CN110011994A - A kind of EMS based on big data - Google Patents
A kind of EMS based on big data Download PDFInfo
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- CN110011994A CN110011994A CN201910230740.7A CN201910230740A CN110011994A CN 110011994 A CN110011994 A CN 110011994A CN 201910230740 A CN201910230740 A CN 201910230740A CN 110011994 A CN110011994 A CN 110011994A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/02—Network architectures or network communication protocols for network security for separating internal from external traffic, e.g. firewalls
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/04—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks
- H04L63/0428—Network architectures or network communication protocols for network security for providing a confidential data exchange among entities communicating through data packet networks wherein the data content is protected, e.g. by encrypting or encapsulating the payload
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/12—Applying verification of the received information
- H04L63/123—Applying verification of the received information received data contents, e.g. message integrity
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
- H04L67/1097—Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
Abstract
The invention discloses a kind of EMS based on big data, the data acquisition module of the Data Detection terminal of the system obtains the environment measuring data of current environment by sensor；The data that first transmission module will acquire carry out encrypting and transmitting to cloud computing server；Received data are decrypted in the data decryption module of cloud computing server, and are sent to data pre-processing unit progress data and carry out cleaning and format conversion；Data memory module stores detection data；Data security module is for the data safety in maintenance data storage module；Data analysis module is analyzed according to the data being collected into, and is predicted using neural network environment；Data processing module generates instruction information according to data statistic analysis result；Intelligent terminal is connected to cloud computing server by the second transmission module, for the ambient conditions in display environment detection zone.System disclosed by the invention is conducive to carry out environment measuring science, safe and efficient management.
Description
Technical field
The present invention relates to EMS fields, and in particular to a kind of EMS based on big data.
Background technique
In recent years, with the raising of the development of social economy and industrial automatization, the operating of various mechanical equipments is public
Road motor vehicle is increasingly incremented by, and all the time all in burns gasoline or coal, discharges a large amount of nitrogen oxides, vulcanization to atmosphere
Object, coal dust cigarette.The pollutants such as various weather, haze PM2.5, CO, SO2, NO2, O3 gas make the trip of people, health
At very big puzzlement, environmental improvement is very urgent.
The development of internet makes big data technology suffer from significance in current many industries and work, and and
People's lives and closely bound up, the interwoveness that works, are also such for environment measuring work.Traditional information management
Mode cannot effectively meet the needs of environmental monitoring is to related data.Big data technology can not only promote environment measuring work
Make efficiency, while can also accurately environmental data be calculated and be analyzed, to provide accurate detection letter for testing staff
Breath guarantees that environment measuring work can effectively be carried out.
Summary of the invention
In order to overcome the problems, such as traditional approach to environment measuring, the present invention provides a kind of environment measurings based on big data
System.
A kind of EMS based on big data, the system include: Data Detection terminal, the first transmission module, cloud
Calculation server, the second transmission module and intelligent terminal, it is characterised in that:
Data Detection terminal: including power module, data acquisition module, data acquisition module is obtained currently in real time by sensor
The environment measuring data of environment；
First transmission module: the environment measuring data that Data Detection terminal is got are encrypted, which is sent
To cloud computing server；
Cloud computing server: including data decryption module, data pre-processing unit, data memory module, data security module, number
According to analysis module and data processing module, wherein the encryption data sent through transmission module is decrypted in data decryption module,
And it is sent to data pre-processing unit；Data pre-processing unit cleans the current environment detection data received, rejects
Invalid data, and by the data conversion after cleaning at unified format；Data memory module stores history environment detection data sum number
The data that Data preprocess unit is sent；Data security module includes firewall and Network Security Device, is used for maintenance data storage
Data safety in module, and prevent distorting and stealing to data；Data analysis module divides according to the data being collected into
Analysis forms data statistic analysis as a result, and predicting using neural network environment；Data processing module, according to the number
Analysis result generates instruction information according to statistics；
Intelligent terminal: cloud computing server is connected to by the second transmission module, for the environment in display environment detection zone
Situation.
Further, the data analysis module includes: the shared analysis mould of big data based on Recognition with Recurrent Neural Network
Type, the big data share analysis model using the environment measuring data of acquisition as neural network input, using prediction result as
Output constructs Recognition with Recurrent Neural Network prediction model, and the Recognition with Recurrent Neural Network includes input layer, hidden layer and output layer.
Recognition with Recurrent Neural Network prediction model building specifically: give embedded vector time series,
Subscript indicates the time sequencing of embedded vector, input vectorWith last hidden layer vectorCombine to obtain current
Hidden layer vector, calculation formula is as follows:
The output layer of network uses linear structure, and calculation formula is as follows:
In formula:For activation primitive, Logistic regression function is used herein, it may be assumed that
In formula: vector u, v and matrix w are the parameter to be learnt in network.
Further, the Recognition with Recurrent Neural Network model includes: 1) achievement data pretreatment: being examined to different types of environment
Measured data is classified by the difference of physical significance, dimension and the order of magnitude, and initial data is normalized；2)
Achievement data input: using pretreated data as the input of neural network；3) training sample is formulated: with current acquisition time
The data of section are as a cycle, as the training sample of neural network, so that the air quality index to next period carries out
Forecast test；4) it carries out network training: air quality index prediction, setting is carried out using the neural network of single hidden layer or more hidden layers
Desired value, and the air quality index of prediction result is exported as output valve；5) prediction result is analyzed: passing through nerve net
Network predicts next circulated air quality, and makes prediction curve value and compare with actual value progress registration, obtains prediction accuracy.
Further, the mode that the data are decrypted are as follows: parse the encrypted packet to obtain the first data；It is right
First data are decrypted to obtain the second data；Second data are re-grouped package to obtain target data
Packet.
Further, the data acquisition module includes: PM sensor of dust concentration, hazardous gas inspection sensor, warm and humid
Spend sensor, baroceptor, PM sensor of dust concentration.
Further, the power module includes lithium electrical storage cell, DC/AC inverter, solar panel and protection
Element.
Further, the transmission module includes short range measuring terminal network and remote wireless network, the short range metering
Terminal network is transmitted using electric force carrier transmission or WIFI, and the remote wireless network is transmitted using long range point-to-point type.
Further, the Data Detection terminal is electrically connected with video collector, and video collector is also electrically connected with
Camera, if the bad environments in the region, administrative staff can remotely control microprocessor by operation module, then micro- place
It manages device control camera and video record is carried out to the region, after the completion, again in remote transmission to central processing unit, for management
Personnel's viewing, to make corresponding processing.
Further, data sheet display module, operation monitoring data display module are set in the intelligent terminal, in inspection
Hold logging modle, inspection to check card module, alarm modules.
The invention has the advantages that: the EMS provided by the invention based on big data, can to environmental data into
Row real-time detection is handled and is analyzed to the environmental data detected, and predicts FUTURE ENVIRONMENT index.The system is to getting
Environmental data cleaned, get rid of some abnormal datas, improve forecasting accuracy.The system has information encryption reconciliation
Close module, additionally it is possible to data be encrypted, prevent data from being attacked, distorted and stolen, improve the overall security of system.
Detailed description of the invention
Technical solution of the present invention is described in detail below in conjunction with attached drawing, so that characteristics and advantages of the invention are more
It is obvious.
Fig. 1: the schematic diagram of big data EMS of the invention；
Fig. 2: the schematic diagram of neural network of the invention；
Fig. 3: the schematic diagram of power module of the invention；
Fig. 4: Recognition with Recurrent Neural Network timeline expanded view of the invention.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiment is section Example of the present invention, and not all embodiment.Based in the present invention
Embodiment, every other embodiment obtained by those of ordinary skill in the art without making creative efforts,
It shall fall within the protection scope of the present invention.
Fig. 1 is a kind of EMS schematic diagram of big data proposed by the present invention, as shown in Figure 1, the system includes:
Data Detection terminal, the first transmission module, cloud computing server, the second transmission module and intelligent terminal.Data Detection terminal packet
Power module, data acquisition module are included, data acquisition module obtains the environment measuring data of current environment by sensor in real time；
Transmission module encrypts the environment measuring data that Data Detection terminal is got, which is sent to cloud computing
Server.
Cloud computing server: including data decryption module, data pre-processing unit, data memory module, data safety mould
Block, data analysis module and data processing module, wherein data decryption module carries out the encryption data sent through transmission module
Decryption, and it is sent to data pre-processing unit；Data pre-processing unit cleans the current environment detection data received,
Invalid data is rejected, and by the data conversion after cleaning at unified format；Data memory module stores history environment detection data
The data sent with data pre-processing unit；Data security module includes firewall and Network Security Device, for safeguarding data
Data safety in memory module, and prevent distorting and stealing to data；Data analysis module to according to the data that are collected into
Row analysis forms data statistic analysis as a result, and predicting using neural network environment；Data processing module, according to institute
It states data statistic analysis result and generates instruction information；Intelligent terminal: cloud computing server is connected to by transmission module, for showing
Show the ambient conditions in environment measuring region.
The environmental data in the real-time Acquisition Detection region of Data Detection terminal, and cloud computing service is sent to by transmission module
Device, cloud computing server form data statistic analysis result and indication information by analysis, processing, and intelligent terminal is passed by second
Defeated module accesses the data information in cloud computing server.
As shown in Fig. 2, the data analysis module is realized based on Recognition with Recurrent Neural Network, Recognition with Recurrent Neural Network
(RNN) it is depth network that one kind can be used for unsupervised (and having supervision) study, depth even can achieve and list entries
Length is consistent, and under unsupervised learning mode, RNN is used to the data sequence following according to previous data sample prediction, and
And classification information is not used in learning process, therefore RNN is very suitable to sequence data modeling.
As shown in Fig. 2, Recognition with Recurrent Neural Network used in this programme is divided into input layer, hidden layer and output layer, hidden layer it
Between node be no longer connectionless but have connection, and hidden layer input not only including input layer output further include on
The output of one moment hidden layer.After Recognition with Recurrent Neural Network structure expansion shown in Fig. 2, as shown in figure 3, by the environment measuring of acquisition
Data are inputted as neural network, are labeled as.Using the environmental data in next period as neural network
Output, is labeled as.The hidden unit of RNN is labeled as。
In conjunction with Fig. 3 it is found that by taking t moment as an example, Zong Xiangshang, the information flow of an one-way flow is reached from input unit
Hidden unit, environment measuring data xt is input in neural network；In transverse direction, the input of hidden layer further includes previous moment
Hidden layer export st-1, i.e. st is the hidden unit output st-1 calculating in conjunction with current observation data xt and previous moment
It obtains；The information flow of another longitudinal one-way flow reaches output unit from hidden unit, it can counts from hidden unit st
Calculation obtains the output ot of network, therefore the output of t moment is codetermined by the state of current input and previous moment.Together
The hidden unit output st of reason, the moment can equally be transmitted to subsequent time, codetermine st+1 with xt+1.
Recognition with Recurrent Neural Network prediction model building specifically: give embedded vector time series
, subscript indicates the time sequencing of embedded vector, input vectorWith last hidden layer vectorCombine to obtain current
Hidden layer vector, calculation formula is as follows:
The output layer of network uses linear structure, and calculation formula is as follows:
In formula:For activation primitive, Logistic regression function is used herein, it may be assumed that
In formula: vector u, v and matrix w are the parameter to be learnt in network.
Further, the data analysis module steps flow chart include: 1) achievement data input: with environment measuring data into
The input pointer of row neural network；2) achievement data is handled: to different types of input pointer, by physical significance, dimension and
The difference of the order of magnitude is classified, and initial data is normalized；3) training sample is formulated: with current acquisition time
The data of section are as a cycle, as the training sample of neural network, so that the air quality index to next period carries out
Forecast test；4) it carries out network training: air quality index prediction, setting is carried out using the neural network of single hidden layer or more hidden layers
Desired value, and the air quality index of predetermined period is exported as output valve；5) prediction result is analyzed: passing through nerve net
Network predicts next circulated air quality, and makes prediction curve value and compare with actual value progress registration, obtains prediction accuracy.
Research indicates that the discharge of dust, industrial waste gas and vehicle exhaust causes serious pollution to atmosphere.Thus judge
Relation factor SO2, NO2, PM2.5, PM10 of predicted value out, air quality index etc..But for a neural network,
It is not that input pointer is The more the better, it is more that model can be made to be more prone to produce over-fitting instead or keep the training time excessively unrestrained
It is long.Comprehensively consider the factor of various aspects, the input pointer that this programme selects is history PM2.5, air quality index and control enterprise
Industry electricity, output are to predict the air quality index of day.
The data acquisition module include: PM sensor of dust concentration, hazardous gas inspection sensor, Temperature Humidity Sensor,
Baroceptor, PM sensor of dust concentration.
As shown in figure 4, the power module includes lithium electrical storage cell, DC/AC inverter, solar panel and protection
Element.
The transmission module includes short range measuring terminal network and remote wireless network, and the short range measuring terminal network is adopted
It is transmitted with electric force carrier transmission or WIFI, the remote wireless network is transmitted using long range point-to-point type.
In order to guarantee the safety of data that Data Detection terminal is got, the data of capture can be encrypted, data
Deciphering module parses the encrypted packet to obtain the first data；First data are encrypted or decrypted to obtain
Two data；Second data are re-grouped package to obtain target packet.
The Data Detection terminal is also electrically connected with video collector, and video collector is also electrically connected with camera,
If the bad environments in the region, administrative staff can remotely control microprocessor, then microprocessor control by operation module
Camera processed carries out video record to the region, after the completion, again in remote transmission to central processing unit, for administrative staff's sight
It sees, to make corresponding processing.
Data sheet display module, operation monitoring data display module, inspection content record mould are set in the intelligent terminal
Block, inspection are checked card module, alarm modules.
Although present disclosure is as above, present invention is not limited to this.Anyone skilled in the art are not departing from this
It in the spirit and scope of invention, can make various changes or modifications, therefore protection scope of the present invention should be with claim institute
Subject to the range of restriction.
Claims (9)
1. a kind of EMS based on big data, which includes: Data Detection terminal, the first transmission module, cloud meter
Calculate server, the second transmission module and intelligent terminal, it is characterised in that:
Data Detection terminal: including power module, data acquisition module, data acquisition module is obtained currently in real time by sensor
The environment measuring data of environment；
First transmission module: the environment measuring data that Data Detection terminal is got are encrypted, which is sent
To cloud computing server；
Cloud computing server: including data decryption module, data pre-processing unit, data memory module, data security module, number
According to analysis module and data processing module, wherein the encryption data sent through transmission module is decrypted in data decryption module,
And it is sent to data pre-processing unit；Data pre-processing unit cleans the current environment detection data received, rejects
Invalid data, and by the data conversion after cleaning at unified format；Data memory module stores history environment detection data sum number
The data that Data preprocess unit is sent；Data security module includes firewall and Network Security Device, is used for maintenance data storage
Data safety in module, and prevent distorting and stealing to data；Data analysis module divides according to the data being collected into
Analysis forms data statistic analysis as a result, and predicting using neural network environment；Data processing module, according to the number
Analysis result generates instruction information according to statistics；
Intelligent terminal: cloud computing server is connected to by the second transmission module, for the environment in display environment detection zone
Situation.
2. the EMS according to claim 1 based on big data, data analysis module includes: to recycle nerve
Big data based on network shares analysis model, the big data share analysis model using the environment measuring data of acquisition as
Neural network input, using prediction result as export, building Recognition with Recurrent Neural Network prediction model, specifically: give it is embedded to
Measure time series, subscript indicates the time sequencing of embedded vector, input vectorWith the last time
Hidden layer vectorCombine to obtain current hidden layer vector, calculation formula is as follows:
The output layer of network uses linear structure, and calculation formula is as follows:
In formula:For activation primitive, Logistic regression function is used herein, it may be assumed that
In formula: vector u, v and matrix w are the parameter to be learnt in network.
3. the EMS according to claim 2 based on big data, 1) the Recognition with Recurrent Neural Network model includes:
Achievement data pretreatment: to different types of environment measuring data, divided by the difference of physical significance, dimension and the order of magnitude
Grade, and initial data is normalized；2) achievement data inputs: using pretreated data as the defeated of neural network
Enter；3) training sample is formulated: using the data of current acquisition time section as a cycle, as the training sample of neural network,
So that the air quality index to next period carries out forecast test；4) network training is carried out: using single hidden layer or more hidden layers
Neural network carries out air quality index prediction, sets desired value, and using the air quality index of prediction result as output valve
It is exported；5) prediction result is analyzed: by the lower circulated air quality of neural network prediction, and making prediction curve value and reality
Actual value carries out registration comparison, obtains prediction accuracy.
4. the EMS according to claim 1 based on big data, the mode that the data are decrypted are as follows: solution
The encrypted packet is analysed to obtain the first data；First data are decrypted to obtain the second data；To described
Two data are re-grouped package to obtain target packet.
5. the EMS according to claim 1 based on big data, the data acquisition module includes: PM dust
Concentration sensor, hazardous gas examine sensor, Temperature Humidity Sensor, baroceptor, PM sensor of dust concentration.
6. the EMS according to claim 1 based on big data, power module include lithium electrical storage cell,
DC/AC inverter, solar panel and protection element.
7. the EMS according to claim 1 based on big data, the transmission module includes that short range metering is whole
Network and remote wireless network are held, the short range measuring terminal network is transmitted using electric force carrier transmission or WIFI, described long-range
Wireless network is transmitted using long range point-to-point type.
8. the EMS according to claim 1 based on big data, Data Detection terminal are electrically connected with video
Collector, video collector are also electrically connected with camera, if the bad environments in the region, administrative staff can pass through operation
Module remotely controls microprocessor, and then microprocessor control camera carries out video record to the region, after the completion, again far
Journey is transmitted in central processing unit, for administrative staff's viewing, to make corresponding processing.
9. the EMS according to claim 1 based on big data, it is aobvious that data sheet is set in the intelligent terminal
Show that module, operation monitoring data display module, inspection content record module, inspection are checked card module, alarm modules.
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| CN201910230740.7A CN110011994A (en) | 2019-03-26 | 2019-03-26 | A kind of EMS based on big data |
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| CN110987081A (en) * | 2019-12-20 | 2020-04-10 | 云南方源科技有限公司 | Outdoor environment detection system |
| CN111157682A (en) * | 2020-01-06 | 2020-05-15 | 上海应用技术大学 | Air quality monitoring and predicting system and method |
| CN112097822A (en) * | 2020-07-10 | 2020-12-18 | 上海悠络客电子科技股份有限公司 | Real-time system based on environment big data |
| CN113011092A (en) * | 2021-03-15 | 2021-06-22 | 广东电网有限责任公司清远供电局 | Meteorological environment monitoring method, system, electronic equipment and storage medium |
| CN113110387A (en) * | 2021-04-20 | 2021-07-13 | 上海市环境科学研究院 | Environment-friendly intelligent diagnosis system, method and storage medium |
| CN115438073A (en) * | 2022-09-06 | 2022-12-06 | 广西柳州晨生信息科技有限公司 | Big data information analysis system based on cloud computing |
| CN116032668A (en) * | 2023-03-29 | 2023-04-28 | 广东维信智联科技有限公司 | Computer network data security system |
| CN116707146A (en) * | 2023-08-08 | 2023-09-05 | 深圳航天科创泛在电气有限公司 | Intelligent monitoring method and related equipment for photovoltaic power generation and energy storage system |
| CN117097592A (en) * | 2023-10-20 | 2023-11-21 | 南京科控奇智能科技有限公司 | Edge computing gateway based on cloud computing |
| CN117111540A (en) * | 2023-10-25 | 2023-11-24 | 南京德克威尔自动化有限公司 | Environment monitoring and early warning method and system for IO remote control bus module |
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| CN110987081A (en) * | 2019-12-20 | 2020-04-10 | 云南方源科技有限公司 | Outdoor environment detection system |
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| CN113011092A (en) * | 2021-03-15 | 2021-06-22 | 广东电网有限责任公司清远供电局 | Meteorological environment monitoring method, system, electronic equipment and storage medium |
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| CN116707146A (en) * | 2023-08-08 | 2023-09-05 | 深圳航天科创泛在电气有限公司 | Intelligent monitoring method and related equipment for photovoltaic power generation and energy storage system |
| CN116707146B (en) * | 2023-08-08 | 2024-01-23 | 深圳航天科创泛在电气有限公司 | Intelligent monitoring method and related equipment for photovoltaic power generation and energy storage system |
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| CN117111540A (en) * | 2023-10-25 | 2023-11-24 | 南京德克威尔自动化有限公司 | Environment monitoring and early warning method and system for IO remote control bus module |
| CN117111540B (en) * | 2023-10-25 | 2023-12-29 | 南京德克威尔自动化有限公司 | Environment monitoring and early warning method and system for IO remote control bus module |
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Application publication date: 20190712 |