Method and system for controlling communication cycle of water meter based on freeze risk prediction

Abstract

A method for controlling a communication cycle based on a prediction of a freezing risk of a water meter according to an embodiment of the present invention utilizes a server configured to communicate with a water meter through a communication network to predict the freezing risk of the water meter and, based thereon, control the communication cycle of the water meter. The method comprises: a step of estimating a Time-to-Freeze (TTF) representing the time remaining until the water meter freezes based on at least one of the temperature, humidity, and flow rate of the water meter; a step of calculating a freezing risk index using the estimated TTF, a low-temperature duration representing the cumulative time the water meter remains below a critical temperature, and the flow rate status of the water meter; and a step of transmitting a control signal to the water meter for adjusting the communication cycle of the water meter based on the calculated freezing risk index.

Description

Technology Field

[0001] The present invention relates to a method and system for controlling the communication cycle based on the prediction of the risk of freezing of a water meter. Background Technology

[0002] In various field environments, water meters have been exposed to the risk of meter damage and water supply interruption due to freezing and bursting during the winter. Conventionally, a simple threshold method was common, which would sound an alarm when a temperature sensor detected a temperature below 0°C. However, since the actual occurrence of bursting is influenced by the meter temperature, the cumulative time spent below the threshold temperature, and the flow rate, this single threshold method had limitations, as it frequently resulted in false alarms and missed detections.

[0003] For example, conventional technology suffered from low accuracy due to its single-sensor focus and difficulty in reflecting regional or installation environmental differences caused by the operation of fixed thresholds. Furthermore, the lack of predictive capabilities limited response to manual intervention after freezing occurred, and the absence of multi-sensor fusion made it difficult to quantify risk levels. Most notably, the absence of a Time-to-Freeze (TTF) model to estimate the time remaining until freezing made it difficult to predict the time, and the lack of transmission control based on risk levels resulted in inefficient management of communication and operational resources.

[0004] The matters described in the background technology above are intended to aid in understanding the background of the invention and may include matters that are not disclosed prior art. Prior art literature

[0005] Korean Patent Publication No. 10-2158188 (September 15, 2020) The problem to be solved

[0006] One embodiment of the present invention provides a method and system for controlling the communication cycle of a water meter based on the prediction of freezing risk, which quantifies the risk of freezing by fusing temperature, humidity, and flow rate data of the water meter and calculates it as a multi-stage risk level to dynamically control the communication cycle of the water meter, thereby increasing alarm reliability by reducing false positives and missed detections, saving battery life and network resources, and enabling early detection and rapid response to the risk of freezing. means of solving the problem

[0007] A method for controlling a communication cycle based on a prediction of a freezing risk of a water meter according to an embodiment of the present invention utilizes a server configured to communicate with a water meter through a communication network to predict the freezing risk of the water meter and, based thereon, control the communication cycle of the water meter. The method comprises: a step of estimating a Time-to-Freeze (TTF) representing the time remaining until the water meter freezes based on at least one of the temperature, humidity, and flow rate of the water meter; a step of calculating a freezing risk index using the estimated TTF, a low-temperature duration representing the cumulative time the water meter remains below a critical temperature, and the flow rate status of the water meter; and a step of transmitting a control signal to the water meter for adjusting the communication cycle of the water meter based on the calculated freezing risk index.

[0008] The step of estimating the TTF may include: a step of calculating an initial TTF using the current temperature of the water meter and the rate of change of temperature over a certain period of time based on the current temperature; a step of calculating a humidity correction value of the water meter using a pre-learned humidity correction coefficient; a step of calculating a flow rate correction value of the water meter using a pre-learned flow rate correction coefficient; and a step of estimating a final TTF using the initial TTF, the humidity correction value, and the flow rate correction value.

[0009] The step of calculating the above freezing risk index may include: a step of converting each of the above TTF, the above low temperature duration, and the above flow rate status into a relative risk within a preset standard range; and a step of calculating the above freezing risk index by weighting the relative risk for each of the above items.

[0010] The step of converting to the relative risk level may include: a step of assigning a predetermined threshold value to each of the above items; a step of comparing each of the above items with the corresponding threshold value; and a step of determining the relative risk level for each of the above items within the above standard range based on the result of the comparison.

[0011] A method for controlling a communication cycle based on a prediction of freezing risk of a water meter according to one embodiment of the present invention further includes the step of determining a risk level corresponding to a freezing risk index according to a predetermined standard, and the step of transmitting the control signal to the water meter may include the step of generating the control signal to adjust the communication cycle differently based on the determined risk level; and the step of transmitting the generated control signal to the water meter.

[0012] The step of determining the above risk level may include the step of determining a risk level corresponding to the above freezing risk index by referring to a lookup table stored in memory or a corresponding calculation rule.

[0013] The step of determining the risk level may further include the step of storing in the memory a lookup table that maps each of the plurality of risk levels, each indicating the degree of risk for each of the preset plurality of score intervals.

[0014] The step of determining the risk level may include: a step of determining a risk level corresponding to the freeze risk index by applying a hysteresis transition rule to the freeze risk index, and maintaining a state value representing a previously determined and stored risk level; a step of referring to the hysteresis transition rule in which an upward transition threshold value and a downward transition threshold value are set differently for each boundary of adjacent risk levels; and a step of determining the risk level such that if the newly calculated freeze risk index is greater than or equal to the upward transition threshold value of the corresponding boundary, it transitions to a higher risk level, and if it is less than or equal to the downward transition threshold value, it transitions to a lower risk level, and in the interval between the upward transition threshold value and the downward transition threshold value, the state value is maintained without changing.

[0015] The step of generating the control signal may include generating the control signal to adjust the communication period to be shorter or longer than the basic transmission period according to the determined risk level based on a preset basic transmission period.

[0016] The step of transmitting the control signal to the water meter may include the step of transmitting the control signal to the water meter so that, in the event that an acknowledgment (ACK) for the control signal is not received from the water meter or an error occurs in the acknowledgment, the communication cycle automatically returns to a preset basic transmission cycle.

[0017] A server performing a communication cycle control method based on a prediction of freezing risk of a water meter according to an embodiment of the present invention includes a memory; and a processor that loads and executes a plurality of instructions stored in the memory. The processor estimates a Time-to-Fast (TTF) representing the time remaining until the water meter freezes based on at least one of the temperature, humidity, and flow rate of the water meter, calculates a freezing risk index using the estimated TTF, a low-temperature duration representing the cumulative time the water meter remains below a critical temperature, and the flow rate status of the water meter, and transmits a control signal for adjusting the communication cycle of the water meter to the water meter based on the calculated freezing risk index.

[0018] The processor can convert each of the TTF, the low temperature duration, and the flow rate status into a relative risk within a preset standard range, and calculate the freezing risk index by weighting the relative risk for each of the items. Effects of the invention

[0019] According to one embodiment of the present invention, Time-to-Freeze (TTF) is estimated using data such as temperature, humidity, and flow rate of a water meter, and the result is calculated as a single freezing risk index along with the low-temperature duration and flow rate status, thereby structurally reducing the problems of false positives and missed detections associated with existing simple threshold-based detection methods and improving alarm reliability.

[0020] According to one embodiment of the present invention, multi-stage risk assessment considering various environments and usage patterns is possible, and through the communication cycle control logic of the water meter at each risk level (e.g., risk level 1 to 5), when the risk level is low, communication is reduced (by extending the reporting cycle) to save battery life and network resources, and when the risk level is high, the reporting cycle is shortened to enable early detection and rapid response.

[0021] According to one embodiment of the present invention, rapid data reporting and response at the risk stage can prevent freezing accidents of water meters and improve maintenance efficiency. Brief explanation of the drawing

[0022] FIG. 1 is a diagram showing the network configuration of a server that performs a communication cycle control method based on the prediction of the risk of freezing of a water meter according to one embodiment of the present invention. Figure 2 is a block diagram illustrating the detailed configuration of the server of Figure 1. FIGS. 3 to 6 are flowcharts illustrating a communication cycle control method based on the prediction of freezing risk of a water meter according to an embodiment of the present invention. FIG. 7 is a diagram exemplifying the communication cycle of risk levels according to the freezing risk index of a water meter in one embodiment of the present invention. Specific details for implementing the invention

[0023] Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the attached drawings.

[0024] The embodiments are provided to more fully explain the invention to those skilled in the art, and the following embodiments may be modified in various different forms, and the scope of the invention is not limited to the following embodiments. Rather, these embodiments are provided to make the disclosure more faithful and complete and to fully convey the spirit of the invention.

[0025] The terms used herein are for describing specific embodiments and are not intended to limit the invention. Additionally, the singular form in this specification may include the plural form unless the context clearly indicates otherwise. Terms such as “comprising,” “having,” and “having” in this application are intended to specify the presence of features, numbers, steps, actions, components, parts, or combinations thereof of the invention, and should be understood as not precluding the existence or addition of one or more other features, numbers, steps, actions, components, parts, or combinations thereof.

[0026] The drawings are intended solely to facilitate an understanding of the concept of the present invention and should not be interpreted as limiting the scope of the invention. Additionally, relative thicknesses, lengths, or sizes in the drawings may be exaggerated for convenience and clarity of explanation.

[0027] FIG. 1 is a diagram showing the network configuration of a server that performs a communication cycle control method based on the prediction of the risk of freezing of a water meter according to one embodiment of the present invention.

[0028] Referring to FIG. 1, the server (140) is connected to a communication network (130), such as a base station / gateway, and is connected to a communication terminal (110) through the communication network (130) to communicate with water meters (120) installed at multiple sites.

[0029] A water meter (120) is installed on-site and periodically measures at least one sensor data of temperature, humidity, and flow rate. Each consumer may have one or more water meters (120).

[0030] A communication terminal (110) is connected to a water meter (120) via a wired or wireless connection and transmits sensor data measured by the water meter (120) to a server (140) via a communication network (130). At this time, the communication network (130) may include various wireless / wired infrastructures such as NB-IoT, LTE-M, LoRa, Sigfox, Wi-Fi / Ethernet.

[0031] The communication network (130) can collect report data coming from multiple consumers and transmit it to the server (140), and relay control signals (communication cycle adjustment, etc.) from the server (140) downlink.

[0032] FIG. 2 is a block diagram illustrating the detailed configuration of the server (140) of FIG. 1.

[0033] Referring to FIGS. 1 and 2, the server (140) may be configured to include a communication module (210), memory (220), and a processor (230).

[0034] The communication module (210) is connected to the communication terminal (110) of each customer via the communication network (130), and can perform data transmission and reception with the water meter (120) through this. The communication module (210) can receive sensor data, status information, etc. upstream, and transmit communication cycle adjustment commands, notification triggers, parameter updates (correction coefficients, threshold values, etc.) downstream.

[0035] The memory (220) can store program code and operational parameters, etc. Operational parameters may include critical temperature, correction coefficients (humidity / flow rate) required for TTF calculation, weights for risk calculation, risk level criteria, etc. The risk level criteria may be implemented as a lookup table (mapping multiple score intervals and multiple risk levels) or calculation rules (critical comparison, interval determination, application of hysteresis upward / downward thresholds, state transition rules, time duration conditions, etc.).

[0036] The processor (230) can load and execute multiple instructions (program code) stored in memory (220). Accordingly, the processor (230) can perform the following operations.

[0037] That is, the processor (230) can calculate the time remaining until freezing by considering the current temperature of the water meter (120) and the temperature change trend of the recent section, and estimate the final Time-to-Freeze (TTF) by applying humidity / flow rate correction. The processor (230) can calculate the risk of freezing of the water meter (120) based on the estimated TTF and determine the risk level based thereon. The processor (230) can generate and transmit a control signal that adjusts the communication cycle of the water meter (120) in stages according to the determined risk level, and can generate notifications such as a control system, mobile app, or text message as needed.

[0038] In embodiments of the present invention, the communication period refers to an uplink transmission interval in which a water meter (120) or a communication terminal (110) connected thereto periodically reports measurement data (including risk alert data) to a server (140).

[0039] FIGS. 3 to 6 are flowcharts illustrating a communication cycle control method based on the prediction of freezing risk of a water meter according to an embodiment of the present invention.

[0040] First, referring to FIGS. 1 and FIGS. 3, in step (310), the server (140) can estimate the time remaining until the water meter (120) freezes based on at least one of the data of the temperature, humidity, and flow rate of the water meter (120).

[0041] In this regard, the following is a detailed explanation with reference to Fig. 4.

[0042] First, in step (410), the server (140) can calculate the initial TTF using the current temperature of the water meter and the rate of change of temperature over a certain period of time based on the current temperature. Specifically, the server (140) can collect temperature time series periodically collected from each water meter (120) through the communication network (130). The collected data can be preprocessed by first aligning the time, removing outliers (replacing sensor spikes / missing values), and applying a low-pass weighted moving average (EWMA, etc.), through which the server (140) can stably extract the short-term cooling trend. After preprocessing, the server (140) can calculate the average cooling rate in the recent observation interval (e.g., a variable window of 10 to 30 minutes) and calculate the initial TTF (estimated time required until freezing when the current trend is maintained) by considering the temperature difference between the current meter temperature and the freezing standard (e.g., near 0℃).

[0043] At this time, when the cooling rate approaches nearly zero (sensor stagnation period, heating period, etc.), the server (140) sets a minimum resolution threshold to prevent the denominator from converging to zero, and in this case, the initial TTF can be saturated to a sufficiently large value (e.g., several hours or more) to prevent an over-alarm. For example, if the temperature has dropped from -2.0℃ to -3.0℃ (average -3℃ / h) in the recent 20-minute window and the current temperature is -3.0℃, the server (140) can calculate the initial TTF at the 60-minute level.

[0044] Subsequently, in step (420), the server (140) can calculate the humidity correction value of the water meter (120) using a pre-learned humidity correction coefficient. Specifically, the server (140) can calculate the humidity correction value corresponding to the relative humidity reported by the water meter (120) by querying a humidity correction mapping / model (e.g., parameters learned by region / season) stored in memory. In other words, the server (140) can calculate the humidity correction value by applying a correction that shortens the initial TTF, reflecting that freezing progress may accelerate as humidity increases.

[0045] At this time, the server (140) may set upper and lower clamping (e.g., range of -20 to 0%) as boundary conditions so that the correction value does not become excessive in the ultra-low humidity / ultra-high humidity range, and if humidity data is lost, the humidity correction value may be calculated by applying a neutral or weak shortening correction in a conservative (risk-upward) direction. For example, if the correction rate set in the 80% relative humidity range is -10%, the server (140) may calculate the initial TTF of 60 minutes as 54 minutes with humidity correction.

[0046] Subsequently, in step (430), the server (140) can calculate the flow rate correction value of the water meter (120) using a pre-learned flow rate correction coefficient. That is, the server (140) checks the flow rate value / existence of the flow rate of the water meter (120) and can calculate the flow rate correction value by referring to a pre-defined reference flow rate (Q_ref) or a learned normalization rule. Since the more water flow there is, the more heat is transferred and circulated, and the more likely it is that the time until freezing will be delayed, the server (140) can correct in a direction that increases the initial TTF as the flow rate increases.

[0047] At this time, the server (140) limits the correction effect or considers it as zero when the flow rate is zero or very small compared to the reference, and conversely, when a continuous flow rate is detected, sets an upper limit for the correction but increases it stepwise (by section) to be insensitive to sudden changes. In addition, the server (140) may assign a value equivalent to a correction value of zero by assuming no flow rate (conservatively) in the event of a flow rate sensor error or loss. For example, in an environment where the average flow rate is 6 L / min and Q_ref is 5 L / min, if the correction is +15% according to the set rule, the server (140) can correct the value from 54 minutes after humidity correction to 62 minutes through flow rate correction.

[0048] Subsequently, in step (440), the server (140) can estimate the final TTF using the initial TTF, humidity correction value, and flow rate correction value. That is, the server (140) can calculate the final TTF by combining the humidity correction value of step (420) and the flow rate correction value of step (430) with respect to the initial TTF. Subsequently, for operational stability, the following can be performed.

[0049] The server (140) can clip the final TTF to the system operating range (e.g., minimum 0 minutes to maximum 24 hours) for saturation processing. Additionally, the server (140) can label the correction status of input missing values / outliers, the size of the correction amount, etc., as metadata, and use this for weight adjustment / remuneration judgment in the subsequent risk index calculation step. Additionally, if the final TTF falls below the operating standard (e.g., 30 minutes or less), the server (140) can trigger an immediate notification in parallel with the risk index calculation and risk level determination.

[0050] For example, if the initial TTF is 60 minutes, the server (140) can correct the initial TTF to 54 minutes with a humidity correction (-10%), and then correct the initial TTF again to 62 minutes with a flow rate correction (+15%). In this way, the server (140) can estimate the final TTF to be 62 minutes (label: normal / valid). This value can be used as an input for subsequent steps (calculation of freeze risk index, level determination, communication cycle adjustment).

[0051] Next, referring again to FIGS. 1 and FIGS. 3, in step (320), the server (140) can calculate a freezing risk index using the estimated TTF, the low temperature duration representing the cumulative time the water meter (120) stayed below the critical temperature, and the flow rate status of the water meter (120).

[0052] In this regard, the following is a detailed explanation with reference to Fig. 5.

[0053] First, in step (510), the server (140) may assign a predetermined threshold value to each of the items of TTF, low temperature duration, and flow rate status. That is, the server (140) may assign a predetermined judgment criterion to each of the items of TTF, low temperature duration, and flow rate status. The judgment criterion may be defined as a threshold value, an interval boundary value, or a corresponding calculation rule, and may be set differently or remotely updated depending on the region, season, and installation environment.

[0054] For example, the server (140) can set the range so that the shorter the remaining time for the TTF, the higher the risk range is mapped, and for the low temperature duration, the longer the accumulated time, the higher the risk range is mapped, and for the flow rate status, the risk is increased when there is no flow and the risk is mitigated when there is continuous flow.

[0055] Subsequently, in step (520), the server (140) can compare each item with a corresponding threshold. In other words, the server (140) can compare the actual value of each item (e.g., final TTF, accumulated time of residence below the threshold temperature, flow rate value, or presence of flow rate) with the judgment criteria assigned in step (510). If the data is determined to be missing or erroneous, the server (140) can assign a quality flag or process it as a risk increase.

[0056] Subsequently, in step (530), the server (140) can determine the relative risk level for each item within a preset standard range based on the comparison results. That is, the server (140) can determine the relative risk level of each item within a preset common scale (e.g., range of 0 to 1) based on the comparison results. At this time, the server (140) normalizes the items to '0=safe, 1=dangerous' to ensure consistency in directionality between items, and may include interval linear relaxation, deadbands, or time duration conditions to prevent frequent reversals near the boundaries.

[0057] Subsequently, in step (540), the server (140) can calculate a freezing risk index by weighting the relative risk for each item. That is, the server (140) can calculate a freezing risk index by weighting the relative risk for each item determined above. Here, weighted sum refers to an operation of summing the items by multiplying each item by a pre-set weight. For example, it refers to the result of adding the first value and the second value after multiplying them by a coefficient that reflects their respective importance.

[0058] At this time, weights are pre-set based on the importance of TTF, low temperature duration, and flow rate status, and can be updated during operation. The calculated freeze risk index is clipped to a defined range and can be used as input for the next steps, which are determining the risk level and adjusting the communication cycle (server transmission cycle).

[0059] For example, if the final TTF is around 60 minutes (boundary range), the low temperature duration is 180 minutes, and the flow rate is determined to be 0, the server (140) can determine the relative risk for the TTF to be above average, the relative risk for the low temperature duration to be above average, and the relative risk for the flow rate condition to be high. Subsequently, the server (140) can calculate a freezing risk index as a result of weighted summing the relative risks of each item.

[0060] Next, referring again to FIGS. 1 and FIGS. 3, in step (330), the server (140) can determine a risk level corresponding to the calculated freezing risk index.

[0061] In this regard, the following is a detailed explanation with reference to Fig. 6.

[0062] First, in step (610), the server (140) can pre-set multiple score ranges. That is, the server (140) can pre-set the value range of the freeze risk index into multiple score ranges. For example, the server (140) can divide the freeze risk index range of 0.0 to 1.0 into five ranges (0.00 to 0.20, 0.20 to 0.40, 0.40 to 0.60, 0.60 to 0.80, 0.80 to 1.00). The number, boundary values, or width of the score ranges may be defined differently depending on the system operation policy. That is, during the cold season, the width of the upper ranges may be narrowed (e.g., 0.70 to 0.80, 0.80 to 1.00) to increase sensitivity. Meanwhile, the score ranges may be remotely updated in response to the season, region, installation environment, etc. For example, in coastal area profiles, when the influence of wind speed and humidity is found to be significant, the upper section entry boundary can be adjusted from 0.75 to 0.70.

[0063] Subsequently, in step (620), the server (140) can generate a lookup table that maps each of a plurality of risk levels representing the degree of risk for each preset score range. For example, when generating the lookup table, the server (140) can map the score range of 0.00 to 0.20 to Level 1, the score range of 0.20 to 0.40 to Level 2, the score range of 0.40 to 0.60 to Level 3, the score range of 0.60 to 0.80 to Level 4, and the score range of 0.80 to 1.00 to Level 5.

[0064] Here, the lookup table may be configured to include a level identifier (e.g., levels 1 to 5) corresponding to each score range. Additionally, the lookup table may include a version identifier for ease of management. For example, if the level identifier is level 5, the server (140) may store the version identifier and the policy code together to be linked with the 'immediate alert / cycle reduction' policy. At this time, the server (140) may operate different lookup tables for each region in parallel by assigning a version name such as 'FRI_LUT_v3.2'.

[0065] Subsequently, in step (630), the server (140) can store the generated lookup table in memory (see 220 in FIG. 2). At this time, the server (140) can minimize delay by loading the lookup table into the parameter table of the operation DB or into an in-memory cache. Here, minimizing delay means reducing parameter lookup delays and operation delays, and consequently shortening the internal processing time until the issuance of the control signal.

[0066] Afterward, in step (640), the server (140) can determine a risk level corresponding to the freezing risk index by referring to a lookup table stored in memory. For example, when a freezing risk index of 0.67 is input, the server (140) can determine the risk level to be 4 according to the lookup table mapping.

[0067] According to another embodiment, the server (140) can determine a risk level corresponding to the freezing risk index by referring to calculation rules (threshold comparison, interval judgment, state transition rule, time duration condition, etc.) corresponding to the lookup table. For example, the server (140) can produce the same result without a lookup table using threshold comparison rules such as "if R≥0.80 -> L=5; else if 0.60≤R<0.80 -> L=4; ...". Here, the calculation rules may be defined to provide judgment results equivalent to those of the lookup table. To this end, the server (140) may operate a test set such that the agreement rate between the rule-based judgment and the lookup table-based judgment results is 99% or higher.

[0068] Meanwhile, the server (140) can determine a risk level corresponding to the freezing risk index by applying a hysteresis transfer rule to the freezing risk index.

[0069] Specifically, the server (140) may maintain a state value representing a previously determined and stored risk level. As an example, the server (140) may maintain a state variable "L_prev=3" indicating that the previous state value was stored as a risk level of 3.

[0070] Next, the server (140) may refer to a hysteresis transition rule in which the upward transition threshold and the downward transition threshold are set differently for each boundary of adjacent risk levels. For example, the server (140) may set the upward transition threshold to 0.77 and the downward transition threshold to 0.73 at the boundary between risk levels 3 and 4, and may refer to a hysteresis transition rule that applies this.

[0071] Next, the server (140) can determine the risk level by transitioning to an upper risk level if the newly calculated freezing risk index is greater than or equal to the upward transition threshold value of the boundary, transitioning to a lower risk level if it is less than or equal to the downward transition threshold value, and maintaining the state value without changing it in the interval between the upward transition threshold value and the downward transition threshold value.

[0072] For example, if the total score R corresponding to the freezing risk index is 0.79 and the previous state value is stored as a risk level 3 (L_prev=3), the server (140) can transition the risk level to 4, and if the total score R is 0.72 and the state value is stored as a risk level 4 (L_prev=4), the server can transition the risk level downward to 3. Additionally, if the total score R is 0.75 and the state value is stored as a risk level 4 (L_prev=4), the server (140) can maintain the risk level at 4 (restriction on round-trip transition).

[0073] If necessary, the server (140) may impose restrictions on saturation operations at the highest / lowest level or on transitions only to adjacent levels. For example, the server (140) may not allow further upward transitions at risk level 5 (saturation) and may prohibit direct transitions from risk level 3 to level 5.

[0074] Next, referring again to FIGS. 1 and FIGS. 3, in step (340), the server (140) can transmit a control signal to the water meter (120) for adjusting the communication cycle of the water meter (120) based on the determined risk level.

[0075] That is, the server (140) can generate a control signal to adjust the communication cycle of the water meter (120) differently based on a determined risk level and transmit the generated control signal to the water meter (120). At this time, the server (140) can generate a control signal to adjust the communication cycle to be shorter or longer than the basic transmission cycle according to the determined risk level, based on a preset basic transmission cycle.

[0076] For example, in an environment where the basic transmission cycle is set to 6 hours, the server (140) can generate a control signal to maintain 6 hours for risk levels 1 to 3, 3 hours for risk level 4, and 1 hour for risk level 5, and transmit this to the water meter (120). Meanwhile, the server (140) may also set it to extend to 8 hours for risk levels 1 to 2 to save battery power as needed.

[0077] Meanwhile, the server (140) can verify the application of the control signal with an acknowledgment (ACK). That is, if the server (140) does not receive an ACK for the control signal from the water meter (120) or if the received ACK is determined to be an error, the server (140) can transmit the control signal to the water meter (120) so that the communication cycle automatically returns to a preset basic transmission cycle.

[0078] That is, if the ACK does not arrive for a predetermined waiting time after the server (140) transmits a control signal, it may perform retransmission up to N times. If the retry fails, the server (140) can ensure operational stability by sending down a command to return to the default cycle (e.g., 6 hours). For example, if the ACK is missed due to link quality degradation immediately after sending a command to shorten the communication cycle to risk level 5, the server (140) transmits a control signal including a command to return to the default to the water meter (120), and later, when the link stabilizes, the command to shorten the communication cycle can be reapplied according to the level determination.

[0079] In addition, the server (140) can trigger a notification policy in parallel with the adjustment of the communication cycle. For example, when the server (140) determines a risk level of 5, it can transmit a high-risk notification signal to a control system or mobile app simultaneously with the control of shortening the communication cycle.

[0080] FIG. 7 is a diagram exemplifying the communication cycle of risk levels according to the freezing risk index of a water meter in one embodiment of the present invention.

[0081] In this embodiment, the server (140) can determine the risk level according to the criteria (lookup table or calculation rule) of FIG. 6 by referring to the freeze risk index (total score R) calculated through the procedure of FIG. 5, and can adjust the communication cycle of the water meter in conjunction with the determined risk level.

[0082] Referring to Figure 7, when R ≤ 0.10, the risk level is classified as Level 1 (very safe), and a communication cycle of 6 hours may be applied. When 0.10 < R ≤ 0.30, the risk level is classified as Level 2 (safe), and a communication cycle of 6 hours may be applied. When 0.30 < R ≤ 0.75, the risk level is classified as Level 3 (caution), and a communication cycle of 6 hours may be applied. As such, when the risk level is Level 1 to Level 3, the communication cycle of 6 hours may be applied equally.

[0083] However, if the risk level is higher than the previous stage, the communication cycle may be shortened. That is, if 0.75 < R ≤ 0.90, the risk level is classified as stage 4 (Caution) and a communication cycle of 3 hours may be applied, and if R > 0.90, the risk level is classified as stage 5 (Danger) and a communication cycle of 1 hour may be applied.

[0084] The mapping between the total score R range, risk level, and communication cycle described above is exemplary; in actual operation, the interval boundary values, number of levels, and communication cycle may be set differently depending on the region, season, installation environment, or operator policy. For instance, in a cold weather operation profile, the Level 4 entry boundary may be lowered to 0.70 to increase alarm sensitivity, or the Level 2 transmission cycle may be extended to 8 hours according to a battery saving policy. These policies can be applied remotely through version updates of the lookup table or calculation rule updates.

[0085] According to one embodiment, the values ​​of FIG. 7 can be used with hysteresis operation. That is, by setting the upward transition criteria and the downward transition criteria differently for the interval boundaries of FIG. 7 (e.g., the upward criteria of 0.77 and the downward criteria of 0.73 for the 3-4 step boundary), frequent step roundabouts near the boundary can be suppressed. In this case, the server (140) maintains the previously stored state value (previous risk level), transitions to an upper step if the newly calculated R is above the upward criteria, transitions to a lower step if it is below the downward criteria, and maintains the current step in the interval between them.

[0086] According to another embodiment, the mapping of FIG. 7 may be implemented as a lookup table stored in the memory of the server (140) or as a corresponding calculation rule (threshold comparison, interval determination, state transition rule, etc.). By loading the lookup table / calculation rule into memory, the server (140) eliminates parameter lookup delays caused by accessing an external storage device or a remote database, and minimizes computational delays through constant time determination based on table indexing, thereby shortening the internal processing time from the calculation of the freezing risk index to the generation and transmission of a control signal for adjusting the communication cycle.

[0087] According to the mapping policy of Fig. 7 as described above, in low-risk stages (stages 1 to 3), the communication cycle is extended to reduce battery consumption and network load, and in high-risk stages (stages 4 to 5), the communication cycle is shortened to enable early detection of dangerous situations and rapid response.

[0088] The device (unit) described above may be implemented as a hardware element and / or a software element. For example, the hardware element may include a microphone, an amplifier, a bandpass filter, an A / D converter, and a processing device. The processing device may be implemented using one or more general-purpose or special-purpose computers, such as a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable gate array (FPGA), a programmable logic unit (PLU), a microprocessor, or other devices capable of responding to and executing instructions in a defined manner. The processing device may operate an operating system (OS) and one or more software applications running on the operating system. Additionally, the processing device may access, store, manipulate, process, and generate data in response to the execution of the software. For the sake of brevity, the processing unit may be described as a single unit; however, those skilled in the art will understand that the processing unit may include multiple processing elements and / or multiple types of processing elements. For example, the processing unit may include multiple processors or a processor and a controller. Additionally, other processing configurations, such as parallel processors, are also possible.

[0089] Software, including computer programs, code, instructions, or combinations thereof, may configure or command a processing unit independently or collectively to operate as desired. Software and data may be embodied permanently or temporarily as propagated signal waves that can be interpreted by the processing unit or provide instructions or data to the processing unit, or as various types of machines, components, physical devices, virtual equipment, computer storage media or devices, etc. Software may be distributed over networked computer systems and may be stored and executed in a distributed manner. Software and data may be stored on one or more computer-readable recording media, which include data storage devices that store data and allow the computer system or processing unit to read it later. The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded on a computer-readable medium. Examples of computer-readable recording media include ROM, RAM, CD-ROM, magnetic tape, floppy disk, and optical data storage devices. It includes magnetic media such as hard disks, floppy disks, and magnetic tapes, optical media such as CD-ROMs and DVDs, magneto-optical media such as floptical disks, and hardware devices specifically configured to store and execute program instructions such as ROM, RAM, and flash memory.In addition, functional programs, code, and code segments that fulfill the examples disclosed herein can be easily understood and implemented by a programmer with ordinary knowledge in the technical field related to these examples based on or using the flowcharts and block diagrams of the drawings and the descriptions provided herein.

[0090] Although various embodiments have been described above, it should be understood that various modifications are possible. For example, suitable results may be achieved even if the described techniques are performed in a different order, and / or the elements of the described system, structure, device, circuit, etc. are combined in a different way, or are replaced or supplemented by other elements or equivalents. Accordingly, other embodiments fall within the scope of the claims set forth below. Explanation of the symbols

[0091] 110: Communication terminal 120: Water meter 130: Communication network 140: Server 210: Communication module 220: Memory 230: Processor

Claims

Claim 1 A method for predicting the risk of freezing of a water meter and controlling the communication cycle of the water meter based thereon, using a server configured to communicate with the water meter through a communication network, comprising: a step of estimating a Time-to-Freeze (TTF) representing the time remaining until the water meter freezes based on at least one of the temperature, humidity, and flow rate of the water meter; a step of calculating a freezing risk index using the estimated TTF, a low-temperature duration representing the cumulative time the water meter has remained below a critical temperature, and the flow rate status of the water meter; and a step of transmitting a control signal to the water meter for adjusting the communication cycle of the water meter based on the calculated freezing risk index, wherein the step of estimating the TTF includes: a step of calculating an initial TTF using the current temperature of the water meter and the rate of change of temperature over a certain period based on the current temperature; a step of calculating a humidity correction value of the water meter using a pre-learned humidity correction coefficient; and a step of calculating a flow rate correction value of the water meter using a pre-learned flow rate correction coefficient. A method for controlling the communication cycle based on the prediction of freezing risk of a water meter, comprising the step of estimating a final TTF using the initial TTF, the humidity correction value, and the flow rate correction value. Claim 2 delete Claim 3 A method for controlling the communication cycle of a water meter based on the prediction of the risk of freezing, using a server configured to communicate with the water meter through a communication network, comprising: a step of estimating a Time-to-Freeze (TTF) representing the time remaining until the water meter freezes based on at least one of the temperature, humidity, and flow rate of the water meter; a step of calculating a freezing risk index using the estimated TTF, a low-temperature duration representing the cumulative time the water meter has remained below a critical temperature, and the flow rate status of the water meter; and a step of transmitting a control signal to the water meter for adjusting the communication cycle of the water meter based on the calculated freezing risk index, wherein the step of calculating the freezing risk index comprises: a step of converting each of the TTF, the low-temperature duration, and the flow rate status into a relative risk within a preset reference range; and a step of calculating the freezing risk index by weighting the relative risk for each of the items. Claim 4 A method for controlling a communication cycle based on the prediction of freezing risk of a water meter, wherein the step of converting to a relative risk level comprises: a step of assigning a predetermined threshold value to each of the items; a step of comparing each of the items with the corresponding threshold value; and a step of determining the relative risk level for each of the items within the standard range based on the result of the comparison. Claim 5 A method for controlling the communication cycle of a water meter based on the prediction of the risk of freezing of the water meter, using a server configured to communicate with the water meter through a communication network, comprising: a step of estimating a Time-to-Freeze (TTF) representing the time remaining until the water meter freezes based on at least one of the temperature, humidity, and flow rate of the water meter; a step of calculating a freezing risk index using the estimated TTF, a low-temperature duration representing the cumulative time the water meter has remained below a critical temperature, and the flow rate status of the water meter; a step of transmitting a control signal to the water meter for adjusting the communication cycle of the water meter based on the calculated freezing risk index; and a step of determining a risk level corresponding to the freezing risk index according to a predetermined standard, wherein the step of transmitting the control signal to the water meter includes: a step of generating the control signal to adjust the communication cycle differently based on the determined risk level; and a step of transmitting the generated control signal to the water meter. Claim 6 A method for controlling a communication cycle based on the prediction of freezing risk of a water meter, wherein, in claim 5, the step of determining the risk level includes the step of determining a risk level corresponding to the freezing risk index by referring to a lookup table stored in memory or a corresponding calculation rule. Claim 7 A method for controlling a communication cycle based on the prediction of freezing risk of a water meter, wherein the step of determining the risk level further includes the step of storing in the memory a lookup table that maps each of a plurality of risk levels representing the degree of risk for each of a plurality of preset score intervals. Claim 8 In claim 6, the step of determining the risk level comprises: a step of determining a risk level corresponding to the freeze risk index by applying a hysteresis transition rule to the freeze risk index, and maintaining a state value representing a previously determined and stored risk level; a step of referring to the hysteresis transition rule in which an upward transition reference value and a downward transition reference value are set differently for each boundary of adjacent risk levels; and a step of determining the risk level such that if the newly calculated freeze risk index is greater than or equal to the upward transition reference value of the corresponding boundary, it transitions to an upper risk level, and if it is less than or equal to the downward transition reference value, it transitions to a lower risk level, and in the interval between the upward transition reference value and the downward transition reference value, the state value is maintained without changing. This describes a method for controlling a communication cycle based on a freeze risk prediction of a water meter. Claim 9 A method for controlling a communication cycle based on a risk of freezing of a water meter, wherein, in claim 5, the step of generating the control signal comprises the step of generating the control signal to adjust the communication cycle to be shorter or longer than the basic transmission cycle according to the determined risk level based on a preset basic transmission cycle. Claim 10 A method for controlling a communication cycle of a water meter based on a prediction of the risk of freezing of the water meter using a server configured to communicate with the water meter through a communication network, comprising: a step of estimating a Time-to-Freeze (TTF) representing the time remaining until the water meter freezes based on at least one data of the temperature, humidity, and flow rate of the water meter; a step of calculating a freezing risk index using the estimated TTF, a low-temperature duration representing the cumulative time the water meter has remained below a critical temperature, and the flow rate status of the water meter; and a step of transmitting a control signal to the water meter to adjust the communication cycle of the water meter based on the calculated freezing risk index, wherein the step of transmitting the control signal to the water meter includes a step of transmitting the control signal to the water meter such that, if an acknowledgment (ACK) for the control signal is not received from the water meter or if there is an error in the acknowledgment, the communication cycle automatically returns to a preset basic transmission cycle. Claim 11 A server configured to communicate with a water meter through a communication network, predicts freezing of the water meter, and controls the communication cycle of the water meter based on this, wherein the server comprises: memory; A server comprising a processor that loads and executes a plurality of instructions stored in the memory, wherein the processor estimates a Time-to-Flash (TTF) representing the time remaining until the water meter freezes based on at least one of the temperature, humidity, and flow rate of the water meter, calculates a freezing risk index using the estimated TTF, a low-temperature duration representing the cumulative time the water meter remains below a critical temperature, and the flow rate status of the water meter, and transmits a control signal to the water meter for adjusting the communication cycle of the water meter based on the calculated freezing risk index, wherein the processor calculates an initial TTF using the current temperature of the water meter and the rate of change of temperature over a certain period based on the current temperature, calculates a humidity correction value of the water meter using a pre-learned humidity correction coefficient, calculates a flow rate correction value of the water meter using a pre-learned flow rate correction coefficient, and estimates a final TTF using the initial TTF, the humidity correction value, and the flow rate correction value. Claim 12 A server configured to communicate with a water meter through a communication network, and predicts freezing of the water meter and controls the communication cycle of the water meter based thereon, wherein the server comprises: a memory; and a processor that loads and executes a plurality of instructions stored in the memory, wherein the processor estimates a Time-to-Fast (TTF) representing the time remaining until the water meter freezes based on at least one of the temperature, humidity, and flow rate of the water meter, calculates a freezing risk index using the estimated TTF, a low-temperature duration representing the cumulative time the water meter remains below a critical temperature, and the flow rate status of the water meter, and transmits a control signal to the water meter for adjusting the communication cycle of the water meter based on the calculated freezing risk index, wherein the processor converts each of the TTF, the low-temperature duration, and the flow rate status into a relative risk within a preset standard range, and calculates the freezing risk index by weighting the relative risk for each of the items.

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