CN113834545A - Urban low-lying area water level early warning system based on electronic positioning system - Google Patents
Urban low-lying area water level early warning system based on electronic positioning system Download PDFInfo
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- CN113834545A CN113834545A CN202111023221.7A CN202111023221A CN113834545A CN 113834545 A CN113834545 A CN 113834545A CN 202111023221 A CN202111023221 A CN 202111023221A CN 113834545 A CN113834545 A CN 113834545A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01F—MEASURING VOLUME, VOLUME FLOW, MASS FLOW OR LIQUID LEVEL; METERING BY VOLUME
- G01F23/00—Indicating or measuring liquid level or level of fluent solid material, e.g. indicating in terms of volume or indicating by means of an alarm
- G01F23/0007—Indicating or measuring liquid level or level of fluent solid material, e.g. indicating in terms of volume or indicating by means of an alarm for discrete indicating and measuring
Abstract
The invention discloses an urban low-lying area water level early warning system based on an electronic positioning system, and belongs to the technical field of urban low-lying area water level early warning, disaster prevention and harm reduction. The water level early warning system comprises a field water level monitoring sensor, a General Packet Radio Service (GPRS) transmission network, a data processing center, a navigation system APP display terminal and a traffic warning electronic display screen. The water level monitoring sensor can collect water level data of a low-lying area site, the water level data is transmitted to the data processing center through GPRS (general packet radio service) in cooperation with site navigation data to be interactively verified and transmitted to the threshold configuration unit, and then the low-lying area water level early warning level is judged; and finally, the data processing center remotely transmits the water level early warning grade signal to a navigation system APP display terminal and a traffic warning electronic display screen terminal through GPRS, so that drivers and passengers are prompted to plan driving routes in advance, and unnecessary traffic jam and even life and property loss caused by driving into a deep water area are avoided.
Description
Technical Field
The invention relates to a water level early warning system based on an electronic positioning system, which is used for monitoring and early warning the water level of a low-lying area in a city and plays a role in preventing disasters and reducing harm.
Background
In recent years, flood disasters caused by heavy rainfall have received increasing attention and vigilance from people. At present, no effective measure is available in rainy days for drivers and passengers to acquire real-time water level information of roads in low-lying areas in front of cities in advance. According to retrieval, the related technologies of monitoring and early warning the water level of low-lying areas such as city underbridge and culvert have appeared. For example, the water level early warning system disclosed in chinese patent application No. CN201922498485.2, the water level early warning system described in the patent can transmit the water level signal at the lowest point of the culvert to the remote monitoring platform and display the signal through the display screen. For another example, chinese patent application No. CN201420045963.9 discloses a "water level warning system for a tunnel bridge", which can detect the height information of the water level in the tunnel bridge and display it above the bridge head of the tunnel bridge. Although the above two patents can both detect and display the water level information in the urban low-lying area to play a warning role, they cannot transmit the water level information to the driving driver or passenger in real time, and thus cannot play a good early warning role. Therefore, the invention provides an urban road low-lying area water level early warning system based on an electronic positioning system, which provides real-time road water level conditions for drivers and passengers on roads, and further can select safe roads to move ahead.
Disclosure of Invention
The invention aims to provide an urban low-lying area water level early warning system based on an electronic positioning system.
The technical scheme adopted by the invention to achieve the aim is as follows: the utility model provides a city low-lying district water level early warning system based on electronic positioning system, this system comprises city low-lying regional on-the-spot water level monitoring sensor, General Packet Radio Service (GPRS) transmission network, data processing center, navigation APP display terminal and traffic warning electronic display screen. The water level monitoring sensor transmits water level information data of the low-lying area site to the data processing center through GPRS, and meanwhile navigation data of the low-lying area site are also transmitted to the data processing center through GPRS; then the data processing center carries out interactive verification on the navigation data and the sensor data and then transmits the data to a threshold configuration unit, and then the water level early warning level of the low-lying area is judged; and finally, the data processing center remotely transmits the water level early warning grade signal to a navigation system APP display terminal and a traffic warning electronic display screen terminal through GPRS.
The specific method for data interaction verification is as follows: different from the traditional off-line water level early warning system, the invention provides a data interaction verification neural network model in a crowdsourcing mode. The model inputs are low-lying area field water level monitoring sensor data and surrounding navigation terminal user GPS movement data. Further information mining (such as driving speed, acceleration and the like) is carried out on the driving state to serve as neural network model characteristics, and the probability and the grade of the water accumulation accident are solved. In addition, the neural network model can output the credibility of data, can be used for data screening, has high universality and anti-interference performance, and can be suitable for different terminals.
Compared with the prior art, the invention has the beneficial effects that:
(1) the invention simultaneously detects the water level of the urban low-lying area through the water level detection sensor and the navigation data, and carries out interactive verification on the detection data and the navigation data of the sensor, thereby improving the accuracy of the water level early warning in the low-lying area.
(2) The water level early warning system for the urban low-lying area can transmit water level information to the electronic positioning system App terminal, provide real-time water level conditions of the low-lying area of the road in front for drivers and passengers, and report early warning levels, so that the drivers can make driving plans in advance, and unnecessary traffic jam and life and property loss caused by driving into a deep water area are avoided.
(3) The water level early warning system for the urban low-lying area can simultaneously transmit and display the water level early warning state on the navigation system App terminal and the traffic warning electronic display screen through the GPRS transmission network so as to remind drivers and passengers of making a safe driving route scheme in advance from multiple channels.
Drawings
FIG. 1 is a block diagram of the architecture of the present invention
FIG. 2 is a schematic diagram of data interaction verification
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.
As shown in a structural block diagram of fig. 1, the urban low-lying area water level early warning system based on the electronic positioning system comprises an urban low-lying area field water level monitoring sensor, a General Packet Radio Service (GPRS) transmission network, a data processing center, a navigation system APP display terminal and a traffic warning electronic display screen.
The water level monitoring sensor is installed in low-lying areas where accumulated water easily occurs, such as urban underbridge and culvert, and is used for collecting water level data information of the low-lying areas.
And a general packet radio service (6PRS) transmission network transmits the water level data collected by the water level monitoring sensor and the low-lying zone congestion condition data detected by the electronic positioning system to a data processing center.
The data processing center comprises two subunits, namely a data interaction verification unit and a threshold configuration unit.
And the data interactive verification unit interactively verifies the water level monitoring sensor data and the navigation data so as to accurately judge the water level condition on site. As shown in fig. 2, the method for identifying water accumulation accident based on crowdsourcing according to the present embodiment includes the following steps:
and acquiring a ponding accident occurrence judgment model, namely an optimal neural network model. In this embodiment, the process of constructing and training the neural network model is implemented in each terminal. In other embodiments, the construction and training of the neural network model can be completed at the server side, and then the optimal neural network model is sent to each terminal.
Specifically, firstly, a neural network model is constructed, and a preset number of sample terminal data and navigation GPS data corresponding to the sample terminal data are acquired. The step of constructing and the step of obtaining the sample are not executed in sequence.
After the samples are obtained, dividing the preset number of sample terminal data and the corresponding navigation data according to a preset proportion to obtain a training set and a verification set. For example, 80% of the sample terminal data is used as the training set, and 20% of the sample terminal data is used as the verification set. Each group of sample terminal data comprises vehicle running speed and acceleration; and the accumulated water accident data corresponding to the data of the sample terminal is collected by a low-lying area field water level monitoring sensor at the periphery of the sample terminal.
For the construction of the neural network model, compared with the traditional encoding and decoding model, the attention mechanism focuses more on the relationship between different input variables and the degree of association between the input variables and the tags, so in the embodiment, the multi-head self-attention mechanism and the target attention mechanism are used simultaneously to strengthen the model, and the degree of association between the input variables and the accident level are considered by using the attention mechanism, so that the average prediction error of the final model can be smaller than an acceptable range.
The output of the neural network model of the present embodiment is a gaussian distribution function of the accident-level discrimination result, the mathematical expectation of the gaussian distribution function represents the accident-level discrimination value having the highest probability, and the standard deviation of the gaussian distribution function represents the reliability of the accident-level discrimination result. Wherein, the larger the standard deviation is, the lower the reliability is; the smaller the standard deviation, the higher the confidence.
And acquiring accident grade judging results of other terminals within a preset range, and acquiring an accident grade judging value with the highest reliability as a final accident grade judging value according to the accident grade judging result of the terminal and the accident grade judging results of the other terminals.
The threshold value configuration unit sets the threshold value of the water level early warning level in advance and compares the threshold value with the data transmitted from the data interaction verification unit, and then the final early warning level is determined.
And finally, the data processing center simultaneously transmits the early warning grade signal to an App display terminal of the electronic positioning system and a traffic warning electronic display screen terminal, so that drivers and passengers are prompted to plan driving routes in advance, and traffic jam and even damage to lives and properties caused by the fact that the drivers and passengers are encumbered in a deepwater area are avoided.
Claims (3)
1. The utility model provides an urban low-lying regional water level early warning system based on electronic positioning system, characterized by water level monitoring sensor, General Packet Radio Service (GPRS) transmission network, data processing center, navigation APP display terminal and traffic warning electronic display screen.
2. The urban low-lying area water level early warning system based on the electronic positioning system as claimed in claim 1, wherein the data processing center comprises a data interaction verification unit and a threshold configuration unit.
3. The urban low-lying area water level early warning system based on the electronic positioning system as claimed in claim 1, wherein the data interaction unit inputs the terminal data into a preset discrimination model and outputs early warning discrimination results, and the early warning discrimination includes road section water accumulation danger levels and reliability thereof.
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| CN202111023221.7A CN113834545A (en) | 2021-08-26 | 2021-08-26 | Urban low-lying area water level early warning system based on electronic positioning system |
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105139603A (en) * | 2015-07-24 | 2015-12-09 | 华中科技大学无锡研究院 | Intelligent urban water accumulation monitoring and early warning system |
| CN105241524A (en) * | 2015-10-26 | 2016-01-13 | 河海大学常州校区 | Urban flood warning system and method based on radial basic function neural network model |
| CN108961703A (en) * | 2018-06-28 | 2018-12-07 | 深圳中学 | A kind of surface gathered water monitoring and pre-alarming method, apparatus and system |
| CN112085928A (en) * | 2020-08-13 | 2020-12-15 | 长威信息科技发展股份有限公司 | Urban low-lying road section ponding emergency rescue system based on big data |
-
2021
- 2021-08-26 CN CN202111023221.7A patent/CN113834545A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105139603A (en) * | 2015-07-24 | 2015-12-09 | 华中科技大学无锡研究院 | Intelligent urban water accumulation monitoring and early warning system |
| CN105241524A (en) * | 2015-10-26 | 2016-01-13 | 河海大学常州校区 | Urban flood warning system and method based on radial basic function neural network model |
| CN108961703A (en) * | 2018-06-28 | 2018-12-07 | 深圳中学 | A kind of surface gathered water monitoring and pre-alarming method, apparatus and system |
| CN112085928A (en) * | 2020-08-13 | 2020-12-15 | 长威信息科技发展股份有限公司 | Urban low-lying road section ponding emergency rescue system based on big data |
Non-Patent Citations (1)
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| 陈云霁 等: "《大数据技术原理与实践》", vol. 1, 北京邮电大学出版社, pages: 136 - 39 * |
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