CN115174606A - Fluid volume time change mode data coding method - Google Patents
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- H—ELECTRICITY
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Abstract
The invention discloses a method for encoding fluid quantity time change mode data, which comprises the following steps: in a time section, a sensor is used for a user end to obtain a fluid volume data of a resource; a first processor calculates a bit of metadata of the time section according to a compression multiple comparison table and the fluid volume data; the first processor transmits the bit data to a second processor of a supply end through a first transceiver and a second transceiver; and the second processor restores the bit data into the fluid volume data of the time zone according to the compression multiple comparison table. Therefore, a large amount of data does not need to be transmitted between the user side and the supply side, the correctness and the stability of data communication of the Internet of things are improved, and meanwhile, the power loss of the transceiver is greatly reduced, which is very important for the user side equipment powered by the battery.
Description
Technical Field
The present invention relates to a method for encoding a fluid amount, and more particularly to a method for encoding data in which the fluid amount changes with time.
Background
The water supply network hydraulic model is a necessary tool for optimizing scheduling and reducing water leakage loss of a water service company, and the water consumption time change mode of the user side is basic data for constructing the hydraulic model.
The water consumption changes of the users in different time periods are manually taken every day to build a hydraulic model, which is obviously impractical. And with the automatic meter reading mode of the internet of things, if water consumption data is returned every 30 minutes, the power consumption of the water meter of the internet of things powered by the battery is difficult to load. An example of an automatic meter reading method of the internet of things is an intelligent reading device for a water meter and a control method thereof provided by taiwan patent publication No. I710752, which mainly uses an image capturing element to capture a value display area of the water meter to obtain a water level image, and then analyzes the water level value from the water level image.
In the aforementioned patent, it is conceivable to transmit a water meter value, even a large power loss of a water level image, every 30 minutes.
Disclosure of Invention
Therefore, the present invention provides a method for encoding time-varying water volume data to solve the above-mentioned problems by recording the peak-to-peak water consumption by bits, so that the water meter can upload the water consumption data of the current day by only one communication in one day, thereby greatly reducing the power consumption.
The fluid volume time change mode data coding method comprises the following steps: in a time section, a sensor is used for a user terminal to obtain a fluid volume data of a resource; a first processor of the user side obtains a compression multiple comparison table, a bit length and the fluid volume data, wherein the compression multiple comparison table corresponds to a compression multiple by different time sections; the first processor calculates a bit of metadata of the time section according to the compression multiple comparison table and the fluid volume data, and the length of the bit of data is the bit length; the first processor transmits the bit data to a first transceiver of the user side, and the first transceiver transmits the bit data to a supply end of the data; after receiving the bit data, a second transceiver of the supply end transmits the bit data to a second processor of the supply end; and the second processor restores the bit data into the fluid volume data of the time zone according to the compression multiple comparison table.
Further, the bit length is not greater than one byte, and the first transceiver transmits the bit data to the second transceiver in Narrow-Band Internet of Things (NB-IoT) technology.
Further, a time period comprises a plurality of time segments, and the compression factor lookup table corresponds to the compression factor in different time segments in the time period; every time the time period passes, the first processor transmits the bit data corresponding to all the time sections to the second processor through the first transceiver and the second transceiver.
Further, the second processor transmits an indication bit data to the first processor of the user side through the second transceiver and the first transceiver, and the first processor changes a total number of bytes and/or an interval time corresponding to the time period according to the indication bit data; every time the interval time passes, the first processor calculates the bit data according to the compression multiple comparison table and the fluid volume data.
Further, the second processor transmits an indication bit data to the first processor of the user terminal through the second transceiver and the first transceiver, the first processor changes the compression multiple comparison table and/or a bit length comparison table according to the indication bit data, and the bit length comparison table corresponds to the bit length in different time sections.
Further, the second transceiver transmits the indication bit data to the first transceiver by narrowband internet of things technology.
Furthermore, the time period has a peak time and an off-peak time, and the bit length corresponding to the time segment at the peak time is not less than the bit length corresponding to the time segment at the off-peak time.
Further, the sensor obtains the fluid amount data from a water meter or a gas meter, and the supply end corresponds to a water company or a natural gas company.
Wherein, this sensor is one of following: light sensor, magnetic reed pipe, electromagnetic wave sensor, image sensor and electronic water meter.
Furthermore, the second processor of the supply end draws a fluid volume time change trend graph corresponding to the user end according to the plurality of fluid volume data and the corresponding time section.
According to the technical characteristics, the following effects can be achieved:
1. the user end converts the fluid volume data into bit data and transmits the bit data to the supply end, and the supply end converts the bit data back into the fluid volume data.
2. By uploading all the bit data of one day to the supply terminal, the power consumption of the first transceiver for multiple on-line registrations is greatly saved, which is very important for the battery-powered client device.
3. The length of the bit and the length of the indicating bit data are controlled in one byte, so that the method can be better applied to the narrow-frequency Internet of things, and the accuracy and stability of data transmission are ensured.
4. The second processor provides the time variation trend of the water consumption of the user terminal, and the supply terminal grasps the peak and off-peak water consumption habits of the user terminal according to the trend, so as to adjust the water supply plan of the water treatment plant and meet the water demand.
5. According to the user's peak and off-peak water usage habits, the supply end dynamically adjusts the total number of bytes and the bit length by issuing the indication bit data, so as to accurately record the user's water usage change with the most appropriate interval time and compression factor.
6. The water supply mode of a user is mastered in real time by using a narrow-frequency Internet of things communication technology, and the dynamic simulation of a water supply network of a hydraulic model is specifically realized.
Drawings
FIG. 1 is a schematic diagram of an embodiment of the present invention.
Fig. 2 is a first flowchart illustrating a method for encoding fluid volume time variation pattern data according to an embodiment of the present invention.
FIG. 3 is a functional block diagram of an embodiment of the present invention, illustrating the conversion of fluid volume data and bit data.
FIG. 4 is a second flowchart illustrating the second processor transmitting bit indicating data according to the embodiment of the present invention.
Description of the symbols:
1 user terminal
11: sensor
12 first processor
13 first transceiver
2 supply end
21 second processor
22 second transceiver
3: water meter
Fluid volume data
B compression multiple comparison table
C bit length comparison table
D is bit data
E indicating bit data
NB-IoT is a narrow-frequency Internet of things.
Detailed Description
In combination with the above technical features, the main efficacy of the fluid volume time variation pattern data encoding method of the present invention will be clearly demonstrated in the following embodiments.
Referring to fig. 1 to 3, a method for encoding fluid quantity time variation pattern data according to an embodiment of the present invention is disclosed, and preferably, the method is applied to water consumption data, and the method for encoding fluid quantity time variation pattern data includes the following steps:
a first processor 12 of a user terminal 1 first obtains a compression factor lookup table B and a bit length lookup table C, wherein the compression factor lookup table B corresponds to a compression factor in different time segments of a time period, and the bit length lookup table C corresponds to a bit length in different time segments of the time period, and the first processor 12 obtains the compression factor and the bit length of each time segment of the time period, for example, one day.
The first processor 12 obtains an interval time, i.e. the length of the time segment, according to the total number of bytes corresponding to the time period and the bit length. More specifically, assuming that the time period is one day, the total number of bytes is 24 bytes, and the bit length is 4 bits in the time period, the quotient of the total number of bytes divided by the bit length is the number of time segments, i.e., 48; the time interval, i.e. 0.5 hour, can be calculated from the time period and the number of the time segments. Every time the interval elapses, the first processor 12 converts a fluid volume data a of a resource acquired by the sensor 11 in the time zone at the user terminal 1 into a bit of metadata D and transmits the bit of metadata D to a supply terminal 2 of the data, and the length of the bit of metadata D is the bit length.
In the preferred embodiment of the present invention, the bit length is not greater than one byte, and every time period passes, the first processor 12 further transmits the bit data D corresponding to all the time segments to a second processor 21 of the providing end 2 via a first transceiver 13 of the user end 1 and a second transceiver 22 of the providing end 2, for example, the bit data D corresponding to the time segments are transmitted once a day and a whole day.
The byte count, the compression factor comparison table B and the bit length comparison table C may be stored in a memory or a cloud space, etc., and the first processor 12 and the second processor 21 obtain the byte count, the compression factor comparison table B and the bit length comparison table C from the memory or the cloud space directly or via the first transceiver 13 and the second transceiver 22, but the memory and the cloud space are not shown in the present disclosure.
The data is water, the supply end 2 of the data corresponds to a water company, and the sensor 11 obtains the fluid volume data a from a water meter 3. The sensor 11 is one of the following: optical sensor, magnetic reed, electromagnetic wave sensor and image sensor, and the sensor 11 may be an electronic water meter. In actual practice, the data may be natural gas, and the supply end 2 corresponds to a natural gas company in response to the fluid amount data a being obtained from a gas meter. When the data is water, the fluid amount data a may be water consumption; when the data is natural gas, the fluid amount data a may be a natural gas usage amount, but is not limited thereto in actual practice. The power for the sensor 11, the first processor 12 and the first transceiver 13 may come from a battery or a socket, etc., but the battery and the socket are not shown in the drawings of the present invention.
The following describes in more detail how the first processor 12 converts the fluid volume data a into the bit data D, and the first processor 12 transmits the bit data D to the supply end 2:
after the first processor 12 obtains the compression factor lookup table B, the corresponding compression factor is obtained according to the time segment, the first processor 12 divides the fluid volume data a by the compression factor to obtain the bit data D, and the length of the bit data D is the same as the bit length corresponding to the time segment in the bit length lookup table C.
The first processor 12 transmits the bit data D to the first transceiver 13 of the ue 1, and the first transceiver 13 transmits the bit data D to the providing end 2 of the data by using Narrow-Band Internet of Things NB-IoT (Narrow-Band Internet of Things) technology.
After receiving the bit data D, a second transceiver 22 of the providing end 2 transmits the bit data D to the second processor 21 of the providing end 2. The second processor 21 multiplies the bit data D by the compression factor according to the compression factor comparison table B to restore the fluid volume data a corresponding to the time segment.
The second processor 21 can also plot the fluid volume data a in the time period, even in a whole cycle or a whole month, and the time section into a fluid volume time variation trend graph corresponding to the user terminal 1, so as to facilitate the providing terminal 2 to master the fluid volume data a in a period of time of the user terminal 1, and further evaluate whether to change the total number of bytes, the compression factor, the bit length, and so on.
Referring to fig. 3 and fig. 4, if the second processor 21 of the providing end 2 considers that the total number of bytes, the compression factor (or the compression factor look-up table B), the bit length (or the bit length look-up table C), and the interval time need to be changed according to the time resolution requirement or the fluid volume resolution requirement, the second processor 21 can also control the first processor 12 of the user end 1 to change by transmitting the indication bit data E to the first processor 12 of the user end 1 through the second transceiver 22 and the first transceiver 13 by using an indication bit data E of the same string. In practical implementation, the second transceiver 22 can also transmit the indication bit data E to the first transceiver 13 by the narrow-band internet of things NB-IoT technology.
For example: in one example, the bit length is 4 bits, and the total number of bytes is 24 bytes; in the second example, the interval time is increased to exchange for a larger length of the bit, such as 8 bits, without increasing the total number of bytes in the first example; in an example three, the total number of bytes is increased to exchange for a larger length of the bits, such as 8 bits, without increasing the interval time of the example one.
The first example is: taking the direct user of a 20 mm one-caliber water meter as an example, the minimum unit cell sensed by the one-caliber water meter is 1 liter. The total number of bytes is 24 bytes, the bit length is 4 bits, and the time interval is 30 minutes. Assuming that the water consumption (i.e., the fluid amount data a at 1 point 30 min) received at 1 point 30 min is 6 liters, and the water consumption (i.e., the fluid amount data a at 18 point 0 min) received at 18 point 0 min is 54 liters; according to the following table one, the compression factor of the former is 1, and the compression factor of the latter is 4; the fluid volume data a is divided by the compression factor, and the quotient is converted into the binary bit data D, so that the former bit data D is 0110, and the latter bit data D is 1101. After receiving the bit data D, the supply end 2 reduces the bit data D to the water consumption of the time zone according to the corresponding compression factor. Accordingly, the water consumption from 1 point 0 to 1 point 30 is 6 liters, and the water consumption from 17 points 30 to 18 points 0 is 52+3 liters; the latter adds 3 liters to the water consumption, reflecting the maximum truncation error after the supply 2 decompresses the water consumption.
Table one, compression factor comparison table (excerpt) of example one:
| time zone | Multiple of compression |
| 01:01-01:30 | 1 |
| 17:31-18:00 | 4 |
Example two: taking the direct water user of the 20 mm caliber water meter as an example, the minimum sensing unit of the caliber water meter is 1 liter. The total number of bytes is 24 bytes, the bit length is 8 bits, and the interval time is 60 minutes. Assuming that the water consumption (i.e., the fluid amount data a at 2 point and 0 point) received at 2 point and 0 time is 15 liters, and the water consumption (i.e., the fluid amount data a at 9 point and 0 time) received at 9 point and 0 time is 100 liters; according to the following table two, the compression factor of both is 1; the former bit data D is 00001111, and the latter bit data D is 01100100. After receiving the bit data D, the supply end 2 reduces the bit data D to the water consumption of the time zone according to the corresponding compression factor. Accordingly, the water consumption of 1 point 01 to 2 points 0 is 15 liters, and the water consumption of 8 points 01 to 9 points 0 is 100 liters; since the compression factor is 1, although there is no truncation error after decompression, the interval time of the second example is 60 minutes, which reduces the time resolution of water consumption analysis compared to the first example.
Table two, compression factor comparison table (excerpt) for example two:
| time zone | Multiple of compression |
| 01:01-02:00 | 1 |
| 08:01-09:00 | 1 |
The third example: taking the direct water user of the 20 mm caliber water meter as an example, the minimum sensing unit of the caliber water meter is 1 liter. The total number of bytes is 48 bytes, the bit length is 8 bits, and the interval time is 30 minutes. Assuming that the water consumption (i.e., the fluid amount data a at 1 point and 30 minutes) received at 1 point and 30 minutes is 6 liters, and the water consumption (i.e., the fluid amount data a at 7 points and 30 minutes) received at 7 points and 30 minutes is 72 liters; according to the third table, the compression times of the two are both 1; the former bit data D is 00000110, and the latter bit data D is 01001000. After receiving the bit data D, the supply end 2 reduces the bit data D to the water consumption of the time zone according to the corresponding compression factor. Accordingly, the water consumption from 1 point 01 to 1 point 30 is 6 liters, and the water consumption from 7 points 01 to 7 points 30 is 72 liters; here, since the compression factor is 1, although there is no truncation error after decompression, the bit length of the example three is 8 bits, which greatly increases the data amount of narrowband communication compared to the example one.
Table three, compression factor comparison table for example three (excerpt):
| time zone | Multiple of compression |
| 01:01-01:30 | 1 |
| 07:01-07:30 | 1 |
In the first to third examples, the bit length is constant in the time period regardless of whether the time segment is located at a peak time or an off-peak time in the time period. If the bit length can be flexibly adjusted according to the water consumption, it will be better to achieve the data correctness and reduce the data amount than the second and third examples. The following is described in detail by way of an example four:
the example four: taking the direct water user of the 20 mm caliber water meter as an example, the minimum sensing unit of the caliber water meter is 1 liter. The total number of bytes is 32 bytes, which can accommodate 16 segments of the bit data D with the bit length of 8 bits and 32 segments of the bit data D with the bit length of 4 bits, so that the interval time is 30 minutes. Assuming that the water consumption (i.e., the fluid amount data a at 1 point and 30 minutes) received at 1 point and 30 minutes is 6 liters, and the water consumption (i.e., the fluid amount data a at 7 points and 30 minutes) received at 7 points and 30 minutes is 72 liters; according to the fourth table, the compression factor of both is 1; according to the fifth table, the bit length of the former is 4 bits, and the bit length of the latter is 8 bits; the former bit data D is 0110, and the latter bit data D is 01001000. After receiving the bit data D, the supply end 2 reduces the bit data D to the water consumption of the time zone according to the corresponding compression factor. Accordingly, the water consumption from 1 point 01 to 1 point 30 is 6 liters, and the water consumption from 7 points 01 to 7 points 30 is 72 liters.
Here, because the compression multiple is 1, there is no truncation error after decompression, meanwhile, because the water consumption of 30 minutes at 1 point in the morning is small, belonging to the off-peak time, the bit length only needs to be configured with 4 bits; the 7 o 'clock and 30 o' clock uses more water, which is the peak time, and the bit length is increased to 8 bits. It can be found that the bit length corresponding to the time segment at the peak time is not less than the bit length corresponding to the time segment at the off-peak time. Therefore, not only the truncation error after decompression is avoided, but also the unnecessary bit length can be reduced, and the data volume of narrow-band communication is reduced.
Table four, compression factor comparison table (excerpt) for example four:
| time zone | Multiple of compression |
| 01:01-01:30 | 1 |
| 07:01-07:30 | 1 |
Table five, bit length comparison table (excerpt) for example four:
| time zone | Bit length |
| 01:01-01:30 | 4 |
| 07:01-07:30 | 8 |
As can be understood from the above illustration, if the peak time and the off-peak time are learned and the total number of bytes, the compression factor and the bit length are appropriately adjusted, a 24-hour water usage pattern can be recorded with the least bit length. For the fourth example, assuming that 07. For narrow-band communication, the smaller the packet size, the more stable the data transmission can be ensured, and this example four can indeed achieve more stable transmission.
By the method for encoding the time-varying pattern data of the fluid amount, the water service company can know the water consumption pattern of the user in the water supply area, taking the case that the supply end 2 is the water service company as an example. By combining the water consumption mode of the user and the water supply pressure of the water plant, a water supply network hydraulic model can be constructed, and the water service company can further search for the optimal water supply pressure, thereby not only reducing the power loss of the pressurizing motor, but also reducing the water leakage loss.
Water usage patterns analysis is such as a user water leakage monitor. The user will not continue to use water for 24 hours, for example, deep at night or no one is at home, and the water consumption should be zero. If the water consumption mode is maintained above a certain water consumption for 24 hours, the water consumption may be the water leakage of the user.
The water usage pattern analysis may assist in home care for the user. Based on the characteristic that the water usage pattern indirectly reflects living of the user, if the water usage pattern is suddenly changed, it is possible that the living of the user is abnormal. For example, an elderly living alone may accidentally fall if the water usage pattern for getting up and going to toilet in the late night is suddenly terminated. The water company can change the impression of the carved board which can only read the meter and charge, and the image of the relatives and people who are served by the user is improved.
In summary, the method for encoding the fluid volume time variation pattern data is based on the characteristic that the peak and off-peak water consumption of users are extremely asymmetric, and records unit cells by using bits as the water consumption, and endows the compression times with the peak water consumption exceeding the length of the bits, thereby achieving the purpose that the peak and off-peak water consumption can be recorded by using the bit data D. When the supply end 2 receives the bit data D, the water consumption of the time section is reduced according to the compression multiple of different time sections. Because this bit data D record that each time zone water consumption can both be with the most retrenching, as long as the thing networking communication of once can upload the high in the clouds with all time zone water consumption of one day, not only reduce power consumption by a wide margin, more because the dynamic compression technique of water consumption data, promote the success rate that thing networking data uploaded by a wide margin.
While the operation, use and operation of the present invention as disclosed herein may be fully understood, the present invention is not limited to the details of the foregoing description, since various modifications and changes may be made without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (10)
1. A method for encoding fluid volume time variation pattern data, comprising:
in a time section, a sensor is used for a user end to obtain a fluid volume data of a resource;
a first processor of the user side obtains a compression multiple comparison table, a bit length and the fluid volume data, wherein the compression multiple comparison table corresponds to a compression multiple by different time sections;
the first processor calculates a bit of metadata of the time section according to the compression multiple comparison table and the fluid volume data, and the length of the bit of data is the bit length;
the first processor transmits the bit data to a first transceiver of the user end, and the first transceiver transmits the bit data to a supply end of the data;
after receiving the bit data, a second transceiver of the supply end transmits the bit data to a second processor of the supply end; and
the second processor restores the bit data to the fluid volume data of the time zone according to the compression ratio look-up table.
2. The method as claimed in claim 1, wherein the bit length is not greater than one byte, and the first transceiver transmits the bit data to the second transceiver using narrowband internet of things.
3. The method of claim 1, further comprising a time period including a plurality of time segments, wherein the compression factor lookup table corresponds to the compression factor in different time segments of the time period; and after the time period passes, the first processor transmits the bit data corresponding to all the time sections to the second processor through the first transceiver and the second transceiver.
4. The method as claimed in claim 3, wherein the second processor transmits an indication bit data to the first processor of the user end via the second transceiver and the first transceiver, and the first processor changes a byte count and/or an interval time corresponding to the time period according to the indication bit data; every time the interval time passes, the first processor calculates the bit data according to the compression multiple comparison table and the fluid volume data.
5. The method as claimed in claim 3, wherein the second processor transmits an indication bit data to the first processor of the user end via the second transceiver and the first transceiver, the first processor changes the compression factor lookup table and/or a bit length lookup table according to the indication bit data, the bit length lookup table corresponds to the bit length in different time segments.
6. The method as claimed in claim 4 or 5, wherein the second transceiver transmits the indication bit data to the first transceiver by narrowband internet of things.
7. The method as claimed in claim 5, wherein the time period has a peak time and an off-peak time, and the bit length corresponding to the time segment at the peak time is not less than the bit length corresponding to the time segment at the off-peak time.
8. The method as claimed in claim 1, wherein the sensor obtains the data of the fluid amount from a water meter or a gas meter, and the supply end corresponds to a water company or a gas company.
9. The method of claim 1, wherein the sensor is one of: light sensor, magnetic reed pipe, electromagnetic wave sensor, image sensor and electronic water meter.
10. The method as claimed in claim 1, wherein the second processor of the supply end draws a fluid volume time trend graph corresponding to the user end according to a plurality of fluid volume data and the corresponding time segment.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101894153A (en) * | 2010-06-29 | 2010-11-24 | 武汉绿色网络信息服务有限责任公司 | Annular storage list-based dynamic data compressing and storing method |
| CN109374051A (en) * | 2018-11-06 | 2019-02-22 | 北京京航计算通讯研究所 | Naval port bank warship water feeding tank system based on Internet of Things |
| CN109425402A (en) * | 2017-08-24 | 2019-03-05 | 台湾优化水务股份有限公司 | Intelligent flowmeter |
| CN110031055A (en) * | 2019-04-03 | 2019-07-19 | 苏州德晟能源科技有限公司 | A kind of meter reader and the Meter Monitor System equipped with the reader |
| US20200372320A1 (en) * | 2019-05-24 | 2020-11-26 | Neuchips Corporation | Computing system and compressing method for neural network parameters |
-
2021
- 2021-03-18 CN CN202110292433.9A patent/CN115174606A/en not_active Withdrawn
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101894153A (en) * | 2010-06-29 | 2010-11-24 | 武汉绿色网络信息服务有限责任公司 | Annular storage list-based dynamic data compressing and storing method |
| CN109425402A (en) * | 2017-08-24 | 2019-03-05 | 台湾优化水务股份有限公司 | Intelligent flowmeter |
| CN109374051A (en) * | 2018-11-06 | 2019-02-22 | 北京京航计算通讯研究所 | Naval port bank warship water feeding tank system based on Internet of Things |
| CN110031055A (en) * | 2019-04-03 | 2019-07-19 | 苏州德晟能源科技有限公司 | A kind of meter reader and the Meter Monitor System equipped with the reader |
| US20200372320A1 (en) * | 2019-05-24 | 2020-11-26 | Neuchips Corporation | Computing system and compressing method for neural network parameters |
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