CN111199636B - Working method of hydrological meteorological service system based on cloud computing - Google Patents
Working method of hydrological meteorological service system based on cloud computing Download PDFInfo
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Abstract
The invention provides a working method of a cloud computing-based hydrometeorology service system, which comprises a hydrometeorology observation system, a cloud computing center and an intelligent terminal connected with the cloud computing center through a network, wherein the hydrometeorology observation system is used for collecting hydrometeorology information and transmitting the hydrometeorology information to the cloud computing center; and the cloud computing center is used for receiving the hydrometeorological information and preprocessing and storing the hydrometeorological information. According to the invention, the data processing technology of cloud computing is utilized to realize real-time processing and control on the hydrometeorological information, and a user can acquire the required hydrometeorological information at any time through the intelligent terminal, so that the data sharing is realized in a wider range, and the user cost is reduced.
Description
Technical Field
The invention relates to the field of hydrological meteorological monitoring, in particular to a working method of a hydrological meteorological service system based on cloud computing.
Background
The cloud computing hydrological meteorological service can play a role in information integration and seamless sharing of a climate system, and help is provided for all parties who study the climate system and climate change and sustainable development. At present, the hydrological meteorological information system is positioned as a data center, and provides real-time observation data and historical statistical data for users in other industries. For the majority of industry users, especially the users in the non-hydrometeorological industry, the processed hydrometeorological information is required in addition to the original detection data. To further meet the demand and improve the service level, how to provide a more advanced hydrometeorological information service form should be considered.
Disclosure of Invention
Aiming at the problems, the invention provides a hydrological meteorological service system based on cloud computing.
The purpose of the invention is realized by adopting the following technical scheme:
the hydrological meteorological service system comprises a hydrological meteorological observation system, a cloud computing center and an intelligent terminal connected with the cloud computing center through a network, wherein the hydrological meteorological observation system is used for collecting hydrological meteorological information and transmitting the hydrological meteorological information to the cloud computing center; and the cloud computing center is used for receiving the hydrometeorological information and preprocessing and storing the hydrometeorological information.
The invention has the beneficial effects that: the data processing technology of cloud computing is utilized to realize real-time processing and control on the hydrometeorological information, and a user can acquire the needed hydrometeorological information at any time through the intelligent terminal, so that data sharing can be realized in a wider range, and the user cost is reduced.
Drawings
The invention is further illustrated by means of the attached drawings, but the embodiments in the drawings do not constitute any limitation to the invention, and for a person skilled in the art, other drawings can be obtained on the basis of the following drawings without inventive effort.
FIG. 1 is a block diagram of the present invention;
fig. 2 is a connection block diagram of the cloud computing center of the present invention.
Reference numerals:
the system comprises a hydrometeorology observation system 1, a cloud computing center 2, an intelligent terminal 3, a data preprocessing module 10, a data storage module 20, a hydrometeorology parameter historical information database server 30 and a network communication server 40.
Detailed Description
The invention is further described with reference to the following examples.
Referring to fig. 1 and fig. 2, the cloud computing-based hydrometeorological service system provided in this embodiment includes a hydrometeorological observation system 1, a cloud computing center 2, and an intelligent terminal 3 connected to the cloud computing center 2 through a network, where the hydrometeorological observation system 1 is configured to collect hydrometeorological information and transmit the hydrometeorological information to the cloud computing center 2; the cloud computing center 2 is used for receiving the hydrometeorology information, and preprocessing and storing the hydrometeorology information.
Preferably, the cloud computing center 2 includes a data preprocessing module 10, a data storage module 20, a hydrographic meteorological parameter historical information database server 30, and a network communication server 40, and the data storage module 20 and the hydrographic meteorological parameter historical information database server 30 are respectively connected to the data preprocessing module 10.
Preferably, the hydrographic meteorological information includes temperature and humidity, air pressure, rainfall, wind direction, wind speed, visibility.
The hydrometeorology service system of the embodiment of the invention utilizes the data processing technology of cloud computing to realize real-time processing and control on the hydrometeorology information, and a user can acquire the required hydrometeorology information at any time through the intelligent terminal 3, thereby being convenient for realizing data sharing in a wider range and reducing the user cost.
Preferably, the hydrometeorology observation system 1 adopts the mobile sensor network to collect and send the hydrometeorology information, including a plurality of mobile sensor nodes and fixed sensor node, carries out data transmission each other between each mobile sensor node, constitutes delay tolerant network, and each fixed sensor node constitutes the intercommunication network, and fixed sensor node and the mobile sensor node communication of communication range in, the mobile sensor node removes in the monitoring area, and fixed sensor node is fixed to be set up in the monitoring area.
The mobile sensor node sends self-positioning data while sending the hydrometeorology information, and the mobile sensor node specifically executes when self-positioning:
(1) according to the set transmitting signal strength, the mobile sensor node continuously sends positioning request data packets to the fixed sensor node at a time interval of T in a set period, and the format of the positioning request data packets is as follows:
{IDH,MH,γH,T}
wherein, IDHNumber of mobile sensor nodes, MHNumber of positioning request packets, gamma, sent in a cycle for the mobile sensor nodeHThe sequence numbers of the positioning request data packets sent this time in all the sent positioning request data packets are represented;
(2) after the fixed sensor node receives the positioning request data packet for the first time, the fixed sensor node continuously receives MHThe time is multiplied by T, when a positioning request data packet is received, a corresponding signal strength indicated value is detected and recorded, and if a certain positioning request data packet is not received, the corresponding signal strength indicated value is set to be 0;
(3) after the fixed sensor node receives the positioning request data packet, a feedback data packet is constructed and sent to the mobile sensor node, wherein the format of the feedback data packet is as follows:
where IDS denotes the number of the fixed sensor node, xθ,yθFor the position coordinates of the fixed sensor node,
sequentially recorded signal strength indication values;
(4) after receiving all the feedback data packets, the mobile sensor node performs positioning calculation according to the feedback data packets, and the positioning calculation specifically includes: setting M1 fixed sensor nodes which have sent feedback data packets, wherein any two fixed sensor nodes form a sensor node pair, and the fixed sensor nodes form a sensor node pair
A pair of sensor nodes; the mobile sensor node calculates the distance ratio of the mobile sensor node to two fixed sensor nodes in the sensor node pair according to the signal strength indicated value in the feedback data packet; if the distance ratio of the sensor node pair is smaller than the set ratio threshold, extracting the position coordinates of two fixed sensor nodes in the sensor node pair, and calculating the position coordinates (x, y) of the mobile sensor node by the mobile sensor node according to the following formula:
in the formula (I), the compound is shown in the specification,
respectively representing the transverse position coordinates of the first and second fixed sensor nodes in the sensor node pair with the alpha distance ratio smaller than the set ratio threshold,
respectively indicate that the alpha-th distance ratio is smaller than the set ratioThe longitudinal position coordinates of the first and second fixed sensor nodes in the sensor node pair of the threshold value,
indicating the number of sensor node pairs whose distance ratio is less than a set ratio threshold.
In the related technology, the mobile sensor node positioning calculates the distance between a mobile node and a plurality of fixed nodes by obtaining the signal strength indicated values between the plurality of fixed nodes and the mobile node, then establishes an equation set according to the coordinates of the fixed nodes and the distance between the mobile node and the plurality of fixed nodes by utilizing a trilateral positioning method or a centroid algorithm, and finally solves the coordinate position of the mobile node;
the preferred embodiment improves the positioning mode of the mobile sensor node, simplifies the operation process and improves the positioning efficiency of the mobile sensor node compared with the positioning method in the related art, so that the position of the mobile sensor node and the hydrometeorology information acquired by the mobile sensor node can be sent to the cloud computing center 2 in real time for corresponding data processing.
Preferably, when calculating the distance ratio between the mobile sensor node and two fixed sensor nodes in the sensor node pair, specifically executing:
(1) according to the logarithmic path loss model, the difference value of the signal strength indicating values recorded by two fixed sensor nodes in the sensor node pair is represented as:
in the formula (I), the compound is shown in the specification,
respectively representing the signal strength indicating values recorded by the first fixed sensor node and the second fixed sensor node in the beta sensor node pair when receiving the positioning request data packet at the kth time, wherein rho is the path loss index of the logarithmic path loss model,
respectively, random noise generated when a first fixed sensor node and a second fixed sensor node in a beta sensor node pair receive a positioning request data packet at the kth time;
(2) calculating the magnitude probability of the difference value of the signal strength indicating values recorded by two fixed sensor nodes in the sensor node pair:
in the formula (I), the compound is shown in the specification,
representing the magnitude probability of the difference value of the signal strength indicating values recorded by two fixed sensor nodes in the beta sensor node pair, and the count () is a counting function used for calculating
Number of times of hour, MKThe number of signal strength indicator values recorded for fixed sensor nodes;
(3) to be provided with
And determining a corresponding expected value through a standard normal distribution table as a standard normal distribution probability, and taking the expected value as the distance ratio of the mobile sensor node to two fixed sensor nodes in the beta-th sensor node pair.
In the preferred embodiment, when the distance ratio of two fixed sensor nodes in the pair of the mobile sensor node and the sensor node is calculated, the relation between the difference value of the signal strength indicating values recorded by the two fixed sensor nodes and the distance ratio is measured by using a normal distribution statistical method, so that the corresponding expected value, namely the distance ratio, is determined by inquiring a standard normal distribution table, the rapid calculation of the distance ratio is realized, the flexible and robust positioning of the mobile sensor node is facilitated, and the hydrological meteorological service system can acquire the hydrological meteorological information in all directions in a monitoring area.
Preferably, before the mobile sensor node performs positioning calculation according to the feedback data packet, the feedback data packet is screened, and if a signal strength indicating value in the feedback data packet satisfies the following formula, the feedback data packet is removed:
wherein, count (. cndot.) is a counting function,
the number of the signal strength indication values when satisfied is respectively calculated,
indicating the f signal strength indicator value, M, in the b feedback data packet received by the mobile sensor nodeTFor a set maximum value of the signal strength indicator value, MBThe number of the signal strength indicating values of the b-th feedback data packet received by the mobile sensor node is phi, which is a set threshold value.
The preferred embodiment ensures that the mobile sensor node can carry out self-positioning by utilizing the signal strength indicated value of the feedback data packet which meets the condition, thereby reducing the influence of certain signal strength indicated values which are greatly influenced by the outside on positioning calculation, being beneficial to improving the positioning precision of the mobile sensor node and ensuring the accuracy of the hydrometeorology information.
Finally, it should be noted that the above embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the protection scope of the present invention, although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions can be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.
Claims (2)
1. A working method of a hydrometeorology service system based on cloud computing is characterized in that the hydrometeorology service system comprises a hydrometeology observation system, a cloud computing center and an intelligent terminal connected with the cloud computing center through a network, and the working method comprises the following steps:
the hydrological meteorological observation system collects the hydrological meteorological information and transmits the hydrological meteorological information to the cloud computing center;
the cloud computing center receives the hydrometeorological information and preprocesses and stores the hydrometeorological information;
the cloud computing center comprises a data preprocessing module, a data storage module, a hydrographic meteorological parameter historical information database server and a network communication server, wherein the data storage module and the hydrographic meteorological parameter historical information database server are respectively connected with the data preprocessing module;
the hydrometeorology observation system adopts a mobile sensor network to collect and send hydrometeology information and comprises a plurality of mobile sensor nodes and fixed sensor nodes, data transmission is carried out between the mobile sensor nodes to form a delay tolerant network, each fixed sensor node forms a communication network, the fixed sensor nodes are communicated with the mobile sensor nodes in a communication range, the mobile sensor nodes move in a monitoring area, and the fixed sensor nodes are fixedly arranged in the monitoring area;
the mobile sensor node sends self-positioning data while sending the hydrometeorology information, and the mobile sensor node specifically executes when self-positioning:
(1) according to the set transmitting signal strength, the mobile sensor node continuously sends positioning request data packets to the fixed sensor node at a time interval of T in a set period, and the format of the positioning request data packets is as follows:
{IDH,MH,γH,T}
wherein, IDHNumber of mobile sensor nodes, MHNumber of positioning request packets, gamma, sent in a cycle for the mobile sensor nodeHIndicating that the positioning request data packet sent this time is in allThe sequence number in the sent positioning request data packet;
(2) after the fixed sensor node receives the positioning request data packet for the first time, the fixed sensor node continuously receives MHThe time is multiplied by T, when a positioning request data packet is received, a corresponding signal strength indicated value is detected and recorded, and if a certain positioning request data packet is not received, the corresponding signal strength indicated value is set to be 0;
(3) after the fixed sensor node receives the positioning request data packet, a feedback data packet is constructed and sent to the mobile sensor node, wherein the format of the feedback data packet is as follows:
where IDS denotes the number of the fixed sensor node, xθ,yθFor the position coordinates of the fixed sensor node,
sequentially recorded signal strength indication values;
(4) after receiving all the feedback data packets, the mobile sensor node performs positioning calculation according to the feedback data packets, and the positioning calculation specifically includes: setting M1 fixed sensor nodes which have sent feedback data packets, wherein any two fixed sensor nodes form a sensor node pair, and the fixed sensor nodes form a sensor node pair
A pair of sensor nodes; the mobile sensor node calculates the distance ratio of the mobile sensor node to two fixed sensor nodes in the sensor node pair according to the signal strength indicated value in the feedback data packet; if the distance ratio of the sensor node pair is smaller than the set ratio threshold, extracting the position coordinates of two fixed sensor nodes in the sensor node pair, and calculating the position coordinates (x, y) of the mobile sensor node by the mobile sensor node according to the following formula:
in the formula
Respectively representing the transverse position coordinates of the first and second fixed sensor nodes in the sensor node pair with the alpha distance ratio smaller than a set ratio threshold,
respectively representing the longitudinal position coordinates of the first and second fixed sensor nodes in the sensor node pair with the alpha distance ratio smaller than the set ratio threshold,
indicating the number of sensor node pairs whose distance ratio is less than a set ratio threshold.
2. The method of claim 1, wherein the mobile sensor node filters the feedback data packet before performing the positioning calculation according to the feedback data packet, and the feedback data packet is rejected if the signal strength indicating value in the feedback data packet satisfies the following formula:
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101873664A (en) * | 2010-07-06 | 2010-10-27 | 西安交通大学 | Method for positioning mobile wireless sensor network |
| CN102547973A (en) * | 2010-12-17 | 2012-07-04 | 上海工程技术大学 | RSSI (received signal strength indicator)-based multi-sensor fusion mobile node tracking method |
| CN204425399U (en) * | 2015-01-04 | 2015-06-24 | 江苏海事职业技术学院 | A kind of hydrometeorological operation system based on cloud computing |
| CN105813193A (en) * | 2016-04-15 | 2016-07-27 | 国网河北省电力公司 | Node positioning method of wireless sensor network of smart power grid |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101466146A (en) * | 2009-01-08 | 2009-06-24 | 上海交通大学 | Multi-target orientation method of wireless sensor network based on probability weighting |
| CN101909353B (en) * | 2009-06-05 | 2014-03-12 | 中国移动通信集团上海有限公司 | System and method for determining position information and mobile terminal and sensor node equipment |
| WO2010149796A1 (en) * | 2009-06-26 | 2010-12-29 | Masat B.V. | Method and system for determining the location of a moving sensor node |
| CN101801012B (en) * | 2010-01-29 | 2013-02-27 | 东南大学 | Self-adapting positioning method for mobile nodes of hybrid sensor network |
| US11120371B2 (en) * | 2014-06-23 | 2021-09-14 | Sensia Netherlands B.V. | Systems and methods for cloud-based asset management and analysis regarding well devices |
| US10344567B2 (en) * | 2014-06-23 | 2019-07-09 | Rockwell Automation Asia Pacific Business Center Pte. Ltd. | Systems and methods for cloud-based automatic configuration of remote terminal units |
| WO2016160376A1 (en) * | 2015-03-27 | 2016-10-06 | Pcms Holdings, Inc. | System and method for indoor localization using beacons |
| CN105163382A (en) * | 2015-05-07 | 2015-12-16 | 中国科学院信息工程研究所 | Indoor region location optimization method and system |
| CN106385432A (en) * | 2016-08-30 | 2017-02-08 | 孟玲 | Big data based insect disease monitoring and early warning system |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101873664A (en) * | 2010-07-06 | 2010-10-27 | 西安交通大学 | Method for positioning mobile wireless sensor network |
| CN102547973A (en) * | 2010-12-17 | 2012-07-04 | 上海工程技术大学 | RSSI (received signal strength indicator)-based multi-sensor fusion mobile node tracking method |
| CN204425399U (en) * | 2015-01-04 | 2015-06-24 | 江苏海事职业技术学院 | A kind of hydrometeorological operation system based on cloud computing |
| CN105813193A (en) * | 2016-04-15 | 2016-07-27 | 国网河北省电力公司 | Node positioning method of wireless sensor network of smart power grid |
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