TWI770870B - Encoding method for processing time-based change data of fluid volume - Google Patents
Encoding method for processing time-based change data of fluid volume Download PDFInfo
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本發明係關於一種流體量的編碼方法,特別是指一種流體量隨時間變化的數據編碼方法。 The present invention relates to a coding method of fluid quantity, in particular to a data coding method of fluid quantity varying with time.
供水管網水力模型是自來水公司優化調度及降低漏水損失的必備工具,而用戶端用水量時間變化模式則是構建水力模型的基礎數據。 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.
以人工方式每日抄取用戶不同時間段的用水量變化,以構建水力模型,顯然不切實際。而以物聯網自動讀表方式,若每30分鐘回傳一筆用水量數據,其電力損耗是電池供電之物聯網水表難以負荷。物聯網自動讀表方式具體例如有中華民國專利公告號第I710752號所提供的一種水表之智慧讀取裝置及其控制方法,主要是藉由影像擷取元件對水表之數值顯示區進行拍攝,以獲得水度影像,再從水度影像分析出水度數值。 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.
前述專利案中,每30分鐘傳送一筆水表數值,甚至是水度影像的大量電力損耗,可想而知。 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.
爰此,本發明人為了解決上述問題,以將尖離峰用水量皆以位元紀錄,使得水表在一天中僅需一次通訊即可完成當日用水模式數據上傳,大幅減少電力消耗,而提出一種流體量時間變化模式數據編碼方法。 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.
該流體量時間變化模式數據編碼方法,包含:在一時間區段中,一感測器於一用戶端取得一資源的一流體量資料;該用戶端的一第一處理器取得一壓縮倍數對照表、一位元長度及該流體量資料,該壓縮倍數對照表係以不同之該時間區段對應一壓縮倍數;該第一處理器根據該壓縮倍數對照表及該流體量資料,計算出該時間區段的一位元資料,且該位元資料的長度為該位元長度;該第一處理器將該位元資料傳送至該用戶端的一第一收發器,該第一收發器再將該位元資料傳送至該資源的一供給端;該供給端的一第二收發器接收到該位元資料後,將該位元資料傳送至該供給端的一第二處理器;以及該第二處理器根據該壓縮倍數對照表,將該位元資料還原成該時間區段的該流體量資料。 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.
進一步,該位元長度不大於一個位元組,且該第一收發器係以窄頻物聯網(Narrow Band Internet of Things,NB-IoT)技術將該位元資料傳送至該第二收發器。 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.
進一步,有一時間週期包含複數時間區段,該壓縮倍數對照表係在該時間週期中以不同之該時間區段對應該壓縮倍數;每經過該時間週期,該第一處理器再將全部所述時間區段對應之該位元資料經由該第一收發器及該第二收發器傳送至該第二處理器。 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.
進一步,該第二處理器將一指示位元資料經由該第二收發器及該第一收發器傳送至該用戶端的該第一處理器,該第一處理器根據該指示位元資料更改對應該時間週期之一位元組總數及/或一間隔時間;每經過該間隔時間,該第一處理器根據該壓縮倍數對照表及該流體量資料計算出該位元資料。 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.
進一步,該第二處理器將一指示位元資料經由該第二收發器及該第一收發器傳送至該用戶端的該第一處理器,該第一處理器根據該指示位元資料更改該壓縮倍數對照表及/或一位元長度對照表,該位元長度對照表係以不同之該時間區段對應該位元長度。 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.
進一步,該第二收發器係以窄頻物聯網技術將該指示位元資料傳送至該第一收發器。 Further, the second transceiver transmits the indicator bit data to the first transceiver using narrowband Internet of Things technology.
進一步,該時間週期中有一尖峰時間及一離峰時間,位於該尖峰時間之該時間區段對應的該位元長度,不小於位於該離峰時間之該時間區段對應的該位元長度。 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.
進一步,該感測器係自水表或氣量計取得該流體量資料,該供給端對應為水公司或天然氣公司。 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.
其中,該感測器係為以下之一:光感測器、磁簧管、電磁波感測器、影像感測器及電子水量計。 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.
進一步,該供給端的該第二處理器根據複數筆該流體量資料及對應的該時間區段,繪製對應該用戶端的一流體量時間變化趨勢圖。 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.
根據上述技術特徵可達成以下功效: According to the above technical features, the following effects can be achieved:
1.用戶端將流體量資料轉換成位元資料,並將其傳輸至供給端,供給端再將位元資料轉換回流體量資料,用戶端及供給端之間無需傳輸大量數據,有效減少通訊數據量,提高窄頻通訊之可靠性。 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.藉由將一日所有位元資料一次性上傳供給端,大幅節省第一收發器多次連線註冊的電力消耗,這對電池供電的用戶端設備至關重要。 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.將位元長度及指示位元資料的長度都控制在一個位元組內,可以更好的應用於窄頻物聯網,確保數據傳輸的正確性與穩定性。 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.第二處理器提供用戶端用水量時間變化趨勢,供給端據此掌握用戶端尖峰、離峰用水習慣,進而調整淨水廠供水規劃,滿足用水需求。 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.根據用戶尖峰、離峰用水習慣,供給端藉由下發指示位元資料,動態調整位元組總數及位元長度,以最適當的間隔時間與壓縮倍數,準確記錄用戶用水量變化。 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.以窄頻物聯網通訊技術,即時掌握用戶用水模式,具體實現水力模型之供水管網動態模擬。 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:用戶端 1: Client
11:感測器 11: Sensor
12:第一處理器 12: The first processor
13:第一收發器 13: First transceiver
2:供給端 2: Supply side
21:第二處理器 21: Second processor
22:第二收發器 22: Second transceiver
3:水表 3: Water meter
A:流體量資料 A: Fluid volume data
B:壓縮倍數對照表 B: Compression ratio comparison table
C:位元長度對照表 C: bit length comparison table
D:位元資料 D: bit data
E:指示位元資料 E: Indicates bit data
NB-IoT:窄頻物聯網 NB-IoT: Narrowband Internet of Things
[第一圖]係本發明實施例之實施示意圖。 [Figure 1] is a schematic diagram of the implementation of the embodiment of the present invention.
[第二圖]係本發明實施例之流程示意圖一,示意執行流體量時間變化模式數據編碼方法。
[Fig. 2] is a
[第三圖]係本發明實施例之功能方塊示意圖,示意流體量資料與位元資料的轉換。 [Figure 3] is a functional block diagram of an embodiment of the present invention, illustrating the conversion of fluid volume data and bit data.
[第四圖]係本發明實施例之流程示意圖二,示意第二處理器傳送位元指示資料。 [FIG. 4] is a second schematic flowchart of an embodiment of the present invention, which shows that the second processor transmits bit indication data.
綜合上述技術特徵,本發明流體量時間變化模式數據編碼方法的主要功效將可於下述實施例清楚呈現。 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.
請參閱第一圖至第三圖,係揭示本發明實施例流體量時間變化模式數據編碼方法,較佳地,係應用於用水數據上,該流體量時間變化模式數據編碼方法包含以下步驟:一用戶端1的一第一處理器12首先取得一壓縮倍數對照表B及一位元長度對照表C,該壓縮倍數對照表B係在一時間週期中以不同之一時間區段對應一壓縮倍數,該位元長度對照表C係在該時間週期中以不同之該時間區段對應一位元長度,該第一處理器12據此取得該時間週期中每一時間區段的該壓縮倍數及該位元長度,該時間週期例如為一日。
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
該第一處理器12再根據對應該時間週期之一位元組總數以及該位元長度,取得一間隔時間,即該時間區段的長度。更明確的說,假設該時間週期為一日,該位元組總數為24組位元組,該位元長度在該時間週期中皆為4位元,則由該位元組總數除以該位元長度的商即為該時間區段的數量,即48;而由該時間週期及該時間區段的數量即可計算出該間隔時間,該間隔時間也就是0.5小時。每經過該間隔時間,該第一處理器12將一感測器11於該用戶端1在該時間區段中取得之一資源的一流體量資料A,轉換為一位元資料D並傳送至該資源的一供給端2,且該位元資料D的長度為該位元長度。
The
在本發明之較佳實施例中,該位元長度不大於一個位元組,每經過該時間週期,該第一處理器12再將全部所述時間區段對應之該位元資料D經由該用戶端1的一第一收發器13及該供給端2的一第二收發器22傳送至該供給端2的一第二處理器21,例如一天傳一次一整天所述時間區段對應之該位元資料D。
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
該位元組總數、該壓縮倍數對照表B及該位元長度對照表C例如可以儲存於一記憶體或一雲端空間等等,該第一處理器12及該第二處理器21並直接或藉由該第一收發器13及該第二收發器22自該記憶體或該雲端空間取得該位元組總數、該壓縮倍數對照表B及該位元長度對照表C,惟未於本發明圖式中繪出該記憶體及該雲端空間。
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
該資源為水,該資源的該供給端2即對應水公司,該感測器11係自一水表3取得該流體量資料A。該感測器11係為以下之一:光感測器、磁簧管、電磁波感測器及影像感測器,該感測器11也可以就是電子水量計。於實際實施時,該資源也可以為天然氣,而係對應自氣量計取得該流體量資料A,該供給端2即對應為天然氣公司。當該資源為水時,該流體量資料A可以是用水量;當該資源為天然氣時,該流體量資料A可以是天然氣用量,惟實際實施時不限於此。該感測器11、該第一處理器12及該第一收發器13的電力可以來自一電池或一插座等等,惟未於本發明圖式中繪出該電池及該插座。
The resource is water, the
以下更詳細的說明該第一處理器12如何將該流體量資料A轉換為該位元資料D,以及該第一處理器12將該位元資料D傳送至該供給端2的過程:該第一處理器12取得該壓縮倍數對照表B之後,根據該時間區段取得對應之該壓縮倍數,該第一處理器12並將該流體量資料A與該壓縮倍數相除計算,而取得該位元資料D,且該位元資料D的長度與該位元長度對照表C中該時間區段對應之該位元長度相同。
The following is a more detailed description of how the
該第一處理器12將該位元資料D傳送至該用戶端1的該第一收發器13,該第一收發器13再將該位元資料D以一窄頻物聯網NB-IoT(Narrow Band Internet of Things)技術傳送至該資源的該供給端2。
The
該供給端2的一第二收發器22接收到該位元資料D後,將該位元資料D傳送至該供給端2的該第二處理器21。該第二處理器21根據該壓縮倍數對照表B,將該位元資料D乘以該壓縮倍數,而還原成該時間區段對應之該流體量資料A。
After receiving the bit data D, a
該第二處理器21還可以將該時間週期中,甚至一整週、一整月中的該流體量資料A,與該時間區段繪製成對應該用戶端1的一流體量時間變化趨勢圖,方便該供給端2掌握該用戶端1一段時間中的該流體量資料A,進而評估是否要更改該位元組總數、該壓縮倍數、該位元長度等等。
The
請參閱第三圖及第四圖,若是該供給端2的該第二處理器21根據時間解析度需求或流體量解析度需求,認為該位元組總數、該壓縮倍數(或該壓縮倍數對照表B)、該位元長度(或該位元長度對照表C)、該間隔時間需要更改,該第二處理器21也可以藉由同一串的一指示位元資料E,將該指示位元資料E經由該第二收發器22及該第一收發器13傳送至該用戶端1的該第一處理器12,控制該用戶端1的該第一處理器12更改之。於實際實施時,該第二收發器22同樣可以藉由該窄頻物聯網NB-IoT技術將該指示位元資料E傳送至該第一收發器13。
Please refer to the third and fourth figures, if the
舉例來說:在一舉例一中,該位元長度係為4位元,該位元組總數係為24位元組;在一舉例二中,是在不增加該舉例一之該位元組總數的前提下,以增加該間隔時間換取較大的該位元長度,如8位元;在一舉例三中,是在 不增加該舉例一之該間隔時間的前提下,以增加該位元組總數換取較大的該位元長度,如8位元。 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.
該舉例一:以20毫米之一口徑水表的直接用水戶為例,該口徑水表感測最小單位為1公升。該位元組總數為24位元組,該位元長度為4位元,該間隔時間為30分。假設1點30分時接收到的用水量(即1點30分的該流體量資料A)為6公升,而18點0分時接收到的用水量(即18點0分的該流體量資料A)為54公升;根據下表一,前者之該壓縮倍數為1,後者之該壓縮倍數為4;則將該流體量資料A除以該壓縮倍數,並將商轉換為二進位的該位元資料D後,即可得知前者之該位元資料D為0110,後者之該位元資料D為1101。該供給端2接收到該位元資料D後,再將該位元資料D根據各自相應之該壓縮倍數還原為該時間區段的用水量。據此,1點0分至1點30分的用水量為6公升,17點30分至18點0分的用水量為52+3公升;後者用水量加3公升,在反映該供給端2將用水量解壓縮後之最大截尾誤差。
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
舉例二:以20毫米之該口徑水表的直接用水戶為例,該口徑水表感測最小單位為1公升。該位元組總數為24位元組,該位元長度為8位元,該間隔時間為60分。假設2點0分時接收到的用水量(即2點0分的該流體量資料A)為15公升,而9點0分時接收到的用水量(即9點0分的該流體量資料A)為100公升;根據下表二,兩者之該壓縮倍數皆為1;則前者之該位元資料D為00001111,後者
之該位元資料D為01100100。該供給端2接收到該位元資料D後,再將該位元資料D根據各自相應之該壓縮倍數還原為該時間區段的用水量。據此,1點01分至2點0分的用水量為15公升,8點01分至9點0分的用水量為100公升;在此由於該壓縮倍數為1,雖然不存在解壓縮後之截尾誤差,然而,該舉例二的該間隔時間為60分,相較於該舉例一,降低了用水量分析的時間解析度。
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
該舉例三:以20毫米之該口徑水表的直接用水戶為例,該口徑水表感測最小單位為1公升。該位元組總數為48位元組,該位元長度為8位元,該間隔時間為30分。假設1點30分時接收到的用水量(即1點30分的該流體量資料A)為6公升,而7點30分時接收到的用水量(即7點30分的該流體量資料A)為72公升;根據下表三,兩者之該壓縮倍數皆為1;則前者之該位元資料D為00000110,後者之該位元資料D為01001000。該供給端2接收到該位元資料D後,再將該位元資料D根據各自相應之該壓縮倍數還原為該時間區段的用水量。據此,1點01分至1點30分的用水量為6公升,7點01分至7點30分的用水量為72公升;在此由於該壓縮倍數為1,雖然不存在解壓縮後之截尾誤差,然而,該舉例三的該位元長度為8位元,相較於該舉例一,大幅增加窄頻通訊的數據量。
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
在該舉例一至該舉例三中,不論該時間區段位於該時間週期中的一尖峰時間還是一離峰時間,該位元長度在該時間週期中都為固定值。如果該位元長度能隨用水量大小機動調整,將比該舉例二與該舉例三更能兼顧數據正確性與減少數據量。以下以一舉例四詳細說明: 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:
該舉例四:以20毫米之該口徑水表的直接用水戶為例,該口徑水表感測最小單位為1公升。該位元組總數為32位元組,可以容納16段該位元長度為8位元的該位元資料D及32段該位元長度為4位元的該位元資料D,使得該間隔時間為30分。假設1點30分時接收到的用水量(即1點30分的該流體量資料A)為6公升,而7點30分時接收到的用水量(即7點30分的該流體量資料A)為72公升;根據下表四,兩者之該壓縮倍數皆為1;根據下表五,前者之該位元長度為4位元,後者之該位元長度為8位元;則前者之該位元資料D為0110,後者之該位元資料D為01001000。該供給端2接收到該位元資料D後,再將該位元資料D根據各自相應之該壓縮倍數還原為該時間區段的用水量。據此,1點01分至1點30分的用水量為6公升,7點01分至7點30分的用水量為72公升。
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
在此,由於該壓縮倍數為1,因此不存在解壓縮後之截尾誤差,同時,由於凌晨1點30分用水量少,屬該離峰時間,該位元長度只需配置4位元;7點30分用水量多,屬該尖峰時間,該位元長度增加為8位元。可以發現,位於該尖峰時間之該時間區段對應的該位元長度,不小於位於該離峰時間之該時間區段對應的該位元長度。如此不但避免解壓縮後之截尾誤差,更可減少不必要的該位元長度,降低窄頻通訊的數據量。 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.
表四、舉例四的壓縮倍數對照表(節錄):
根據以上舉例說明可以了解,只要掌握該尖峰時間及該離峰時間的用水趨勢,適當調整該位元組總數、該壓縮倍數及該位元長度,即可以最少的該位元長度記錄24小時的用水模式。以該舉例四來說,假設07:01至09:00、11:01至12:30以及17:01至20:30為該尖峰時間,其餘為該離峰時間,則該位元組總數只需32位元組即可達到該舉例三之48位元組的效果。對窄頻通訊而言,由於封包量越小越能確保數據的穩定傳輸,該舉例四確實可以更為穩定的傳輸。 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.
藉由該流體量時間變化模式數據編碼方法,以該供給端2是水公司的情況為例,水公司可以得知供水區域內的用戶用水模式。結合用戶用水模式與水廠供水壓力,即可建構供水管網水力模型,水公司可以進一步尋找最佳供水壓力,不只減少加壓馬達之電力損耗,同時降低漏水損失。
With the data encoding method for the time-varying pattern of fluid volume, taking the case where the
用水模式分析有如用戶漏水監視器。一般用戶不會24小時持續用水,例如夜深人靜或無人在家,此時用水量應該為零。如果用水模式24小時都維持一定用水量以上,此用水量可能就是用戶的漏水量。 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.
用水模式分析可輔助用戶之居家照護。基於用水模式間接反映用戶生活起居之特性,如果用水模式突然改變,可能用戶起居發生異常。例如, 獨居老人深夜起床如廁之用水模式突然終止,可能發生意外跌倒。水公司可藉此改變只能抄表收費的刻板印象,提升用戶服務的親民形象。 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.
綜合來說,該流體量時間變化模式數據編碼方法是基於用戶尖峰與離峰用水量極端不對稱之特性,以位元為用水量記錄單位,並將超出該位元長度之尖峰用水量賦予該壓縮倍數,進而達到尖峰、離峰用水量皆能以該位元資料D記錄之目的。待供給端2收到該位元資料D,再根據不同該時間區段之該壓縮倍數,還原該時間區段之用水量。由於每一時間區段用水量都能以最精簡的該位元資料D記錄,只要一次物聯網通訊即可將一日所有時間區段用水量上傳雲端,不僅大幅減少電力消耗,更由於用水量數據的動態壓縮技術,大幅提升物聯網數據上傳的成功率。
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
綜合上述實施例之說明,當可充分瞭解本發明之操作、使用及本發明產生之功效,惟以上所述實施例僅係為本發明之較佳實施例,當不能以此限定本發明實施之範圍,即依本發明申請專利範圍及發明說明內容所作簡單的等效變化與修飾,皆屬本發明涵蓋之範圍內。 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:用戶端 1: Client
12:第一處理器 12: The first processor
13:第一收發器 13: First transceiver
2:供給端 2: Supply side
21:第二處理器 21: Second processor
22:第二收發器 22: Second transceiver
A:流體量資料 A: Fluid volume data
B:壓縮倍數對照表 B: Compression ratio comparison table
C:位元長度對照表 C: bit length comparison table
D:位元資料 D: bit data
NB-IoT:窄頻物聯網 NB-IoT: Narrowband Internet of Things
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