Method and system for hydrological and meteorological data transmission based on the Internet of Things

Abstract

The present invention relates to the field of wireless communication networks, and in particular to a method and system for transmitting hydrological and meteorological data based on the Internet of Things, the method comprising: obtaining water level data; determining a first quantized value of each position according to the water level data; determining the flood resistance of a position according to a first difference between water level data at adjacent moments, a first time interval between adjacent moments, a second difference between water level data at adjacent moments of a previous position, and a third difference between water level data at adjacent moments of a next position; determining predicted water level data at the recording moment according to the water level data at the current moment, the second time interval, and the first slope average value; determining the possibility of a flood disaster occurring at the position at the recording moment according to the first quantized value, the flood resistance of the position, and the predicted water level data; and transmitting the possibility of each position as hydrological and meteorological data. In this way, the present invention improves the accuracy and timeliness of early warning of flood disasters.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication networks, and in particular to a hydrological and meteorological data transmission method and system based on the Internet of Things. Background Art

[0002] Heavy rain and floods refer to floods caused by excessive rainfall in a short period of time, which causes rivers, lakes and other water bodies to exceed their carrying capacity. The hydrological effects brought by heavy rains are becoming more and more significant, including changes such as an increase in the total amount of floods and a shortening of flood confluence time. These changes have brought challenges to traditional methods of predicting heavy rain and flood disasters.

[0003] At present, the main method is to set up base stations in the water flow area to monitor the changes in the water level line of the water flow in real time, and send out a signal to transmit the alarm of possible flood disasters at that location after the water level line exceeds the set threshold. This method relies on the setting of static thresholds. Although it can provide early warning information in some scenarios, it cannot be applied to other scenarios. For example, in different geographical environments and sudden heavy rain events, the same water level change may have different risk levels. The static threshold may not be applicable to different geographical environments, and heavy rain may not be able to measure the water level line in time. Therefore, the existing method of using early warning for rainstorm and flood disasters has low accuracy and low timeliness, resulting in problems of misjudgment and untimely warning. Summary of the invention

[0004] In order to solve the technical problems of low accuracy and low timeliness in early warning of rainstorm and flood disasters, the purpose of the present invention is to provide a method and system for transmitting hydrological and meteorological data based on the Internet of Things. The technical solutions adopted are as follows:

[0005] An embodiment of the present invention provides a method for transmitting hydrological and meteorological data based on the Internet of Things, including: obtaining water level data at different moments at different positions of a river along a water flow direction; determining a first quantified value of each position according to the water level data, the first quantified value representing the growth amplitude of the water level at the position; determining the flood resistance of the position according to a first difference between water level data at adjacent moments of the position, a first time interval between the adjacent moments, a second difference between water level data at adjacent moments of the previous position of the position, and a third difference between water level data at adjacent moments of the next position of the position; determining predicted water level data at the recording moment according to the water level data at the current moment, a second time interval between a future recording moment and the current moment, and an average value of first slopes of all data points before the current moment; determining the possibility of a flood disaster occurring at the position at the recording moment according to the first quantified value, the flood resistance of the position, and the predicted water level data; and transmitting the possibility of each position as hydrological and meteorological data.

[0006] Optionally, determining the first quantitative value of each of the positions based on the water level line data includes: using the water level data of each of the positions at different times as the vertical coordinate, and using the time corresponding to the water level data of each of the positions as the horizontal coordinate to construct a rectangular coordinate system, and representing the data points of the water level data of each of the positions in the rectangular coordinate system; fitting the data points of each of the positions using the least squares method to obtain a curve of the water level data of each of the positions changing with time; determining a forecast time limit window, and determining the first quantitative value of the position based on the measurement interval time period of the forecast time limit window and the second slope average value of all data points in the forecast time limit window of the position.

[0007] Optionally, determining a forecast time limit window, and determining a first quantized value of the location based on a measurement interval time period of the forecast time limit window and a second slope average value of all data points within the forecast time limit window of the location includes: determining a first ratio between the second slope average value and the measurement interval time period as the first quantized value of the location.

[0008] Optionally, determining the flood resistance capacity of the location based on the first difference between the water level data at adjacent moments of the location, the first time interval between the adjacent moments, the second difference between the water level data at adjacent moments of the previous location of the location, and the third difference between the water level data at adjacent moments of the next location of the location includes: determining the second ratio between the first difference between the water level data at adjacent moments of the location and the first time interval between the adjacent moments as the water level growth rate of the location at each moment; determining the third ratio between the second difference and the first difference as the first influence degree of the location affected by the previous location, and determining the fourth ratio between the third difference and the first difference as the second influence degree of the location affected by the next location; calculating the first average influence degree of all first influence degrees, the second average influence degree of all second influence degrees, and the average water level growth rate of the water level growth rates of the location at all moments; determining the flood resistance capacity of the location based on the first average influence degree, the second average influence degree, and the average water level growth rate.

[0009] Optionally, determining the flood resistance capacity of the location based on the first average impact degree, the second average impact degree and the average water level growth rate includes: calculating a fourth difference between the first average impact degree and the second average impact degree, and a fifth ratio between the fourth difference and the average water level growth rate; and determining the absolute value of the fifth ratio as the flood resistance capacity of the location.

[0010] Optionally, determining the predicted water level data at the recording moment based on the water level data at the current moment, the second time interval between the future recording moment and the current moment, and the first slope average of all data points before the current moment includes: using the average rainfall at the location at the current moment to determine the second time interval between the recording moment of the next recording of the water level data and the current moment; calculating the first product between the first slope average and the second time interval; and determining the sum of the water level data at the current moment and the first product as the predicted water level data at the recording moment.

[0011] Optionally, using the average rainfall at the current moment of the location to determine the second time interval between the recording moment of the next water level line data and the current moment includes: calculating the inverse of the average rainfall at the current moment; selecting the minimum value from the inverse of the average rainfall and a predetermined parameter as the second time interval.

[0012] Optionally, determining the possibility of a flood disaster occurring at the location at the recording time based on the first quantized value, the flood resistance capacity of the location and the predicted water level line data includes: calculating a second product between the first quantized value and the predicted water level line data; and determining a sixth ratio between the second product and the flood resistance capacity of the location as the possibility of a flood disaster occurring at the location at the recording time.

[0013] Optionally, transmitting the possibility of each of the locations as hydrological and meteorological data includes: normalizing the possibility of flood disaster occurring at each of the locations at the recording time and then sorting them in descending order; determining the transmission priority of the possibility according to the sorting order; and transmitting the possibility as hydrological and meteorological data in sequence according to the transmission priority, wherein the higher the sorting position of the possibility is, the higher the transmission priority is.

[0014] In the second aspect, an embodiment of the present invention discloses a hydrological and meteorological data transmission system based on the Internet of Things, comprising: a processor and a memory; wherein the memory is used to store computer programs that can be run on the processor; the processor is used to execute the program stored in the memory to implement the steps of the hydrological and meteorological data transmission method based on the Internet of Things mentioned in the first aspect.

[0015] The present invention has the following beneficial effects: firstly, water level data at different moments of different positions of a river are obtained along the direction of water flow; then, a first quantitative value of each position is determined according to the water level data, the first quantitative value characterizing the growth amplitude of the water level at the position; then, the flood resistance capacity of the position is determined according to the first difference between the water level data at adjacent moments of the position, the first time interval between the adjacent moments, the second difference between the water level data at adjacent moments of the previous position of the position, and the third difference between the water level data at adjacent moments of the next position of the position; secondly, the predicted water level data at the recording moment is determined according to the water level data at the current moment, the second time interval between the future recording moment and the current moment, and the first slope average value of all data points before the current moment; and the possibility of flood disaster occurring at the position at the recording moment is determined according to the first quantitative value, the flood resistance capacity of the position, and the predicted water level data; finally, the possibility of each position is transmitted as hydrological and meteorological data.

[0016] In this way, the embodiment of the present invention can dynamically evaluate the predicted water level data of different locations in the river at future moments according to the changing trend of the water level at different locations, that is, dynamically evaluate the predicted water level data of different geographical environments in the river at different moments in the future, and dynamically evaluate the possibility of flood disasters in different locations at future moments according to the predicted water level data at different locations, the growth rate of the water level at different locations, and the flood resistance capacity at different locations. Finally, the possibility of flood disasters at various locations at a certain moment in the future is transmitted as hydrological and meteorological data. The technical solution provided by the embodiment of the present invention can cope with different geographical environments and sudden heavy rain events, thereby improving the accuracy and timeliness of flood disaster warnings. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 A flow chart of a hydrological and meteorological data transmission method based on the Internet of Things provided by an embodiment of the present invention;

[0019] Figure 2 A schematic diagram of marking each data point on a rectangular coordinate system provided by an embodiment of the present invention;

[0020] Figure 3 A schematic diagram of the structure of a hydrological and meteorological data transmission system based on the Internet of Things provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0021] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the specific implementation method, structure, features and effects of a hydrological and meteorological data transmission method based on the Internet of Things proposed by the present invention in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0022] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0023] The specific scheme of the hydrological and meteorological data transmission method based on the Internet of Things provided by the present invention is described in detail below with reference to the accompanying drawings.

[0024] Embodiment 1:

[0025] See also Figure 1 , which shows a flow chart of a hydrological and meteorological data transmission method based on the Internet of Things provided by an embodiment of the present invention, including:

[0026] Step S101, obtaining water level data at different positions of the river at different times along the water flow direction.

[0027] Specifically, in the embodiment of the present invention, base stations are established at appropriate locations on the edge of the river at intervals along the direction from upstream to downstream of the river according to the actual length of the river. The distance between adjacent locations can be determined according to actual conditions. In the embodiment of the present invention, a base station is set at a location about every 10 kilometers. Each base station includes a complete real-time water level monitoring system, which includes a water level detection instrument and a data transmission unit, etc., wherein the water level detection instrument transmits ultrasonic waves to the water surface and receives the reflected waves reflected by the water surface to calculate the round-trip time of the ultrasonic waves, accurately calculates the distance between the current water level and the water level detection instrument, and sets a unified reference elevation reference plane to monitor the water level height in real time. The fifth generation mobile communication technology (Fifth Generation Mobile Networks, 5G) is used to transmit data to each other between the base stations, and the data is centrally transmitted to the data processing center to perform calculation and evaluation operations on the water level line data measured by each base station.

[0028] More specifically, the time interval between different moments, that is, the time interval between data collection and transmission, is predetermined as The data collection and transmission are performed once, and the time interval for data collection and transmission is determined by taking the current rainfall as a reference. In the embodiment of the present invention, it is assumed that the average rainfall at the current location of each base station is , in millimeters per hour ),like , then update all monitoring systems to is the time interval between data collection and transmission, that is, the time interval between adjacent moments. It can be determined in actual application scenarios, and the value of this embodiment of the present invention is 0.5. The reason for using rainfall as a reference is that the greater the rainfall, the greater and faster the possibility of flood disasters, and a faster and more timely prediction of flood disasters is needed.

[0029] More specifically, a plurality of water level data sequences obtained by real-time monitoring at each monitoring station are transmitted to a data processing center, and the obtained water level data are calculated and evaluated. Base stations, each base station has been monitored The secondary water level data may be data obtained within the past day. The monitoring time may be customized by the user. In the embodiment of the present invention, the water level data sequence obtained by monitoring each base station is recorded as . represents the water level data sequence obtained by the i-th base station, Represents the j-th water level data monitored by the i-th base station.

[0030] Step S102: determining a first quantized value of each position according to the water level data.

[0031] The first quantitative value represents the growth amplitude of the water level at the location.

[0032] Specifically, the main cause of flood disasters caused by heavy rain is that it will cause the river water level to rise, causing the river to become turbulent and turbulent, overflowing the river bank and flooding roads and farmlands. Therefore, the increase in the water level of a certain section of the river is the most significant feature of the impending flood disaster. The water level data sequence of the river area where the base station is located For example, take the data values ​​of the water level data at different times is the ordinate value (in millimeters), and the recording time of each water level data is the abscissa value. The position of each water level data point is marked in the rectangular coordinate system. For the recording time corresponding to each water level data, it is assumed that the first water level data corresponding to the i-th base station The recorded time is the time When the j-th water level data corresponding to the i-th base station The average rainfall during the recording period is recorded as , then we can get the time interval from the water level data being recorded to the next water level data being recorded is .in, represents the time from the jth water level data of the i-th base station to the next water level data. Then the jth water level data corresponding to the i-th base station is The recording time (that is, the horizontal axis value) is (Unit time), represents the kth time interval of the i-th base station. Figure 2A schematic diagram of marking each data point on a rectangular coordinate system provided by an embodiment of the present invention. The marking of each data point on a rectangular coordinate system obtained by the embodiment of the present invention is as follows Figure 2 As shown, it is a scatter plot including multiple data points. The coordinate position of the water level data is ( , ).

[0033] More specifically, when determining the first quantized value of each position, as an optional embodiment of the present invention, firstly, the water level line data of each of the positions at different times are used as the vertical coordinate, and the time corresponding to the water level line data of each of the positions is used as the horizontal coordinate to construct a rectangular coordinate system, and the data points of the water level line data of each of the positions are represented in the rectangular coordinate system; then, the data points of each of the positions are fitted using the least squares method to obtain a curve of the water level line data of each of the positions changing with time; finally, the forecast time limit window is determined, and the first quantized value of the position is determined according to the measurement interval time period of the forecast time limit window and the second slope average value of all data points in the forecast time limit window of the position.

[0034] Specifically, each data point on the indicator coordinate system is fitted by the least squares method to obtain a curve of the water level line of the river area corresponding to the ith base station changing with time, so as to reflect the growth law of the water level line of the river area corresponding to the ith base station. Furthermore, the embodiment of the present invention sets a forecast time limit window, and the forecast time limit window covers a number of water level line data obtained from recent monitoring. The recent growth of the water level line of the river area corresponding to the ith base station can be evaluated based on the water level line data obtained from hydrological monitoring within the forecast time limit window, which serves as a reference for the estimation of subsequent prior values. The size of the forecast time limit window can be customized according to the actual application scenario. The embodiment of the present invention sets the size of the forecast time limit window to 10 data points. The embodiment of the present invention determines the time interval occupied by the data points in the forecast time limit window of the ith base station. Recorded as Further, according to the change curve of the water level data of the i-th base station over time, the slope of the location of a series of data points is obtained and recorded as , and the average slope value of all data points within the forecast time window is obtained and recorded as , which is the second slope average value in the above embodiment of the present invention.

[0035] More specifically, when determining the first quantized value of the position, as an optional embodiment of the present invention, a first ratio between the second slope average value and the measurement interval time period is determined as the first quantized value of the position.

[0036] Specifically, the embodiment of the present invention specifically uses the following formula to calculate the first quantization value:

[0037]

[0038] In the above formula, For the The first quantized value of the river area corresponding to the base station. For the The measurement interval of the data points in the forecast time window of the river area corresponding to the base station. The size of the measurement interval is inversely proportional to the rainfall in the measurement interval. The smaller the value, the greater the rainfall during this measurement interval. It is The average value of the second slope of all data points in the forecast time window on the curve of the change of the water level data of the river area corresponding to the base station over time indicates the change trend of the water level in the measurement interval time period. The larger the value, the higher the water level in the measurement interval time period. The greater the increase in the water level of the river area corresponding to the base station, the greater the increase in the water level of the river area corresponding to the base station. The value is comprehensive The growth of the water level in the river area corresponding to the base station. The larger the value, the higher the growth of the water level in the river area corresponding to the base station. The water level in the river area corresponding to each base station has increased rapidly and rapidly, and the precipitation is large, which can easily overflow the shore and cause floods.

[0039] Step S103, determines the flood resistance capacity of the location based on the first difference between the water level data at adjacent moments of the location, the first time interval between the adjacent moments, the second difference between the water level data at adjacent moments of the previous location of the location, and the third difference between the water level data at adjacent moments of the next location of the location.

[0040] Specifically, during heavy rain, the heavy rain will cause the water level of the entire river to rise to a certain extent. However, not only will the heavy rain cause changes in the water level, but the flow of the river itself will also cause different trends in the water level of different river areas. For example, if too much upstream river flows into the downstream area, the water level in the downstream area will surge. Therefore, it is necessary to judge the occurrence of flood disasters based on the water level fluctuation trend between the various areas of the entire river. The water level data sequence obtained from the monitoring of the i-th base station in the upstream to downstream direction of the river in the above embodiment of the present invention is .

[0041] First, for the river area corresponding to the i-th base station, the embodiment of the present invention evaluates the influence of the water level change in the upstream area of ​​the current river area on the water level of the current river area. First, the amount of the water level increase in the river area is obtained, that is, The difference sequence is obtained by performing difference calculation, that is, the sequence of the first difference values ​​between the water level data at each adjacent time. In the embodiment of the present invention, the difference sequence is recorded as , Indicates the first difference between the water level data of the i-th base station at adjacent moments. Represents the j+1th water level line data of the i-th base station. Represents the jth water level data of the ith base station. The water level difference sequence of the river area corresponding to other base stations is calculated in the same way and recorded as .

[0042] Secondly, for the upstream and downstream waters, rainwater entering the upstream area is more likely to flow into the downstream area along with the water flow. The relationship between the increase values ​​of the upstream and downstream water levels can be used to evaluate the impact of the change in the water level in the upstream area on the change in the water level in the downstream area. The difference sequence of the water level data of the river area corresponding to the base station and the difference sequence of the water level data of the upstream area form a two-tuple sequence corresponding to the base station position. , to Indicates The difference sequence of the river area corresponding to the previous base station of the river area corresponding to the base station, that is, the river area corresponding to the i-1th base station, to Indicates The difference sequence of the river area corresponding to the base station is then fitted by the least squares method to obtain the first The water level change of the river area corresponding to the upstream base station of the river area corresponding to the i-1th base station is related to the i-1th base station. The influence curve of the water level change in the river area corresponding to the base station Among them, the independent variable For this The water level change of the upstream base station of the river area corresponding to the base station, that is, the water level change of the river area corresponding to the i-1th base station, the dependent variable For this The influence curve of the river area corresponding to all base stations on the influence of its upstream area is obtained by the same method as the above embodiment of the present invention. .

[0043] Based on the above embodiments of the present invention, when determining the flood resistance capacity of the location of each base station, first determine the second ratio between the first difference between the water level data of adjacent moments of the location and the first time interval between the adjacent moments as the water level growth rate of the location at each moment; then determine the third ratio between the second difference and the first difference as the first influence degree of the location affected by the previous location, and determine the fourth ratio between the third difference and the first difference as the second influence degree of the location affected by the next location; then calculate the first average influence degree of all the first influence degrees, the second average influence degree of all the second influence degrees, and the average water level growth rate of the water level growth rate of the location at all moments; finally, determine the flood resistance capacity of the location based on the first average influence degree, the second average influence degree, and the average water level growth rate.

[0044] Specifically, in the embodiment of the present invention, the drainage capacity of the river areas corresponding to the base stations when the internal water volume increases, which can also be called flood resistance capacity, is different. The growth of its own water level line, the diversion of its upstream area to it, and its diversion to its downstream area will affect its own flood resistance capacity. Therefore, the embodiment of the present invention can judge the flood resistance capacity of the river area corresponding to each base station based on the growth rate of the water level line of the river area corresponding to each base station and the influence of its upstream and downstream. Among them, for the growth rate of the water level line of the river area of ​​the i-th base station, For a river area with a base station, according to the above embodiment of the present invention, The difference sequence of the first difference between the water level data of the river area of ​​the base stations and the first time interval between the recorded moments , the water level growth rate of the river area of ​​the i-th base station at each moment is recorded as , and further obtain the average water level growth rate of the river area of ​​the i-th base station at all times, recorded as , average water level growth rate It can be intuitively expressed that The water level growth rate of the river area of ​​the base station shows that Secondly, in the embodiment of the present invention, the influence curve of the upstream of the river area of ​​the ith base station on its water level is determined. And the influence curve of the river area of ​​the i-th base station on its downstream area The influence curve of its upstream on its water level line For example, one of the pairs The values ​​are The water level change value of a river area and its upstream area at a certain time, and the ratio of the two For this The river area of ​​the base station is affected by the first degree of its upstream, where the independent variable For this The water level change of the upstream base station of the river area corresponding to the base station, that is, the water level change of the river area corresponding to the i-1th base station, the dependent variable For this The water level changes of the river area corresponding to the base stations are used to obtain the first average impact degree of all the first impact degrees. Similarly, the influence curve of its downstream water level is For example, the average value of the fourth ratio between all the third differences and the first difference is the second average influence degree, which is recorded as Indicates The influence of the river area corresponding to each base station on its downstream.

[0045] Based on the above embodiments of the present invention, when determining the flood resistance capacity of the river area where each base station is located, as an optional embodiment of the present invention, the fourth difference between the first average impact degree and the second average impact degree, and the fifth ratio between the fourth difference and the average water level line growth rate are first calculated; then the absolute value of the fifth ratio is determined as the flood resistance capacity of the location.

[0046] Specifically, the embodiment of the present invention specifically uses the following formula to calculate the flood resistance capability:

[0047]

[0048] In the above formula, Indicates The flood resistance capacity of the river area corresponding to each base station. Indicates The second average impact degree of the river area corresponding to the base station on its downstream area. Indicates The first average degree of influence of the river area corresponding to the base station on its upstream area. The larger the value, the The river area corresponding to the base station has a higher degree of diversion to its downstream area and a lower degree of diversion to its upstream area, which indirectly indicates that the The slower the water level in the river area corresponding to each base station rises, the stronger the flood resistance capability is. The value is The average water level growth rate of the river area corresponding to the base station is intuitively shown. The water level rise rate of the river area corresponding to each base station. The smaller the value, the slower the water level rise rate and the stronger the flood resistance. The value indicates that The strength of the flood resistance capacity of the river area corresponding to each base station. The larger the value, the stronger the flood resistance capacity. Conversely, the easier it is to cause flood disasters.

[0049] Step S104, determining the predicted water level data at the recording moment according to the water level data at the current moment, the second time interval between the future recording moment and the current moment, and the first slope average value of all data points before the current moment.

[0050] Specifically, flood disasters caused by heavy rains are mainly caused by the rise of the water level of the river due to heavy rains. Therefore, the prediction of flood disasters is essentially the prediction of the water level of the river area where the base station is located. By predicting the possible value of the water level in the short term in the future, the possibility of flood disasters can be predicted. For the water level in the river area corresponding to a certain base station, high rainfall will directly cause it to increase, and the water flow in its upstream area will indirectly cause it to increase. Therefore, the change of the water level in each section of the river in the short term in the future can be comprehensively predicted based on the change trend of the water level within each section of the river area and the trend of the water level between it and its upstream, so as to predict the possibility of flood disasters. Among them, for the first For the river area corresponding to the base station, first obtain the The water level growth of the river area corresponding to the base station, that is, the first quantitative value This value is evaluated based on the changes in the intuitive water level in the area. The probability of flood disasters occurring in the river area corresponding to the base station is proportional to the probability of flood disasters occurring in the river area corresponding to the base station. However, it is too one-sided to predict flood disasters based on this value alone. The predicted water level of the river area corresponding to each base station can further predict the possibility of flood disasters.

[0051] More specifically, when determining the predicted water level line data at the recording moment, as an optional embodiment of the present invention, the second time interval between the recording moment of the next recording of the water level line data and the current moment is first determined using the average rainfall at the location at the current moment; then the first product between the first slope average value and the second time interval is calculated; finally, the sum of the water level line data at the current moment and the first product is determined as the predicted water level line data at the recording moment.

[0052] Specifically, when determining the second time interval, the inverse of the average rainfall at the current moment is first calculated; then the minimum value is selected from the inverse of the average rainfall and a predetermined parameter as the second time interval. , so that the second time interval between the next record and the current time is .in, is a predetermined parameter, which can be set according to the actual scenario. In the embodiment of the present invention, the value is 0.5. According to the change curve of the water level line over time in the above embodiment of the present invention, the first slope average value of all data points before the current moment is calculated. The embodiment of the present invention adopts the formula Calculate the predicted water level data for future recording times. Indicates The future of the river area corresponding to the base station Record the predicted water level data at the time, Indicates The current river area corresponding to the base station Water level data at a certain moment, Indicates The current river area corresponding to the base station The second time interval between a moment and the future moment, represents the first slope average. It is worth noting that in order to prevent If the denominator is 0 and cannot be calculated, you can add 1 to avoid it. .

[0053] Step S105 , determining the possibility of a flood disaster occurring at the location at the recording time according to the first quantized value, the flood resistance capability of the location, and the predicted water level data.

[0054] Specifically, the flood resistance capacity of the river area where each base station is located obtained by the above embodiment of the present invention is obtained, and the possibility of flood disasters occurring in the river area corresponding to each base station in the future is evaluated by combining the first quantitative value and the predicted water level line data. Among them, as an optional embodiment of the present invention, the second product between the first quantitative value and the predicted water level line data is first calculated; and then the sixth ratio between the second product and the flood resistance capacity of the location is determined as the possibility of flood disasters occurring in the location at the recording time.

[0055] Specifically, the embodiment of the present invention uses the following formula to calculate the possibility of flood disasters occurring at the location at a future time:

[0056]

[0057] In the above formula, Indicates The possibility of flood disasters occurring in the river area corresponding to each base station. Indicates The first quantized value of the river area corresponding to the base station indicates the The estimated growth rate of the water level line in the river area corresponding to the base station. The larger the value, the The faster the water level in the river area corresponding to a base station grows, the more likely it is to cause flood disasters. This is the The river area corresponding to each base station is determined by its own water level change law and the current rainfall. The predicted value of the next water level line in the river area corresponding to the base station represents the predicted water level line data for the next future moment. The larger the value, the higher the water level line. The higher the water level of the river area corresponding to the base station at a future moment, the more likely it is to cause flood disasters. This is the The smaller the value is, the faster the water level increases, and the more likely it is to cause flood disasters.

[0058] Step S106, transmitting the possibility of each of the locations as hydrological and meteorological data.

[0059] Specifically, the method in the above embodiment of the present invention is used to calculate the possibility of flood disasters occurring in the river area where each base station is located, and then the possibility of flood disasters occurring in the river area at each location is normalized to obtain , Express Perform normalization processing, Indicates The normalized value of the probability of flood disasters in the river area corresponding to the base station is output as and transmits it as hydrometeorological data.

[0060] More specifically, an embodiment of the present invention normalizes the possibility of flood disaster occurring at each location at the recording time and then sorts it in descending order; determines the transmission priority of the possibility according to the sorting order; and transmits the possibility as hydrological and meteorological data in sequence according to the transmission priority, wherein the higher the sorting position of the possibility, the higher the transmission priority.

[0061] Specifically, The values ​​are sorted from large to small, by The value of determines the importance of the data of the river area corresponding to each base station from high to low, and further determines the transmission priority. The larger the value is, the higher the transmission priority is, and it will be transmitted to the data processing center first, indicating that the river area corresponding to the base station has a higher probability of flood disaster.

[0062] Embodiment 2:

[0063] Corresponding to the hydrological and meteorological data transmission method based on the Internet of Things provided in the above embodiment, based on the same technical concept, an embodiment of the present invention further provides a hydrological and meteorological data transmission system based on the Internet of Things, which is used to execute the above hydrological and meteorological data transmission method based on the Internet of Things. Figure 3 A schematic diagram of a hydrological and meteorological data transmission system based on the Internet of Things is provided to implement various embodiments of the present invention. Figure 3 As shown in the hardware level, the hydrological and meteorological data transmission system based on the Internet of Things includes a processor, and optionally, an internal bus, a network interface, and a memory. Among them, the memory may include a memory, such as a high-speed random access memory (RAM), and may also include a non-volatile memory (non-volatile memory), such as at least one disk storage, etc. Of course, the hydrological and meteorological data transmission system based on the Internet of Things may also include hardware required for other services.

[0064] The processor, network interface and memory can be interconnected through an internal bus, which can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one bidirectional arrow is used in the figure, but it does not mean that there is only one bus or one type of bus.

[0065] The memory is used to store the program. Specifically, the program may include a program code, and the program code includes a computer operation command. The memory may include a memory and a non-volatile memory, and provides instructions and data to the processor.

[0066] The processor reads the corresponding computer program from the non-volatile memory into the memory and then runs it, forming a device for locating the specified user at the logical level. The processor executes the program stored in the memory and is specifically used to execute: Figure 3 The method disclosed in the illustrated embodiment realizes the functions and beneficial effects of each method described in the foregoing method embodiments, which will not be described in detail here.

[0067] It should be noted that the hydrological and meteorological data transmission system based on the Internet of Things provided in the embodiment of the present invention and the hydrological and meteorological data transmission method based on the Internet of Things provided in the embodiment of the present invention are based on the same application concept. Therefore, the specific implementation of this embodiment can refer to the implementation of the aforementioned hydrological and meteorological data transmission method based on the Internet of Things, and has the same or similar beneficial effects, and the repetitive parts will not be repeated.

[0068] It should be noted that the sequence of the above embodiments of the present invention is for description only and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0069] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. A method for transmitting hydrological and meteorological data based on the Internet of Things, characterized in that: The method for transmitting hydrological and meteorological data based on the Internet of Things includes: Acquire water level data at different locations of the river at different times along the direction of water flow; Determine a first quantitative value of each of the positions according to the water level data, wherein the first quantitative value represents a growth amplitude of the water level at the position; Determine the flood resistance capacity of the location according to a first difference between water level data at adjacent moments of the location, a first time interval between the adjacent moments, a second difference between water level data at adjacent moments of a previous location of the location, and a third difference between water level data at adjacent moments of a next location of the location, wherein the previous location is located upstream of the location and the next location is located downstream of the location; Determine the predicted water level data at the recording time according to the water level data at the current time, the second time interval between the future recording time and the current time, and the first slope average value of all data points before the current time; Determine the possibility of flood disaster occurring at the location at the recording time according to the first quantified value, the flood resistance capacity of the location and the predicted water level data; transmitting the probability for each of the said locations as hydrometeorological data; Determining the flood resilience of the location includes: Determine a second ratio between a first difference between water level data at adjacent moments of the location and a first time interval between the adjacent moments as a water level growth rate of the location at each moment; Determine a third ratio between the second difference and the first difference as a first degree of influence of the position on the previous position, and determine a fourth ratio between the third difference and the first difference as a second degree of influence of the position on the next position; Calculate a first average influence degree of all first influence degrees, a second average influence degree of all second influence degrees, and an average water level growth rate of the water level growth rates of the location at all times; The flood resistance capacity of the location is determined according to the first average impact degree, the second average impact degree and the average water level growth rate.

2. The method for transmitting hydrological and meteorological data based on the Internet of Things according to claim 1 is characterized in that: Determining the first quantized value of each position according to the water level data comprises: Using the water level data at different times of each of the positions as the ordinate and the time corresponding to the water level data at each of the positions as the abscissa to construct a rectangular coordinate system, and representing the data points of the water level data at each of the positions in the rectangular coordinate system; The data points at each of the positions are fitted using the least square method to obtain a curve of the water level data at each of the positions changing with time; A forecast time limit window is determined, and a first quantized value of the location is determined according to a measurement interval time period of the forecast time limit window and a second slope average value of all data points within the forecast time limit window of the location.

3. The method for transmitting hydrological and meteorological data based on the Internet of Things according to claim 2 is characterized in that: The step of determining a forecast time limit window and determining a first quantized value of the location according to a measurement interval of the forecast time limit window and a second slope average value of all data points within the forecast time limit window of the location includes: A first ratio between the second slope average value and the measurement interval time period is determined as a first quantified value of the position.

4. The method for transmitting hydrological and meteorological data based on the Internet of Things according to claim 1, characterized in that: Determining the flood resistance capacity of the location according to the first average impact degree, the second average impact degree, and the average water level growth rate includes: Calculating a fourth difference between the first average impact level and the second average impact level, and a fifth ratio between the fourth difference and the average water level growth rate; The absolute value of the fifth ratio is determined as the flood resistance of the location.

5. The method for transmitting hydrological and meteorological data based on the Internet of Things according to claim 1, characterized in that: Determining the predicted water level data at the recording time according to the water level data at the current time, the second time interval between the future recording time and the current time, and the first slope average value of all data points before the current time includes: Determine a second time interval between the time of recording the next water level line data and the current time by using the average rainfall at the location at the current time; calculating a first product between the first slope average and the second time interval; The sum of the water level data at the current moment and the first product is determined as the predicted water level data at the recording moment.

6. The method for transmitting hydrological and meteorological data based on the Internet of Things according to claim 5 is characterized in that: The method of determining the second time interval between the recording time of the next recording of water level data and the current time by using the average rainfall of the location at the current time comprises: Calculate the reciprocal of the average rainfall at the current moment; A minimum value is selected from the reciprocal of the average rainfall and a predetermined parameter as the second time interval.

7. The method for transmitting hydrological and meteorological data based on the Internet of Things according to claim 1, characterized in that: Determining the possibility of a flood disaster occurring at the location at the recording time according to the first quantized value, the flood resistance capacity of the location, and the predicted water level data includes: Calculating a second product between the first quantized value and the predicted water level line data; A sixth ratio between the second product and the flood resistance capacity of the location is determined as the possibility of a flood disaster occurring at the location at the recording time.

8. The method for transmitting hydrological and meteorological data based on the Internet of Things according to claim 1, characterized in that: The transmitting of the possibility of each of the locations as hydrometeorological data comprises: Normalizing the probability of flood disaster occurring at each location at the recording time and sorting them in descending order; Determining a transmission priority of the possibilities according to the sorting order; The possibilities are transmitted as hydrological and meteorological data in sequence according to the transmission priorities, wherein the higher the ranking position of the possibility is, the higher the transmission priority is.

9. A hydrological and meteorological data transmission system based on the Internet of Things, characterized in that: include: A processor and a memory; wherein the memory is used to store a computer program that can be run on the processor; The processor is used to execute the program stored in the memory to implement the steps of the hydrological and meteorological data transmission method based on the Internet of Things as described in any one of claims 1 to 8.

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