usage data according to the historical water usage record, where the target water usage data is predicted water usage data corresponding to the target time;
a generating unit 703, configured to generate a control instruction according to the target time and the target water usage data;
an output unit 704, configured to output the control instruction.
By implementing the embodiment of the invention, the server determines the target time and the target water consumption data, so that the control instruction is output after the control instruction is generated, the target equipment can perform water treatment according to the control instruction, the target equipment can effectively and intelligently adapt to the life rule of the user, and the efficiency is improved.
The obtaining unit 701 is further configured to obtain a prediction period and a current time;
the determining unit 702 is specifically configured to determine the target time according to the current time and the prediction period.
By setting the prediction period, the life rule of the user can be better met, the life rule of the user can be more flexibly and intelligently adapted, and the satisfaction degree of the user is improved.
As shown in fig. 8, the server further includes:
a detecting unit 705, configured to detect whether the target time is a predetermined time, where the predetermined time is a time corresponding to a holiday;
the determining unit 702 is specifically configured to determine the target water usage data according to a historical water usage record corresponding to the predetermined time if the target time is the predetermined time.
By implementing the embodiment of the invention, the server can be adaptive to the life rhythm of the user and judge the holiday mode, thereby being beneficial to improving the use effect of the target equipment and meeting the requirements of the user; on the other hand, better energy-saving and environment-friendly effects are realized, the service life of target equipment is prolonged, and the like.
Optionally, the server may further include:
a constructing unit 706, configured to construct a matrix including a target code, where the target code is a code corresponding to the historical water record;
an input unit 707, configured to input the matrix including the target code into a full-link neural network model;
the determining unit 702 is further configured to determine a target matrix through the full-link neural network model, where the target matrix is a matrix corresponding to the target time and the target water usage data;
the determining unit 702 is specifically configured to determine the target time according to the target matrix, and determine the target water usage data according to the target matrix.
Specifically, the target encoding includes: the water consumption monitoring system comprises a code corresponding to a first time, a code corresponding to a second time, a code corresponding to the first time and a code corresponding to the second time.
By implementing the embodiment of the invention, the prediction can be accurately realized by representing the historical water record and the like in a coding form, and the coding is simple and has high reliability.
The output unit 704 is specifically configured to send the control instruction to a target device, where the control instruction is used to instruct the target device to perform water treatment according to the control instruction;
alternatively, the output unit 704 is specifically configured to send the control instruction to a terminal, where the control instruction is used to instruct the terminal to control a target device to perform water treatment according to the control instruction.
By implementing the embodiment of the invention, the target equipment can be controlled to carry out water treatment in time by sending the control instruction to the target equipment, the implementation is simple, and the operation of a user is not required.
Referring to fig. 9, a schematic block diagram of a server according to another embodiment of the present invention is shown. The server in this embodiment as shown in the figure may include: one or more processors 901; one or more input devices 903, one or more output devices 904, and memory 902. The processor 901, the input device 903, the output device 904, and the memory 902 described above are connected by a bus 905.
The processor 901 may be used in any of the above methods of the foregoing embodiments. For example, the processor 901 may be configured to: acquiring a history water consumption record; determining target time, and determining target water use data according to the historical water use record, wherein the target water use data is predicted water use data corresponding to the target time; and generating a control command according to the target time and the target water consumption data, and outputting the control command.
It should be understood that, in the embodiment of the present invention, the Processor 901 may be a Central Processing Unit (CPU), and the Processor may also be other general processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 904 may include both read-only memory and random access memory, and provides instructions and data to the processor 901. A portion of the memory 904 may also include non-volatile random access memory. For example, memory 904 may also store device type information.
In a specific implementation, the processor 901, the input device 902, and the output device 903 described in the embodiment of the present invention may execute the implementation described in any one of the water treatment prediction methods provided in the foregoing embodiments of the present invention, and may also execute the implementation described in the embodiment of the present invention in the server, which is not described herein again.
In another embodiment of the present invention, a computer-readable storage medium is provided, which stores a computer program that when executed by a processor implements: acquiring a history water consumption record; determining target time, and determining target water use data according to the historical water use record, wherein the target water use data is predicted water use data corresponding to the target time; and generating a control command according to the target time and the target water consumption data, and outputting the control command.
The computer readable storage medium may be an internal storage unit of the server according to any of the foregoing embodiments, for example, a hard disk or a memory of the server. The computer readable storage medium may be an external storage device of the server, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like provided in the server. Further, the computer-readable storage medium may include both an internal storage unit and an external storage device of the server. The computer-readable storage medium is used for storing the computer program and other programs and data required by the server. The above-described computer-readable storage medium may also be used to temporarily store data that has been output or is to be output.
Fig. 10 is a schematic diagram of a server structure provided by an embodiment of the present invention, where the server 1000 may have a relatively large difference due to different configurations or performances, and may include one or more Central Processing Units (CPUs) 1022 (e.g., one or more processors) and a memory 1032, one or more storage media 1030 (e.g., one or more mass storage devices) for storing applications 1042 or data 1044. Memory 1032 and storage medium 1030 may be, among other things, transient or persistent storage. The program stored on the storage medium 1030 may include one or more modules (not shown), each of which may include a series of instruction operations for the server. Still further, a central processor 1022 may be disposed in communication with the storage medium 1030, and configured to execute a series of instruction operations in the storage medium 1030 on the server 1000.
The server 1000 may also include one or more power supplies 1026, one or more wired or wireless network interfaces 1050, one or more input-output interfaces 1058, and/or one or more operating systems 1041, such as Windows Server, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM, and so forth.
The steps performed by the server in the above embodiment may be based on the server structure shown in fig. 10.
One of ordinary skill in the art will appreciate that all or part of the processes in the methods of the above embodiments may be implemented by hardware related to instructions of a computer program, which may be stored in a computer-readable storage medium, and when executed, may include the processes of the above method embodiments. And the aforementioned storage medium includes: various media capable of storing program codes, such as ROM or RAM, magnetic or optical disks, etc.
Claims (4)
1. A water treatment prediction method, comprising:
acquiring a history water consumption record;
constructing a matrix containing target codes, wherein the target codes comprise codes corresponding to historical time and codes corresponding to historical water consumption data corresponding to the historical time, the historical time comprises years, months, dates and weeks corresponding to the dates, the codes corresponding to the historical water consumption data corresponding to the historical time are used for indicating whether water consumption behaviors exist in each time period corresponding to the dates, the target codes further comprise codes used for indicating whether the dates are holidays, and the holidays are rest days of the user predicted according to the historical water consumption records;
inputting the matrix containing the target code into a full-link neural network model;
determining a target matrix through the full-link neural network model, wherein the target matrix comprises a code corresponding to target time and a code of predicted water consumption data corresponding to the target time, the code of the predicted water consumption data corresponding to the target time is used for indicating whether water consumption behaviors exist in each time period corresponding to the target time, and the target matrix further comprises a code for indicating whether the target time is a preset time; the preset time is the time corresponding to the holiday;
determining the target time according to the target matrix;
detecting whether the target time is the preset time or not;
if the target time is the preset time, determining the target water consumption data according to the historical water consumption record corresponding to the preset time;
and after generating a control instruction according to the target time and the target water use data, outputting the control instruction.
2. The method of claim 1, wherein the target encoding comprises: the water consumption monitoring system comprises a code corresponding to a first time, a code corresponding to a second time, a code corresponding to the first time and a code corresponding to the second time.
3. The method of claim 1, wherein the outputting the control instruction comprises:
sending the control instruction to target equipment, wherein the control instruction is used for instructing the target equipment to perform water treatment according to the control instruction;
or sending the control instruction to a terminal, wherein the control instruction is used for instructing the terminal to control target equipment to perform water treatment according to the control instruction.
4. A server, comprising:
the acquisition unit is used for acquiring a historical water record;
the construction unit is used for constructing a matrix containing target codes, wherein the target codes comprise codes corresponding to historical time and codes of historical water consumption data corresponding to the historical time, the historical time comprises years, months, dates and weeks corresponding to the dates, the codes of the historical water consumption data corresponding to the historical time are used for indicating whether water consumption behaviors exist in each time period corresponding to the dates, the target codes further comprise codes used for indicating whether the dates are holidays, and the holidays are rest days of the user predicted according to the historical water consumption records;
the input unit is used for inputting the matrix containing the target code into a full-link neural network model;
a determining unit, configured to determine, through the full-link neural network model, a target matrix, where the target matrix includes a code corresponding to a target time and a code of predicted water usage data corresponding to the target time, the target time is a future time determined according to a current time and a prediction period, the code of predicted water usage data corresponding to the target time is used to indicate whether water usage behavior exists in each time period corresponding to the target time, and the target matrix further includes a code used to indicate whether the target time is a predetermined time; the preset time is the time corresponding to the holiday;
the determining unit is specifically configured to determine the target time according to the target matrix;
the detection unit is used for detecting whether the target time is the preset time or not;
the determining unit is specifically configured to determine the target water usage data according to the historical water usage record corresponding to the predetermined time if the target time is the predetermined time;
the generating unit is used for generating a control instruction according to the target time and the target water use data;
and the output unit is used for outputting the control instruction.
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