TWI770870B - Encoding method for processing time-based change data of fluid volume - Google Patents

Abstract

An encoding method for processing time-based change data of fluid volume, including: a sensor retrieving a fluid volume data of a resource from a user end within a time interval; a first processing device calculating a bit-data within the time interval according to a data compression ratio table and the fluid volume data; the first processing device transmitting the bit-data to a second processing device of a supply end through a first transceiver and a second transceiver; and the second processing device restore the bit-data to the fluid volume data within the time interval according to the data compression ratio table. In this way, there is no need to transmit a large amount of data between the user end and the supply end, which not only improves the accuracy and stability of data communication in the Internet of Things, but also greatly reduces the power loss of the transceivers, which is crucial to the battery-powered user end device.

Description

Data Encoding Method for Time Variation Pattern of Fluid Volume

The present invention relates to a coding method of fluid quantity, in particular to a data coding method of fluid quantity varying with time.

The hydraulic model of the water supply network is an essential tool for the water company to optimize scheduling and reduce leakage losses, while the time-varying pattern of water consumption at the user end is the basic data for constructing the hydraulic model.

It is obviously impractical to manually copy the water consumption changes of users in different time periods every day to construct a hydraulic model. In the IoT automatic meter reading method, if a water consumption data is sent back every 30 minutes, the power consumption is such that the battery-powered IoT water meter cannot be loaded. For example, the automatic meter reading method of the Internet of Things is a smart reading device for a water meter and a control method thereof provided by the Patent Publication No. I710752 of the Republic of China. Obtain the water level image, and then analyze the water level value from the water level image.

In the aforementioned patent case, the transmission of a water meter value every 30 minutes, and even a large amount of power consumption of the water level image, can be imagined.

Therefore, in order to solve the above problems, the inventors of the present invention record the peak and off-peak water consumption in bits, so that the water meter can complete the data upload of the water consumption pattern of the day with only one communication in a day, and greatly reduce the power consumption, and proposes a method. A method for encoding fluid volume time-varying pattern data.

The method for encoding fluid volume time change pattern data includes: in a time segment, a sensor obtains a fluid volume data of a resource at a user end; a first processor at the user end obtains a compression ratio comparison table , one-bit length and the fluid volume data, the compression ratio comparison table corresponds to a compression ratio in different time segments; the first processor calculates the time according to the compression ratio comparison table and the fluid volume data One bit data of the segment, and the length of the bit data is the bit length; the first processor transmits the bit data to a first transceiver of the client, and the first transceiver then sends the The bit data is sent to a supply end of the resource; 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 According to the compression ratio comparison table, the bit data is restored to the fluid quantity data of the time period.

Further, the length of the bit is not greater than one byte, and the first transceiver transmits the bit data to the second transceiver using Narrow Band Internet of Things (NB-IoT) technology.

Further, a time period includes a plurality of time segments, and the compression factor comparison table corresponds to the compression factor with different time segments in the time period; every time period elapses, the first processor will all the above The bit data corresponding to the time segment is transmitted to the second processor via the first transceiver and the second transceiver.

Further, the second processor transmits an indication bit data to the first processor of the client through the second transceiver and the first transceiver, and the first processor changes the corresponding bit data according to the indication bit data The total number of bytes in a time period and/or an interval time; each time the interval time elapses, the first processor calculates the bit data according to the compression factor comparison table and the fluid volume data.

Further, the second processor transmits an indication bit data to the first processor of the client through the second transceiver and the first transceiver, and the first processor changes the compression according to the indication bit data A multiple comparison table and/or a bit length comparison table, the bit length comparison table corresponds to the bit length with the different time segments.

Further, the second transceiver transmits the indicator bit data to the first transceiver using narrowband Internet of Things technology.

Further, there is a peak time and an off-peak time in the time period, and the bit length corresponding to the time section located in the peak time is not less than the bit length corresponding to the time section located in the off-peak time.

Further, the sensor obtains the fluid quantity data from a water meter or a gas meter, and the supply end corresponds to a water company or a natural gas company.

Wherein, the sensor is one of the following: a light sensor, a reed switch, an electromagnetic wave sensor, an image sensor and an electronic water meter.

Further, the second processor of the supply end draws a time trend graph of the fluid amount corresponding to the user end according to the plurality of pieces of the fluid amount data and the corresponding time period.

According to the above technical features, the following effects can be achieved:

1. The user end converts the fluid volume data into bit data, and transmits it to the supply end, and the supply end converts the bit data back to the fluid volume data. There is no need to transmit a large amount of data between the user end and the supply end, effectively reducing communication. Data volume, improve the reliability of narrowband communication.

2. By uploading all the bit data of a day to the supply end at one time, the power consumption of the first transceiver for multiple connection registrations is greatly saved, which is very important for battery-powered client equipment.

3. The length of the bit and the length of the indicated bit data are controlled in one byte group, which can be better applied to the narrow-band Internet of Things to ensure the correctness and stability of data transmission.

4. The second processor provides the time change trend of water consumption at the user end, and the supply end grasps the peak and off-peak water consumption habits of the user end accordingly, and then adjusts the water supply plan of the water purification plant to meet the water demand.

5. According to the user's peak and off-peak water consumption habits, the supply end dynamically adjusts the total number of bytes and the length of the bytes by sending the instruction bit data, and accurately records the change of the user's water consumption with the most appropriate interval time and compression ratio.

6. Using the narrow-band Internet of Things communication technology, the user's water consumption pattern can be grasped in real time, and the dynamic simulation of the water supply pipe network of the hydraulic model can be realized.

1: Client

11: Sensor

12: The first processor

13: First transceiver

2: Supply side

21: Second processor

22: Second transceiver

3: Water meter

A: Fluid volume data

B: Compression ratio comparison table

C: bit length comparison table

D: bit data

E: Indicates bit data

NB-IoT: Narrowband Internet of Things

[Figure 1] is a schematic diagram of the implementation of the embodiment of the present invention.

[Fig. 2] is a schematic flow chart 1 of an embodiment of the present invention, illustrating the execution of a data encoding method for a time-varying mode of fluid volume.

[Figure 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 schematic flowchart of an embodiment of the present invention, which shows that the second processor transmits bit indication data.

In view of the above technical features, the main effect of the data encoding method of the fluid volume time change pattern data of the present invention will be clearly presented in the following embodiments.

Please refer to the first figure to the third figure, which show the data encoding method of the time-varying pattern of fluid volume according to the embodiment of the present invention. Preferably, it is applied to water data. The method for encoding the data of the time-varying pattern of fluid volume includes the following steps: 1. A first processor 12 of the client 1 first obtains a compression factor comparison table B and a one-bit length comparison table C, and the compression factor comparison table B corresponds to a compression factor in a different time period in a time period , the bit length comparison table C corresponds to one bit length with different time segments in the time period, and the first processor 12 obtains the compression factor and the compression factor of each time segment in the time period accordingly. The bit length, the time period, for example, is one day.

The first processor 12 then obtains an interval, that is, the length of the time segment, according to the total number of bytes corresponding to the time period and the length of the bit. More specifically, assuming that the time period is one day, the total number of bytes is 24 groups of bytes, and the bit length is 4 bits in the time period, then the total number of bytes is divided by the The quotient of the bit length is the number of the time segment, that is, 48; and the interval time can be calculated from the time period and the number of the time segment, and the interval time is 0.5 hours. Every time the interval elapses, the first processor 12 converts a fluid quantity data A of a resource obtained by a sensor 11 at the client 1 in the time period into one-bit data D and transmits it to A supply end 2 of the resource, and the length of the bit data D is the bit length.

In a preferred embodiment of the present invention, the length of the bit is not greater than one byte, and each time the time period elapses, the first processor 12 sends the bit data D corresponding to all the time segments through the A first transceiver 13 of the user end 1 and a second transceiver 22 of the supply end 2 transmit the data to a second processor 21 of the supply end 2, for example, once a day for a whole day, the time period corresponding to the The bit data D.

The total number of bytes, the compression factor comparison table B, and the byte length comparison table C can be stored in a memory or a cloud space, for example, and the first processor 12 and the second processor 21 directly or The total number of bytes, the compression factor comparison table B and the bit length comparison table C are obtained from the memory or the cloud space by the first transceiver 13 and the second transceiver 22, which are not used in the present invention. The memory and the cloud space are depicted in the figure.

The resource is water, the supply end 2 of the resource corresponds to a water company, and the sensor 11 obtains the fluid quantity data A from a water meter 3 . The sensor 11 is one of the following: a light sensor, a reed switch, an electromagnetic wave sensor and an image sensor, and the sensor 11 can also be an electronic water meter. In actual implementation, the resource may also be natural gas, which corresponds to the fluid quantity data A obtained from the gas meter, and the supply end 2 corresponds to a natural gas company. When the resource is water, the fluid quantity data A may be the water consumption; when the resource is natural gas, the fluid quantity data A may be the natural gas consumption, but the actual implementation is not limited to this. The power of 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 is a more detailed description of how the first processor 12 converts the fluid volume data A into the bit data D, and the process that the first processor 12 transmits the bit data D to the supply end 2: the first After obtaining the compression ratio comparison table B, the processor 12 obtains the corresponding compression ratio according to the time period, and the first processor 12 divides the fluid volume data A by the compression ratio to obtain the bit Metadata 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 comparison table C.

The first processor 12 transmits the bit data D to the first transceiver 13 of the client 1 , and the first transceiver 13 then transmits the bit data D to a narrowband Internet of Things NB-IoT (Narrow Band Internet of Things) technology is transmitted to the supply end 2 of the resource.

After receiving the bit data D, a second transceiver 22 of the supply end 2 transmits the bit data D to the second processor 21 of the supply 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 period.

The second processor 21 can also draw the fluid volume data A in the time period, even in a whole week or a whole month, and the time segment to form a time change trend diagram of the fluid volume corresponding to the client 1 , so that the supply end 2 can grasp the fluid volume data A of the client end 1 for a period of time, and then evaluate whether to change the total number of bytes, the compression factor, the length of the bytes, and so on.

Please refer to the third and fourth figures, if the second processor 21 of the supply end 2 considers the total number of bytes, the compression ratio (or the compression ratio comparison) according to the time resolution requirement or the fluid volume resolution requirement Table B), the bit length (or the bit length comparison table C), the interval time needs to be changed, the second processor 21 can also use an indicator bit data E in the same string to change the indicator bit The data E is transmitted to the first processor 12 of the client 1 via the second transceiver 22 and the first transceiver 13, and controls the first processor 12 of the client 1 to modify it. In actual implementation, the second transceiver 22 can also transmit the indicator bit data E to the first transceiver 13 through the NB-IoT technology.

For example: in example 1, the length of the byte is 4 bits, and the total number of bytes is 24 bytes; in example 2, the byte in example 1 is not added Under the premise of the total number, increase the interval time in exchange for a larger length of the bit, such as 8 bits; in example 3, it is in Under the premise of not increasing the interval time in the example 1, the total number of bytes is increased in exchange for a larger length of the bytes, such as 8 bits.

The example 1: Take the direct water user of a 20 mm diameter water meter as an example, the minimum unit of sensing of this diameter water meter is 1 liter. The total number of the bytes is 24 bytes, the length of the bytes is 4 bytes, and the interval time is 30 minutes. Assume that the water consumption received at 1:30 (ie the fluid volume data A at 1:30) is 6 liters, and the water consumption received at 18:00 (ie the fluid volume data at 18:00) is 6 liters A) is 54 liters; according to the following table 1, the compression ratio of the former is 1, and the compression ratio of the latter is 4; then divide the fluid volume data A by the compression ratio, and convert the quotient to the binary digit After the metadata D is obtained, it can be known that the bit data D of the former is 0110, and the bit data D of the latter is 1101. After receiving the bit data D, the supply end 2 restores the bit data D to the water consumption of the time period according to the corresponding compression factor. According to this, the water consumption from 1:00 to 1:30 is 6 liters, and the water consumption from 17:30 to 18:00 is 52+3 liters; the latter water consumption plus 3 liters is reflected in the supply end 2 Maximum truncation error after decompressing water consumption.

Example 2: Take the direct water users of the 20mm water meter as an example. The minimum sensing unit of the water meter is 1 liter. The total number of the bytes is 24 bytes, the length of the bytes is 8 bytes, and the interval time is 60 minutes. Assume that the water consumption received at 2:00 (ie the fluid volume data A at 2:00) is 15 liters, and the water consumption received at 9:00 (ie the fluid volume data at 9:00) is 15 liters A) is 100 liters; according to the following table 2, the compression factor of both is 1; then the bit data D of the former is 00001111, and the latter The bit data D is 01100100. After receiving the bit data D, the supply end 2 restores the bit data D to the water consumption of the time period according to the corresponding compression factor. According to this, the water consumption from 1:01 to 2:00 is 15 liters, and the water consumption from 8:01 to 9:00 is 100 liters; here, since the compression factor is 1, although there is no decompression However, the interval time of Example 2 is 60 minutes, which reduces the time resolution of water consumption analysis compared to Example 1.

Example 3: Take the direct water users of the 20mm water meter as an example. The minimum sensing unit of the water meter is 1 liter. The total number of the bytes is 48 bytes, the length of the bytes is 8 bytes, and the interval time is 30 minutes. Assuming that the water consumption received at 1:30 (ie the fluid volume data A at 1:30) is 6 liters, and the water consumption received at 7:30 (ie the fluid volume data at 7:30) A) is 72 liters; according to Table 3 below, the compression factor of both is 1; then the bit data D of the former is 00000110, and the bit data D of the latter is 01001000. After receiving the bit data D, the supply end 2 restores the bit data D to the water consumption of the time period according to the corresponding compression factor. According to this, the water consumption from 1:01 to 1:30 is 6 liters, and the water consumption from 7:01 to 7:30 is 72 liters; here, since the compression factor is 1, although there is no decompression However, the bit length of Example 3 is 8 bits, which greatly increases the data volume of narrowband communication compared to Example 1.

In the examples 1 to 3, regardless of whether the time segment is at a peak time or an off-peak time in the time period, the bit length is a fixed value in the time period. If the bit length can be adjusted flexibly according to the water consumption, it will be better to take into account the data correctness and reduce the amount of data than the second example and the third example. The following is a detailed description of four examples:

Example 4: Take the direct water users of the 20mm water meter as an example. The minimum sensing unit of the water meter is 1 liter. The total number of bytes is 32 bytes, which can accommodate 16 pieces of the bit data D with the bit length of 8 bits and 32 pieces of the bit data D with the bit length of 4 bits, so that the interval The time is 30 minutes. Assuming that the water consumption received at 1:30 (ie the fluid volume data A at 1:30) is 6 liters, and the water consumption received at 7:30 (ie the fluid volume data at 7:30) A) is 72 liters; according to Table 4, the compression factor of both is 1; according to Table 5, the bit length of the former is 4 bits, and the bit length of the latter is 8 bits; then the former The bit data D is 0110, and the bit data D of the latter is 01001000. After receiving the bit data D, the supply end 2 restores the bit data D to the water consumption of the time period according to the corresponding compression factor. According to this, the water consumption from 1:01 to 1:30 is 6 liters, and the water consumption from 7:01 to 7:30 is 72 liters.

Here, since the compression factor is 1, there is no truncation error after decompression. At the same time, due to the low water consumption at 1:30 in the morning, which is the off-peak time, the bit length only needs to be configured with 4 bits; At 7:30, the water consumption is high, 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. This not only avoids the truncation error after decompression, but also reduces the unnecessary bit length and reduces the data volume of narrowband communication.

Table 4. Comparison table of compression ratios for example 4 (excerpt):

According to the above example, it can be understood that as long as the water consumption trend of the peak time and the off-peak time is grasped, and the total number of bytes, the compression factor and the bit length are properly adjusted, the minimum bit length can be recorded for 24 hours. Water mode. For example 4, assuming that 07:01 to 09:00, 11:01 to 12:30, and 17:01 to 20:30 are the peak times, and the rest are the off-peak times, the total number of bytes is only It takes 32 bytes to achieve the effect of 48 bytes in the third example. For narrowband communication, since the smaller the packet size, the more stable data transmission can be ensured, and the fourth example can indeed achieve more stable transmission.

With the data encoding method for the time-varying pattern of fluid volume, taking the case where the supply end 2 is a water company as an example, the water company can know the user's water consumption pattern in the water supply area. Combining the user's water consumption pattern with the water supply pressure of the water plant, the hydraulic model of the water supply network can be constructed.

Water usage pattern analysis is like a user leak monitor. Generally, users do not use water continuously for 24 hours. For example, in the dead of night or when no one is at home, the water consumption should be zero. If the water consumption mode maintains a certain amount of water for 24 hours, this water consumption may be the user's water leakage.

Analysis of water consumption patterns can assist users in their home care. Based on the characteristics of the user's daily life indirectly reflected by the water consumption pattern, if the water consumption pattern suddenly changes, the user's daily life may be abnormal. E.g, Elderly people living alone may suddenly fall when they wake up late at night to go to the toilet. Water companies can use this to change the stereotype that they can only charge for meter reading, and enhance the image of user-friendly services.

To sum up, the data encoding method of the time-varying pattern of fluid volume is based on the extreme asymmetry between the peak and off-peak water consumption of the user, and uses bits as the water consumption recording unit, and assigns the peak water consumption exceeding the length of the bit to the Compression factor, so that peak and off-peak water consumption can be recorded with the bit data D. After the supply end 2 receives the bit data D, it restores the water consumption of the time segment according to the compression multiples of the different time segments. Since the water consumption of each time period can be recorded with the most concise bit data D, the water consumption of all time periods of the day can be uploaded to the cloud with only one IoT communication, which not only greatly reduces the power consumption, but also reduces the water consumption. The dynamic data compression technology greatly improves the success rate of IoT data uploading.

Based on the descriptions of the above embodiments, one can fully understand the operation, use and effects of the present invention, but the above-mentioned embodiments are only preferred embodiments of the present invention, which should not limit the implementation of the present invention. Scope, that is, simple equivalent changes and modifications made according to the scope of the patent application of the present invention and the contents of the description of the invention, all fall within the scope of the present invention.

1: Client

12: The first processor

13: First transceiver

2: Supply side

21: Second processor

22: Second transceiver

A: Fluid volume data

B: Compression ratio comparison table

C: bit length comparison table

D: bit data

NB-IoT: Narrowband Internet of Things

Claims (10)

A method for encoding fluid volume time change pattern data, comprising: in a time segment, a sensor obtains a fluid volume data of a resource at a user end; a first processor at the user end obtains a compression factor comparison table , one-bit length and the fluid volume data, the compression ratio comparison table corresponds to a compression ratio in different time segments; the first processor calculates the time according to the compression ratio comparison table and the fluid volume data One bit data of the segment, and the length of the bit data is the bit length; the first processor transmits the bit data to a first transceiver of the client, and the first transceiver then sends the The bit data is sent to a supply end of the resource; 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 According to the compression ratio comparison table, the bit data is restored to the fluid quantity data of the time period. According to the data encoding method of fluid volume time change pattern in claim 1, further, the length of the bit is not more than one byte, and the first transceiver is a Narrow Band Internet of Things (NB-IoT) The technique transmits the bit data to the second transceiver. According to the data encoding method for the time change pattern of fluid volume in claim 1, further, a time period includes a plurality of time sections, and the compression ratio comparison table corresponds to the compression ratio with different time sections in the time period; During the time period, the first processor transmits the bit data corresponding to all the time segments to the second processor through the first transceiver and the second transceiver. According to the method for encoding fluid volume time change pattern data in claim 3, further, the second processor transmits an indication bit data to the first processor of the client through the second transceiver and the first transceiver, The first processor modifies a total number of bytes and/or an interval corresponding to the time period according to the indicated bit data; every time the interval elapses, the first processor changes the compression factor comparison table and the fluid volume according to the data to calculate the bit data. According to the method for encoding fluid volume time change pattern data in claim 3, further, the second processor transmits an indication bit data to the first processor of the client through the second transceiver and the first transceiver, The first processor modifies the compression factor comparison table and/or the bit length comparison table according to the indicated bit data, and the bit length comparison table corresponds to the bit length with the different time segments. As claimed in claim 4 or 5, the data encoding method for the time-varying pattern of fluid volume, further, the second transceiver transmits the indicator bit data to the first transceiver using a narrowband Internet of Things technology. According to the data encoding method for the time change pattern of fluid volume in claim 5, further, there is a peak time and an off-peak time in the time period, and the length of the bit corresponding to the time section located in the peak time is not less than that located in the off-peak time. The length of the bit corresponding to the time segment of the peak time. According to the data encoding method of fluid volume time change pattern in claim 1, further, the sensor obtains the fluid volume data from a water meter or a gas meter, and the supply end corresponds to a water company or a natural gas company. As claimed in claim 1, wherein the sensor is one of the following: a light sensor, a reed switch, an electromagnetic wave sensor, an image sensor and an electronic water meter. According to the data encoding method of the fluid volume time change pattern of claim 1, further, the second processor of the supply end draws a fluid volume time change trend corresponding to the user end according to the plurality of pieces of the fluid volume data and the corresponding time segment picture.

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