CN114037113B - Intelligent water meter control method, device and system, storage medium and cloud computing center - Google Patents
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Abstract
An intelligent water meter control method and device, a cloud computing center, a system and a storage medium. The intelligent water meter control method comprises the following steps: reporting local water consumption related information to a cloud computing center; receiving a control model which is issued by the cloud computing center and is obtained based on the training of the water consumption related information; and executing local control according to the control model. According to the scheme provided by the embodiment, data acquisition and water consumption control are performed at the intelligent water meter end, so that fault response is more timely, and the dependence on a network is lower.
Description
Technical Field
The present disclosure relates to intelligent water meter technologies, and in particular, to a method, an apparatus and a system for controlling an intelligent water meter, a storage medium, and a cloud computing center.
Background
The intelligent water meter is a resident water consumption metering and water supply on-off terminal used according to the resident water fee collecting condition, and the intelligent water meter mainly comprises an IC card intelligent water meter and a remote transmission intelligent water meter in the market at present. Intelligent water meters typically control the water supply according to instructions on the system side.
Disclosure of Invention
The embodiment of the application provides a control method, a device and a system of an intelligent water meter, a storage medium and a cloud computing center, and the dependence of the intelligent water meter on the system is reduced.
The embodiment of the application provides a control method of an intelligent water meter, which comprises the following steps:
reporting local water consumption related information to a cloud computing center;
receiving a control model which is issued by the cloud computing center and is obtained based on the training of the water consumption related information;
and executing local control according to the local water use related information and the control model.
In an exemplary embodiment, the control model includes a plurality of scenarios and corresponding response operations;
the performing local control according to the local water usage related information and the control model includes: and determining the current scene according to the local water consumption related information, and executing response operation corresponding to the scene.
In an exemplary embodiment, the responding operation includes at least one of: controlling the valve state of the intelligent water meter; alarming and reporting related data; and changing the mode of reporting the local water consumption related information.
In an exemplary embodiment, the water usage related information includes: and when reporting, the water characteristic data is directly acquired from the intelligent water meter, and the characteristic data is calculated according to the edge obtained by processing the water information in the period between the last reporting and the current reporting.
In an exemplary embodiment, the edge calculation feature data includes: data on abnormal water usage behavior.
The embodiment of the disclosure provides an intelligent water meter control device, which comprises a memory and a processor, wherein the memory stores a program, and the program realizes the control method of the intelligent water meter in any embodiment when being read and executed by the processor.
The disclosed embodiments provide a computer readable storage medium storing one or more programs executable by one or more processors to implement the method for controlling a smart water meter according to any of the above embodiments.
The embodiment of the disclosure provides an intelligent water meter control method, which comprises the following steps:
the cloud computing center receives water consumption related information reported by the intelligent water meter;
the cloud computing center trains according to the water use related information to obtain a control model;
and the cloud computing center issues the control model to the intelligent water meter.
In an exemplary embodiment, the water usage related information includes: and the characteristic data obtained by calculating the water consumption information in the time period between the last report and the current report is based on the water consumption characteristic data directly collected from the intelligent water meter during the report.
The embodiment of the disclosure provides a cloud computing center, which comprises a memory and a processor, wherein the memory stores a program, and the program realizes the control method of the intelligent water meter in any embodiment when being read and executed by the processor.
The embodiment of the disclosure provides an intelligent water meter control system, which comprises the intelligent water meter control device and a cloud computing center.
Compared with the related art, the embodiment of the application comprises a control method, a device and a system of an intelligent water meter, a storage medium and a cloud computing center, wherein the control method of the intelligent water meter comprises the following steps: reporting local water consumption related information to a cloud computing center; receiving a control model which is issued by the cloud computing center and is obtained based on the training of the water consumption related information; and executing local control according to the local water use related information and the control model. According to the scheme provided by the embodiment, data acquisition and water consumption control are performed at the intelligent water meter end, so that fault response is more timely, and the dependence on a network is lower.
Additional features and advantages of the application will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the application. Other advantages of the present application may be realized and attained by the structure particularly pointed out in the written description and drawings.
Drawings
The accompanying drawings are included to provide an understanding of the technical aspects of the present application, and are incorporated in and constitute a part of this specification, illustrate the technical aspects of the present application and together with the examples of the present application, and not constitute a limitation of the technical aspects of the present application.
Fig. 1 is a schematic diagram of an intelligent water meter control system according to an embodiment of the disclosure;
fig. 2 is a flowchart of a control method of an intelligent water meter according to an embodiment of the disclosure;
FIG. 3 is a schematic diagram of control model parameters provided by an exemplary embodiment;
FIG. 4 is a schematic diagram of response operation of the cloud computing platform provided in an exemplary embodiment in different scenarios;
fig. 5 is a schematic diagram of an intelligent water meter control device according to an embodiment of the disclosure;
fig. 6 is a flowchart of a control method of an intelligent water meter according to an embodiment of the disclosure.
Detailed Description
The present application describes a number of embodiments, but the description is illustrative and not limiting and it will be apparent to those of ordinary skill in the art that many more embodiments and implementations are possible within the scope of the embodiments described herein. Although many possible combinations of features are shown in the drawings and discussed in the detailed description, many other combinations of the disclosed features are possible. Any feature or element of any embodiment may be used in combination with or in place of any other feature or element of any other embodiment unless specifically limited.
The present application includes and contemplates combinations of features and elements known to those of ordinary skill in the art. The embodiments, features and elements of the present disclosure may also be combined with any conventional features or elements to form a unique inventive arrangement as defined in the claims. Any feature or element of any embodiment may also be combined with features or elements from other inventive arrangements to form another unique inventive arrangement as defined in the claims. Thus, it should be understood that any of the features shown and/or discussed in this application may be implemented alone or in any suitable combination. Accordingly, the embodiments are not to be restricted except in light of the attached claims and their equivalents. Further, various modifications and changes may be made within the scope of the appended claims.
Furthermore, in describing representative embodiments, the specification may have presented the method and/or process as a particular sequence of steps. However, to the extent that the method or process does not rely on the particular order of steps set forth herein, the method or process should not be limited to the particular sequence of steps described. Other sequences of steps are possible as will be appreciated by those of ordinary skill in the art. Accordingly, the particular order of the steps set forth in the specification should not be construed as limitations on the claims. Furthermore, the claims directed to the method and/or process should not be limited to the performance of their steps in the order written, and one skilled in the art can readily appreciate that the sequences may be varied and still remain within the spirit and scope of the embodiments of the present application.
Fig. 1 is a schematic diagram of an intelligent water meter control system according to an embodiment of the disclosure. As shown in fig. 1, an intelligent water meter control system provided in an embodiment of the present disclosure includes: a cloud computing center and at least one intelligent water meter. The intelligent water meter may be an internet of things water meter, and the cloud computing center and the intelligent water meter may be interconnected by a narrowband internet of things (Narrow Band Internet of Things, NB-IoT). Embodiments of the present disclosure are not limited thereto and the cloud computing center and the intelligent water meter may be connected by other wired or wireless connection means.
The cloud computing center is configured to receive water use related information reported by the intelligent water meter; training according to the water consumption related information to obtain a control model, and issuing the control model to the intelligent water meter.
The intelligent water meter is configured to report relevant information of local water use to the cloud computing center; receiving a control model which is issued by the cloud computing center and is obtained based on the training of the water consumption related information; and executing local control according to the local water use related information and the control model.
In an exemplary embodiment, the intelligent water meter may report the water related information periodically, or report when a preset report condition is met, or the like.
In an exemplary embodiment, the training control model according to the water usage related information may be a regression model training control model. Embodiments of the present disclosure are not limited thereto.
In an exemplary embodiment, a natural village (rural scene) or a residential community (urban scene) may be taken as a DMA partition (District Metering Area, i.e. an independent metering area), the cloud computing center may count and analyze the water consumption related information of all intelligent water meters in the DMA partition received in a period, the cloud computing center may generate a corresponding control model through big data analysis and training according to different water consumption scenes, send the control model to the intelligent water meters, and optimize the control model according to the reported local water consumption related information, for example, may train the control model through a regression model in machine learning and optimize parameters.
In an exemplary embodiment, the cloud computing center analyzes the reported water usage related information through the cloud strong storage and computing power to form a DMA partition water usage analysis result, including but not limited to at least one of the following: the method comprises the steps of regional water consumption comparison and trend analysis, regional pipe network leakage analysis, regional water consumption safety management analysis, user behavior analysis and the like, abnormal users in the regional can be analyzed and early warned according to analysis results, and emergency response treatment is carried out through various interaction means. Besides the emergency response processing according to the analysis result, the intelligent water meter can also receive the alarm information of the intelligent water meter and then perform the emergency response processing.
In an exemplary embodiment, the cloud computing platform emergency response means may include, but is not limited to, according to different scenarios: the system notification (for running alarm and daily maintenance of the equipment) sent to the intelligent water meter, the micro-message/short message notification (for arrearing, stopping water/opening up, etc. user service, namely, notifying user water through the micro-message/short message) is reported to the relevant departments (for alarming of user characteristic analysis, such as occurrence of abnormal excessive water consumption/occurrence of long-time 0 water consumption of old people/occurrence of abnormal water consumption of farmers, etc.), so that the relevant departments take corresponding countermeasures, such as checking old people with long-time 0 water consumption, checking farmers, etc.
Fig. 2 is a flowchart of a control method of an intelligent water meter according to an embodiment of the disclosure. As shown in fig. 2, an embodiment of the present disclosure provides a control method of an intelligent water meter, including:
and 203, executing water use control operation according to the local water use related information and the control model.
According to the scheme provided by the embodiment, data acquisition and water consumption control are performed at the intelligent water meter end, so that fault response is more timely, and the dependence on a network is lower. In the related scheme, the intelligent water meter is controlled
In an exemplary embodiment, the water usage related information may include: and when reporting, the water characteristic data is directly acquired from the intelligent water meter, and the characteristic data is calculated according to the edge obtained by processing the water information in the period between the last reporting and the current reporting. In the related technical scheme, besides reporting the current water consumption, the water consumption process data of the two reporting times can be reported, the data volume is larger, the power consumption is larger, and according to the scheme provided by the embodiment, the data is stored and calculated at the intelligent water meter end, the intelligent water meter does not need to report the process data (only the edge calculation characteristic data after reporting the processing) between the two reporting times, the number of messages interacted with the cloud calculation center is reduced, the communication time of the intelligent water meter and the cloud calculation center is reduced, and the power consumed by the calculation of the intelligent water meter is much smaller than the power consumed by the message to the cloud calculation center, so that the power consumption of the intelligent water meter can be effectively reduced.
In an exemplary embodiment, the water usage characteristic data may include: user information and water consumption; may further comprise at least one of: valve state, battery voltage, etc.
In an exemplary embodiment, the edge calculation feature data may include: data on abnormal water usage behavior. The edge calculation feature data may also include fault information or the like. The data at the time of water use behavior abnormality may include, for example, water use peak data at the time of water use behavior abnormality, an abnormality period, and the like. Embodiments of the present disclosure are not limited thereto and may include other data.
In an exemplary embodiment, the control model may include a variety of scenarios and corresponding responsive operations;
the performing local control according to the local water usage related information and the control model includes: and determining the current scene according to the local water consumption related information, and executing response operation corresponding to the scene.
In an exemplary embodiment, the determining the current scene from the local water usage related information includes: and determining the current scene according to the stored historical water use related information and the water use related information acquired in real time.
In an exemplary implementation, various control models may be generated based on water usage, water usage behavior, water user characteristics, and the like.
Taking the user characteristic analysis as an example, the method can be divided into ordinary household users or farmers, wherein the ordinary household users can be divided into resident and non-resident types, or the ordinary household users can be divided into families or only the old, so that different control models are matched for different classifications. Taking the old people type as an example, the water consumption rule is characterized by average small quantity, and the control model can be used for finding the water consumption condition of 0 over 24 hours and 48 hours. This is merely an example, and may be categorized according to other ways. Such as sorting by the number of family members of the user, etc.
Taking a water consumer water consumption model as an example, an initial control model takes a water supply equipment type (whether a water faucet, sanitary equipment, rain equipment and the like exist or not), a community type (such as villages, town areas and the like), the highest daily water consumption quota and a time-varying coefficient as parameters, and the last two parameters are range values. Along with the repeated training and optimization of the control model through the machine learning regression model, the range value can be determined more accurately, so that the analysis and the prediction can be performed more accurately. The time-varying coefficient refers to the ratio of the maximum water usage amount per hour to the average water usage amount per hour in the day of the maximum water usage amount (average water usage amount per hour in the day of the maximum water usage amount). FIG. 3 is a schematic diagram of parameters of a control model provided in an exemplary embodiment. The parameters here are just examples, with a time-varying coefficient of 5.0 to 3.2 for the timed feed. The cloud computing center can issue different control models to the intelligent water meter according to community types of users where the intelligent water meter is located and types of water supply equipment.
In an exemplary embodiment, the responding operation includes at least one of: controlling the valve state of the intelligent water meter; alarming and reporting related data; and changing the mode of reporting the local water consumption related information.
The valve state of the intelligent water meter comprises: the valve is closed. The alarm includes: and alarming the cloud computing platform, for example, alarming the cloud computing platform that the water consumption is abnormal, and then responding according to the alarm information by the cloud computing platform, for example, reporting to a related management department, and the like, for example, alarming the cloud computing platform that arrears occur, the cloud computing platform can inform a user to pay fees, and the notification mode can be short messages, weChat, and the like. For example, taking an abnormal water use scene as an example, the intelligent water meter finds that the water use data of the current day is larger than the historical data in comparison (can be judged according to a control model), and besides the conventionally reported data, the water use of the current day is packaged and reported according to the hour-by-hour extremum information as alarm information. The mode of reporting the local water consumption related information by the change comprises the following steps: reporting a change from once a day to once an hour, etc.
FIG. 4 is a schematic diagram of response operation of the cloud computing platform provided by an exemplary implementation in different scenarios. As shown in fig. 4, different response operations are performed for different users. And the user who pays in time with normal water consumption can be informed of paying when the user is defaulting, and water supply is kept. When the user with abnormal water consumption and long-time arrears, the water is stopped to remind the user to pay in time when the arrears occur.
In fig. 4, after the water is stopped in the second case (i.e. the historical water consumption is normal and there is an arrearage record exceeding 7 days), by setting a half-hour reporting mechanism, the communication period between the intelligent water meter and the cloud computing center in the arrearage state is shortened, so that the intelligent water meter can be in a normal working state in time after the user finishes paying, and the water consumption experience of the user is ensured. And in the third case (namely, the historical water consumption is abnormal and has arrearage records for more than 7 days), after the water is stopped, the communication period between the intelligent water meter and the cloud computing center is maintained in the arrearage state, so that the user can experience the inconvenience of stopping the water, and the user can be reminded of paying in time in the later period. The above-described response operation is merely an example, and other response operations may be set as needed. The embodiments of the present disclosure are not limited in this regard.
In an exemplary embodiment, an extended communication protocol may be defined to transmit the local water-usage related information, such as the edge calculation feature data.
As shown in fig. 5, an embodiment of the disclosure provides an intelligent water meter control device 40, which includes a memory 410 and a processor 420, where the memory 410 stores a program, and the program implements the control method of the intelligent water meter according to any one of the embodiments when the program is read and executed by the processor 420.
The embodiment of the disclosure provides an intelligent water meter, which comprises the intelligent water meter control device.
Embodiments of the present disclosure provide a computer-readable storage medium storing one or more programs executable by one or more processors to implement any of the methods of controlling a smart water meter.
Fig. 6 is a flowchart of a control method of an intelligent water meter according to an embodiment of the disclosure. As shown in fig. 6, an embodiment of the present disclosure provides an intelligent water meter control method, including:
and 603, the cloud computing center issues the control model to the intelligent water meter.
In an exemplary embodiment, the water usage related information includes: and the characteristic data obtained by calculating the water consumption information in the time period between the last report and the current report is based on the water consumption characteristic data directly collected from the intelligent water meter during the report.
The embodiment of the disclosure provides a cloud computing center, which comprises a memory and a processor, wherein the memory stores a program, and the program realizes the control method of the intelligent water meter in the embodiment when being read and executed by the processor. The cloud computing center may include one or more servers.
The embodiment of the disclosure provides an intelligent water meter control system, which comprises the intelligent water meter control device and a cloud computing center.
The embodiment of the disclosure provides an intelligent water meter control system, which comprises the intelligent water meter and a cloud computing center.
Those of ordinary skill in the art will appreciate that all or some of the steps, systems, functional modules/units in the apparatus, and methods disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. In a hardware implementation, the division between the functional modules/units mentioned in the above description does not necessarily correspond to the division of physical components; for example, one physical component may have multiple functions, or one function or step may be performed cooperatively by several physical components. Some or all of the components may be implemented as software executed by a processor, such as a digital signal processor or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term computer storage media includes both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, as known to those skilled in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computer. Furthermore, as is well known to those of ordinary skill in the art, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media.
Claims (10)
1. The control method of the intelligent water meter is characterized by comprising the following steps:
reporting local water consumption related information to a cloud computing center;
receiving a control model which is issued by the cloud computing center and is obtained based on the training of the water consumption related information;
executing local control according to the local water use related information and the control model;
the control model is generated by a cloud computing center through big data analysis and training according to different water use scenes by counting and analyzing water use related information of all intelligent water meters in an independent metering area DMA partition received in one period;
the control model comprises a plurality of scenes and corresponding response operations, and the local control is executed according to the local water use related information and the control model, and comprises the following steps: determining a current scene according to the local water consumption related information, and executing response operation corresponding to the scene; the scene comprises an abnormal water use scene, and the response operation comprises alarming the cloud computing platform of water use abnormality;
the control model comprises a water user water consumption model, wherein the water user water consumption model takes a water supply equipment type, a community type, a highest daily water consumption quota and a time-varying coefficient as parameters, and the cloud computing center issues different control models according to the community type of the user where the intelligent water meter is located and the water supply equipment type.
2. The method of claim 1, wherein the responsive operation comprises at least one of: controlling the valve state of the intelligent water meter; alarming and reporting related data; and changing the mode of reporting the local water consumption related information.
3. The control method of an intelligent water meter according to any one of claims 1 or 2, wherein the water-consumption related information includes: and when reporting, the water characteristic data is directly acquired from the intelligent water meter, and the characteristic data is calculated according to the edge obtained by processing the water information in the period between the last reporting and the current reporting.
4. A control method of an intelligent water meter according to claim 3, wherein the edge calculation feature data includes: data on abnormal water usage behavior.
5. An intelligent water meter control device comprising a memory and a processor, wherein the memory stores a program which, when read and executed by the processor, implements the intelligent water meter control method according to any one of claims 1 to 4.
6. A computer-readable storage medium storing one or more programs executable by one or more processors to implement the method of controlling a smart water meter according to any one of claims 1 to 4.
7. An intelligent water meter control method is characterized by comprising the following steps:
the cloud computing center receives water consumption related information reported by the intelligent water meter;
the cloud computing center trains according to the water use related information to obtain a control model;
the cloud computing center issues the control model to the intelligent water meter;
the control model is generated by a cloud computing center through big data analysis and training according to different water use scenes by counting and analyzing water use related information of all intelligent water meters in an independent metering area DMA partition received in one period;
the control model comprises various scenes and corresponding response operations, and the local control is executed according to the local water use related information and the control model, and comprises the following steps: determining a current scene according to the local water consumption related information, and executing response operation corresponding to the scene; the scene comprises an abnormal water use scene, and the response operation comprises alarming the cloud computing platform of water use abnormality;
the control model comprises a water user water consumption model, wherein the water user water consumption model takes a water supply equipment type, a community type, a highest daily water consumption quota and a time-varying coefficient as parameters, and the cloud computing center issues different control models according to the community type of the user where the intelligent water meter is located and the water supply equipment type.
8. The intelligent water meter control method of claim 7, wherein the water usage related information comprises: and the characteristic data obtained by calculating the water consumption information in the time period between the last report and the current report is based on the water consumption characteristic data directly collected from the intelligent water meter during the report.
9. A cloud computing center comprising a memory and a processor, the memory storing a program which, when read by the processor for execution, implements the intelligent water meter control method of claim 7 or 8.
10. An intelligent water meter control system comprising the intelligent water meter control device of claim 5 and the cloud computing center of claim 9.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202111121512.XA CN114037113B (en) | 2021-09-24 | 2021-09-24 | Intelligent water meter control method, device and system, storage medium and cloud computing center |
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| CN202111121512.XA CN114037113B (en) | 2021-09-24 | 2021-09-24 | Intelligent water meter control method, device and system, storage medium and cloud computing center |
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| CN114037113A CN114037113A (en) | 2022-02-11 |
| CN114037113B true CN114037113B (en) | 2023-07-11 |
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| CN105573164B (en) * | 2015-12-28 | 2018-05-11 | 深圳市金正方科技股份有限公司 | Intellectual water meter and its water-saving method, device |
| CN108243216B (en) * | 2016-12-26 | 2020-02-14 | 华为技术有限公司 | Data processing method, end-side device, cloud-side device and end cloud cooperative system |
| CN109677410B (en) * | 2017-10-18 | 2022-11-25 | 宇通客车股份有限公司 | Vehicle self-adaptive control method and system |
| CN108093030B (en) * | 2017-11-29 | 2022-02-22 | 杭州博联智能科技股份有限公司 | Artificial intelligence model deployment method based on cloud server |
| CN108520342B (en) * | 2018-03-23 | 2021-12-17 | 中建三局第一建设工程有限责任公司 | BIM-based Internet of things platform management method and system |
| CN111478832B (en) * | 2020-03-26 | 2022-04-19 | 深圳市汇合云网络科技有限责任公司 | Control method, linkage method, auxiliary method and device of intelligent terminal equipment |
| CN111580449A (en) * | 2020-06-10 | 2020-08-25 | 国网（天津）综合能源服务有限公司 | Energy management control system based on narrow-band Internet of things technology |
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| CN113176758B (en) * | 2021-04-26 | 2022-06-21 | 天津晨天自动化设备工程有限公司 | Data acquisition, monitoring, early warning and maintenance method and system for intelligent water service pipe network |
| CN113341813B (en) * | 2021-06-11 | 2022-11-01 | 上海天麦能源科技有限公司 | Urban gas medium-low pressure pipe network detection method and system |
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| CN110148066A (en) * | 2019-05-23 | 2019-08-20 | 珠海华裕鑫科技有限公司 | A kind of intellectual water meter management system and method |
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