KR20190050745A - Big-data based internet-of-things intelligent monitoring system of filtering device for rain water - Google Patents

Big-data based internet-of-things intelligent monitoring system of filtering device for rain water Download PDF

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KR20190050745A
KR20190050745A KR1020190047037A KR20190047037A KR20190050745A KR 20190050745 A KR20190050745 A KR 20190050745A KR 1020190047037 A KR1020190047037 A KR 1020190047037A KR 20190047037 A KR20190047037 A KR 20190047037A KR 20190050745 A KR20190050745 A KR 20190050745A
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big data
iot
filtration
unit
monitoring system
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KR1020190047037A
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이주승
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(주)랜드로드
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/18—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form
    • G05B19/406—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by monitoring or safety
    • G05B19/4065—Monitoring tool breakage, life or condition
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
    • B01D—SEPARATION
    • B01D35/00—Filtering devices having features not specifically covered by groups B01D24/00 - B01D33/00, or for applications not specifically covered by groups B01D24/00 - B01D33/00; Auxiliary devices for filtration; Filter housing constructions
    • B01D35/28—Strainers not provided for elsewhere
    • E—FIXED CONSTRUCTIONS
    • E03—WATER SUPPLY; SEWERAGE
    • E03F—SEWERS; CESSPOOLS
    • E03F5/00—Sewerage structures
    • E03F5/14—Devices for separating liquid or solid substances from sewage, e.g. sand or sludge traps, rakes or grates
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services

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Abstract

The IoT intelligent monitoring system of the Big Data based superior filtration device is provided. The IoT intelligent monitoring system of the Big Data based extreme filtration apparatus according to an embodiment of the present invention is an IoT intelligent monitoring system of an excellent filtration apparatus based on a Big Data. The IoT intelligent monitoring system includes a first IoT sensing part; A second IoT sensing unit provided outside the superior filtration apparatus; A big data processing unit for collecting and storing the sensing values obtained in the first and second IoT sensing units and analyzing the big data as the accumulated sensing values; A control unit for determining a state of the extra filtration apparatus based on the big data analyzed by the big data processing unit; And a communication unit for transmitting a status signal to the user terminal based on the status of the exceptional filtering apparatus discriminated by the control unit. The control unit controls the operation of the superfiltration apparatus using the big data analyzed by the big data processing unit, Learning is performed using a predetermined deep learning algorithm that targets the cleaning of the robot.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention [0001] The present invention relates to an IoT intelligent monitoring system of a superior data-

The present invention relates to an IoT intelligent monitoring system of a Big Data based extreme filtration device.

In general, pollutants can be classified into point sources with distinct discharge points and nonpoint sources with unclear discharge points. Point pollution sources can be discharged to a certain degree of cleanliness by installing separate purification devices or wastewater treatment facilities at discharge points. On the other hand, nonpoint source pollutants are unclear and remain on a wide range of ground surface, and can enter the aquatic system such as rivers and rivers together with rainfall and cause water pollution.

Particularly, fine particles contained in the exhaust gas discharged by the running of the vehicle, dust caused by the friction of the asphalt tire, soot and dust of the factory, etc. can be introduced into the water system together with rainfall. In order to prevent such water pollution, there is provided a filtration facility for preventing non-point pollutants from flowing into the water system of rivers, rivers, etc., along with the initial rainfall.

However, the screen installed in the filtration facility fixed to the slope of the road due to non-point pollutants may be clogged, which may cause a problem that the passage through which the storm water flows into the drainage channel is blocked.

Most of the filtration equipment is installed in the underground structure, making it difficult to check whether the filter material is clogged or not, and it is difficult to grasp the timing of cleaning and replacement. In addition, residues such as toilets, traffic accidents, and other foreign matter that enter the slope of the road may be infiltrated to damage the filtration device or deteriorate the filtration function.

Recently, various attempts have been made to monitor the filtration apparatus utilizing the ICT technology.

Korean Registered Patent No. 0718719 (registered on May 05, 2007) Korean Registered Patent No. 1712563 (Registered on Feb. 27, 2017) Korea Patent Publication No. 2015-0045187 (published on April 28, 2015)

SUMMARY OF THE INVENTION The present invention has been made to solve the above problems and it is an object of the present invention to provide an IoT intelligent monitoring system of a superior data filtering apparatus capable of monitoring an excellent filtration apparatus by using Big Data and Deep Learning algorithm built in the Internet of IoT to provide.

The problems to be solved by the present invention are not limited to the above-mentioned problems, and other matters not mentioned can be clearly understood by those skilled in the art from the following description.

According to another aspect of the present invention, there is provided an IoT intelligent monitoring system for a superior data filtering apparatus, comprising: A first IoT sensing unit; A second IoT sensing unit provided outside the superior filtration apparatus; A big data processing unit for collecting and storing the sensing values obtained in the first and second IoT sensing units and analyzing the big data as the accumulated sensing values; A control unit for determining a state of the extra filtration apparatus based on the big data analyzed by the big data processing unit; And a communication unit for transmitting a status signal to the user terminal based on the status of the exceptional filtering apparatus discriminated by the control unit. The control unit controls the operation of the superfiltration apparatus using the big data analyzed by the big data processing unit, Learning is performed using a predetermined deep learning algorithm that targets the cleaning of the robot.

In addition, the first IoT sensing unit may include a rain sensor for measuring the amount of rainwater flowing into the filtration unit of the superior filtration apparatus, a weight sensor for measuring the weight of the filtration net provided in the filtration unit, And a water level sensor for measuring the water level.

The second IoT sensing unit may include a temperature sensor for measuring the temperature of the periphery of the superfiltration apparatus and a humidity sensor for measuring humidity.

In addition, the big data processing unit collects the sensing values obtained at the first and second IoT sensing units periodically from the first and second IoT sensing units via the Bluetooth, the WLAN access point, or the IoT gateway Can accumulate.

The control unit may include a depth learning module including an input layer, two or more hidden layers, and an output layer, and may determine a weight applied to each of the two or more hidden layers.

Other specific details of the invention are included in the detailed description and drawings.

According to the present invention, the excellent filtration apparatus can be efficiently managed by monitoring the superior filtration apparatus by using the big data and the deep running algorithm established under the Internet (IoT) environment.

FIG. 1 is a block diagram showing the concept of an IoT intelligent monitoring system of a Big Data-based excellent filtering apparatus according to an embodiment of the present invention.
2 is a view showing a structure of a deep learning module.
FIG. 3 is a perspective view showing an excellent filtration apparatus according to an embodiment of the present invention installed on a slope of a road; FIG.
4 is a perspective view of a superior filtration apparatus according to an embodiment of the present invention.
5 is a cross-sectional view showing that the opening / closing member rotates to open the superior bypass hole in the superior filtration apparatus of FIG.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS The advantages and features of the present invention and the manner of achieving them will become apparent with reference to the embodiments described in detail below with reference to the accompanying drawings. The present invention may, however, be embodied in many different forms and should not be construed as being limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art. Is provided to fully convey the scope of the invention to those skilled in the art, and the invention is only defined by the scope of the claims. Like reference numerals refer to like elements throughout the specification.

Although the first, second, etc. are used to describe various elements, components and / or sections, it is needless to say that these elements, components and / or sections are not limited by these terms. These terms are only used to distinguish one element, element or section from another element, element or section. Therefore, it goes without saying that the first element, the first element or the first section mentioned below may be the second element, the second element or the second section within the technical spirit of the present invention.

The terminology used herein is for the purpose of illustrating embodiments and is not intended to be limiting of the present invention. In the present specification, the singular form includes plural forms unless otherwise specified in the specification. As used herein, the terms "comprises" and / or "made of" means that a component, step, operation, and / or element may be embodied in one or more other components, steps, operations, and / And does not exclude the presence or addition thereof.

Unless defined otherwise, all terms (including technical and scientific terms) used herein may be used in a sense commonly understood by one of ordinary skill in the art to which this invention belongs. Also, commonly used predefined terms are not ideally or excessively interpreted unless explicitly defined otherwise.

Hereinafter, the present invention will be described in more detail with reference to the accompanying drawings.

FIG. 1 is a block diagram showing the concept of an IoT intelligent monitoring system of a Big Data-based excellent filtering apparatus according to an embodiment of the present invention. 2 is a diagram showing a structure of a deep learning module. FIG. 3 is a perspective view showing that an excellent filtration apparatus according to an embodiment of the present invention is installed on a slope of a road.

1 to 3, the IoT intelligent monitoring system 100 of the superior filtration apparatus based on the Big Data according to an embodiment of the present invention includes an IoT intelligent monitoring system 100 for receiving Big Data, IoT Internet of Things, and Artificial Intelligence.

In more detail, the IoT intelligent monitoring system 100 of the superior filtering apparatus based on the Big Data according to an embodiment of the present invention includes a first IoT sensing unit 120 provided in the superior filtration apparatus 100, A second IoT sensing unit 220 provided outside the filtration apparatus 100, and a second sensing unit 220 for sensing and accumulating the sensing values obtained by the first and second IoT sensing units 120 and 220, A control unit 130 for determining the state of the superfiltration apparatus 100 based on the big data analyzed by the big data processing unit 300, And a communication unit 140 for transmitting a status signal to the user terminal 50 based on the status of the superior filtration apparatus 100 determined.

Here, the excellent filtration apparatus 100 functions to filter storm water, and may be installed in a drainage passage or the like. For example, as shown in Fig. 3, the superior filtration apparatus 100 may be installed in a drainage passage 2 installed on a slope 1 of a road or the like.

For example, the drainage passage (2) is embedded in the slope (1) of the road, and the excellent filtration apparatus (100) can be mounted in the middle of the drainage passage (2). At this time, the stormwater filtration apparatus 100 can pass all storm water flowing out through the drainage duct 2 in a structure that is two times higher than the depth of the drainage duct 2. Therefore, the rainwater mixed with the contaminants discharged from the road can be discharged to the ditch 3 through the excellent filtration apparatus 100.

It should be apparent to those skilled in the art that the excellent filtration apparatus 100 is not limited to the one provided on the slope 1 of the road, but may also be installed on the lower part of the trench or the drain where the storm can leak out.

The super filtration apparatus 100 includes a filtering unit 110, a first IoT sensing unit 120, a control unit 130, a communication unit 140 and the like. The second IoT sensing unit 220 and the big data processing unit 300) together with the IoT intelligent monitoring system 1000 of the Big Data-based superior filtration apparatus.

The detailed structure of the filtration unit 110 in the exceptional filtration apparatus 100 according to an embodiment of the present invention will be described later.

The first IoT sensing unit 120 is provided inside the superior filtration apparatus 100 and includes a waste water amount sensor for measuring the amount of waste flowing into the filtration unit 110 of the superior filtration apparatus 100, A weight sensor for measuring the weight of the filter net provided in the filtration unit, and a water level sensor for measuring the water level of the filtration unit.

The second IoT sensing unit 220 may be provided outside the superior filtration apparatus 100 and may include a temperature sensor for measuring the temperature around the superior filtration apparatus 100 and a humidity sensor for measuring the humidity.

The big data processing unit 300 collects and accumulates the sensing values obtained by the first and second IoT sensing units 120 and 220, and analyzes the accumulated big data.

For example, the big data processing unit 300 periodically receives the first and second IoT sensing units 120 and 220 from the first and second IoT sensing units 120 and 220 through a Bluetooth, a wireless LAN access point, an IoT gateway, It is possible to collect and accumulate the sensed values obtained from the sensors 120 and 220.

The big data processing unit 300 can classify normal data and abnormal data using algorithms such as classification, clustering, and regression based on the collected and accumulated sensing signals .

The big data processing unit 300 may include a big data collection module 310, a big data analysis module 320, and a big data storage module 330.

Specifically, the big data collection module 310 collects sensing signals from the first and second IoT sensing units 120 and 220. The big data analysis module 320 classifies the data using algorithms such as classification, clustering, and regression based on the collected sensing signals. The big data storage module 330 stores the analyzed and classified data in the big data analysis module 320.

The controller 130 determines the state of the extraordinary filtration apparatus 100 based on the big data analyzed by the big data processing unit 300.

Specifically, the control unit 130 can learn using a pre-set deep learning algorithm that targets whether or not to clean the superior filtration apparatus 100, using the big data analyzed by the big data processing unit 300 as an input value .

Referring to FIG. 2, data analyzed by the big data processing unit 300 is input to an input, and an output is generated based on the analyzed data. Big data analyzed in the big data processing unit 300 is input to the input layer as an input value of a deep learning neural network, input data becomes learning data, weight is given to learning data, and the deep learning neural network And outputs an output value from the output layer, for example, whether or not the superior filtration apparatus 100 is cleaned.

The artificial neural network consists of an input layer, a hidden layer, and an output layer, and the input layer can transmit the received value to the hidden layer as it is. The hidden layer may include a plurality of nodes, and each node may multiply a plurality of input signals by respective weights, and output an addition signal obtained by adding the input signals. The hidden layer and the output layer can perform weighted sum calculation and active function calculation. The weighted sum calculation may take the form of combining the nodes of the input layer or the hidden layer. The activation function may be a sigmoid function as shown in Equation (1) below, and may be a function for transforming a combination of an input variable or a hidden node.

Figure pat00001

Referring to FIG. 2, the artificial neural network may be a deep neural network having two or more hidden layers, and may be a deep learning neural network to which a deep learning technique is applied. In FIG. 2, the hidden layer is shown as a hidden layer 1 (hidden layer 2), but it is to be understood that it is not limited thereto. At this time, the deep learning neural network is divided into a back-propagation, a restricted Boltzmann machine, an auto encoder, a CNN (Convolutional Neural Network), an RNN (Recurrent Neural Network), a DBN Deep Belief Network).

For example, the control unit 130 may calculate the reduction rate per cycle using the weight of the filtration unit 110 measured at regular intervals, compare the measured weight with the predetermined reference weight value, ) Can be judged as to whether or not to clean.

Here, the control unit 130 includes a deep learning module including an input layer, two or more hidden layers, and an output layer, and can determine a weight applied to each of the two or more hidden layers.

In one embodiment, input nodes of the input layer may be multiplied by weights X, output to multiple nodes of the hidden layer, multiplied by weights Y, and output to the output layer. It is possible to compare the data input to the input layer with the data output to the output layer and update the weight applied to the hidden layers according to the compared value.

Particularly, the controller 130 can control the number of nodes and the number of hidden layers between the input layer and the hidden layer, the hidden layer and the output layer, and can configure the size of the neural network flexibly by constructing the deep learning neural network structure without restriction. .

The communication unit 140 transmits a status signal to the user terminal 50 based on the status of the extra filtration apparatus 100 determined by the control unit 130. [

For example, the communication unit 140 may transmit the right quantity information, the weight information, the water level information, the temperature information, and the humidity information measured by the first and second sensing units 120 and 220 to the outside.

If it is determined that cleaning of the filtration unit 110 is necessary based on the state of the extra filtration apparatus 100, the communication unit 140 may transmit status signals to the outside.

The data and information transmitted from the communication unit 140 may be stored in an external device, a cloud platform, or the like.

The communication unit 140 may use various wireless Internet or wireless communication networks such as Wi-Fi, 3G, and 4G. For example, the communication unit 140 may use an ultra low power long distance mobile communication network such as NB-IoT, LoRa, Wifi, Blutooth low energy, and LTE-M.

Here, the user terminal 50 may have a web browser (Netscape, Internet Explorer, Chrome, etc.) capable of displaying the contents of a web page such as HTML, XML, and the like. The user terminal 50 may be a general mobile communication terminal, a terminal capable of 2G / 3G / 4G / 5G, a WiBro wireless network service, a Palm Personal Computer, a Personal Digital Assistant (PDA) A smart phone, a smart phone, a wireless application protocol phone (WAP phone), and the like, and may be a wired / wireless communication device including an IEEE 802.11 wireless LAN network card, And the like. The user terminal 50 may be an information communication device such as a computer, a notebook computer, or the like, in addition to the mobile communication terminal.

The user terminal 50 can receive the right quantity information, the weight information, the water level information, the temperature information, the humidity information, and the like through the communication unit 140, so that it is possible to monitor the environment information using the excellent filtration apparatus 100 , And the superior filtration apparatus 100 can be used as an automatic weather measurement system (AWS).

4 is a perspective view of a superior filtration apparatus according to an embodiment of the present invention. 5 is a cross-sectional view showing that the opening / closing member rotates to open the superior bypass hole in the superior filtration apparatus of FIG.

Referring to FIG. 4, the filtration unit 110 of the superior filtration apparatus 100 can filter pollutants contained in the rainwater through the rainwater. Here, the filtration unit 110 may include a filtration net 111, a filtration member 112, a support plate 113, and a separation wall 114.

The filter net 111 may include a filter net case 1111, a filter net member 1112, and a filter net opening and closing member 1114.

The filter net case 1111 is fixed in the filter unit 111, and the filter net member 1112 can be fixed. Specifically, one side of the filter net case 1111 may include a perforated network strainer that is opened to allow the inflow to flow in and is fixed to the inflow port.

That is, the bleed water which has passed through the filter net member 1112 through the filter net case 1111 can be discharged to the water bath. Here, when the storm is infiltrated into the filter net case 1111, the strainer is inflated to prevent the filter net member 1112 from being expanded or ruptured by the pressure of the storm.

A weight sensor 122 included in the first IoT sensing unit 120 is connected to the filter network case 1111 and measured together with the weight of the filter net member 1112. Therefore, the weight measured by the weight sensor 122 may include the weight of the filter net case 1111 and the filter net member 1112.

In addition, the filter net 111 may further include a filter net hinge 1113. Here, the filter net hinge 1113 can prevent the filter net 111 from being separated from the filter net hinge 1111 when the filter net case 1111 is fixed to the support plate 113 of the filtration unit 110. [

Further, the filter net hinge 1113 may be disposed apart from the support plate using a step member. Here, the height of the step member may be equal to or lower than the height of the weight sensor. That is, despite the arrangement of the weight sensor for measuring the weight of the filter net 111, the filter net 111 can be stably fixed to the support plate 113 by the step member.

In addition, the filter opening and closing member 1114 is opened when the filter net 111 is cleaned or replaced, thereby facilitating the cleaning of the filter net 111.

Here, the filter net opening and closing member 1114 can open and close the filter net case 1111 by the filter net locking member 1115 and the filter net opening member 1116.

The filter net member 1112 can filter the contaminants contained in the storm that pass through the filter net case 1111. Further, the filter net member 1112 can be expanded in the form of a filter net case 1111 according to the amount of contaminants. Therefore, even if the amount of abundance is rapidly increased, it is possible to prevent the rainwater containing the pollutants contained in the filter net member 11112 from flowing into the water system.

However, it is needless to say that only one filtering net 111 is shown in the excellent filtration apparatus 100, but it is needless to say that two or more filtering net 111 can be installed.

The filtration member 112 may be coupled to a support plate 114 provided in the filtration unit 110 and disposed between the stormwater inlet and the filtration net 111. Here, the filtration member 112 may be a mesh plate type having a filtration hole of a predetermined size. Accordingly, the filtration member 112 can remove contaminants having a filtration hole size or more from the stormwater flowing into the filtration unit 110.

And can be fixed to the support plate 113 by the filter member stopper 1121. Here, the filtration member stopper 1121 can prevent the filtration member 112 from rotating or being separated from the filtration unit 110 due to the inflow of bleeding. In other words, the filtration member stopper 1121 can prevent the filtration member 112 from passing through the filtration net 111 directly due to the rotation of the filtration member 112 in the outflow direction.

However, although the filter member stopper 1121 according to an embodiment of the present invention is described as being fixed, it may also be realized as a one-way hinge. In other words, the one-way hinge-type filter member stopper 1121 can be rotated in the direction opposite to the filtering net 111 (i.e., in the inflow direction) to facilitate the cleaning of the filtering net 111.

The filtration member 112 can also prevent the filtration member 112 from being rotated in the direction of the filtration net 111 (i.e., in the outflow direction) by the filtration member sub stopper 1146 included in the separation wall 114 have.

That is, the filtration member 112 can be rotated only in the direction opposite to the filtration net 111 (that is, in the inflow direction) by the filtration member stopper 1121 and the filtration member sub stopper 1146.

As a result, the superfiltration apparatus 100 according to an embodiment of the present invention can filter the contaminants contained in the stormwater double by using the filter net 111 and the filtration member 112.

The support plate 113 can be inserted into the filtration unit 110 through the inflow port of the filtration unit 110. The support plate 113 may be inserted into the filtration unit 110 together with the filtration net 111 and the filtration member 112 in combination with the filtration net 111 and the filtration member 112.

The support plate 113 may further include a lead-out rail 1131 capable of pulling the support plate 113 to the road slope 1. One end of the drawer rail 1131 is coupled to the support plate 113 and the other end of the drawer rail 1131 that is opposite to the one end of the drawer rail 1131 is fixed to the outside of the filtration unit 110.

The separation wall 114 is installed in the filtration part 110 and can separate the passage through which the storm is introduced into the first excellent passage H1 and the second excellent passage H2.

Here, the separation wall 114 may include a separation wall opening and closing member 1141, a guard rail 1143, and a weight 1144.

The separation wall opening and closing member 1141 can open and close the through hole 1143. The separating wall opening and closing member 1141 is coupled to the separating wall 114 by the hinge 1142 so as to be able to rotate in one direction .

A guard rail 1143 and a weight 1144 may be provided on the support plate 114. The guard rail 1143 and the weight 1144 can control the weight limit at which the partition wall opening and closing member 1141 is opened.

Specifically, the guard rail 1143 includes a plurality of holes, and the minimum weight at which the partition wall opening and closing member 1141 can be opened may vary depending on the position of the hole to which the weight weight 1144 is coupled. That is, as the hole of the guard rail 1143 to which the weight 1144 is coupled is moved away from the hinge 1142, the limit weight at which the separation wall opening and closing member 1141 can be opened increases and the hinge 1142 The higher the quality, the lower the marginal weight.

For example, in a season where precipitation is large as in the summer, the hole of the guard rail 1143, to which the weight 1144 is coupled, is fixed away from the hinge 1142 so that the separation wall opening / .

That is, according to an embodiment of the present invention, opening and closing of the partition wall opening / closing member 1141 can be controlled by using the guard rail 1143 and the weight 1144.

As a result, the guard rail 1143 and the weight 1144 can prevent the vortex from being generated due to the saturation of the fine inflow passage due to the change in the inflow amount.

Referring to FIG. 5, according to an embodiment of the present invention, the inside of the filtration part 110 is separated by the support wall 114. That is, according to the support wall 114, the inside of the filtration part 110 can be separated into the first excellent passage H1 and the second excellent passage H2.

According to an embodiment of the present invention, the superior bypass hole 1145 of the support wall 114 can be opened when the amount of the excess introduced into the filtration part 110 is equal to or larger than the reference amount of water. Here, the reference rainwater can be preset based on the amount of rain that can be accommodated in the first excellent passage (H1) of the filtration unit (110).

That is, the separating wall opening / closing member 1141 can be opened by the determining unit 130 when the excellent amount measured by the right water sensor (not shown) of the first IoT sensing unit 120 is more than the reference right water amount.

Therefore, when the outflow amount flowing into the filtration part 110 is equal to or larger than the standard amount, the outflow of the first excellent passage H1 is discharged to the outside through the second bypass passage H2 through the superior bypass hole 1145 .

As a result, according to the embodiment of the present invention, it is possible to prevent the rainwater from which the pollutants have not been removed from flowing into the water system in the unfiltered state over the excellent filtration apparatus 100.

While the present invention has been described in connection with what is presently considered to be practical exemplary embodiments, it is to be understood that the invention is not limited to the disclosed embodiments, but, on the contrary, You will understand. It is therefore to be understood that the above-described embodiments are illustrative in all aspects and not restrictive.

100: Excellent filtration device
110: filtration unit 120: first IoT sensing unit
130: control unit 140:
220: first IoT sensing unit 300: big data processing unit

Claims (5)

In the IoT intelligent monitoring system of the Big Data based superior filtration device,
A first IoT sensing unit provided in the superior filtration apparatus;
A second IoT sensing unit provided outside the superior filtration apparatus;
A big data processing unit for collecting and storing the sensing values obtained in the first and second IoT sensing units and analyzing the big data as the accumulated sensing values;
A control unit for determining a state of the extra filtration apparatus based on the big data analyzed by the big data processing unit; And
And a communication unit for transmitting a status signal to the user terminal based on the status of the exceptional filtering apparatus discriminated by the control unit,
Wherein the control unit learns by using a preset deep learning algorithm that targets whether or not to clean the excellent filtering apparatus by using the big data analyzed by the big data processing unit as an input value, Monitoring system. The method according to claim 1,
The first IoT sensing unit includes:
A weight sensor for measuring the weight of the filter net provided in the filtration unit; and a water level sensor for measuring the water level of the filtration unit, wherein the water level sensor measures the water level flowing into the filtration unit of the excellent filtration apparatus, IoT intelligent monitoring system of data-based superior filtration device. The method according to claim 1,
The second IoT sensing unit includes:
An IoT intelligent monitoring system of a Big Data based superfiltration device comprising a temperature sensor for measuring the temperature around the superfiltration device and a humidity sensor for measuring humidity. The method according to claim 1,
The big data processing unit,
Based on the first and second IoT sensing units, the sensing values obtained by the first and second IoT sensing units are periodically collected from the first and second IoT sensing units via the Bluetooth, the wireless LAN access point, or the IoT gateway, IoT intelligent monitoring system of filtration device. The method according to claim 1,
Wherein,
A deep-run module comprising an input layer, two or more hidden layers and an output layer,
IoT intelligent monitoring system of a Big Data based extreme filtration device that determines weights applied to each of the two or more hidden layers.
KR1020190047037A 2019-04-23 2019-04-23 Big-data based internet-of-things intelligent monitoring system of filtering device for rain water KR20190050745A (en)

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
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Publication number Priority date Publication date Assignee Title
KR102153829B1 (en) * 2019-09-30 2020-09-08 한국과학기술원 Iot gateway for controlling data reporting interval of iot terminal based on data prediction accuracy and operating method thereof
CN113655193A (en) * 2021-09-15 2021-11-16 陕西地建土地工程技术研究院有限责任公司 Intelligent monitoring system is handled to rainwater

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