CN108600332A - A kind of pollution of waterhead data processing system based on block chain technology - Google Patents
A kind of pollution of waterhead data processing system based on block chain technology Download PDFInfo
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- CN108600332A CN108600332A CN201810284502.XA CN201810284502A CN108600332A CN 108600332 A CN108600332 A CN 108600332A CN 201810284502 A CN201810284502 A CN 201810284502A CN 108600332 A CN108600332 A CN 108600332A
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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
- H04L67/02—Protocols based on web technology, e.g. hypertext transfer protocol [HTTP]
- H04L67/025—Protocols based on web technology, e.g. hypertext transfer protocol [HTTP] for remote control or remote monitoring of applications
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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
- H04L63/08—Network architectures or network communication protocols for network security for authentication of entities
- H04L63/0823—Network architectures or network communication protocols for network security for authentication of entities using certificates
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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
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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
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- 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]
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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
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/18—Water
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/23—Clustering techniques
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A20/00—Water conservation; Efficient water supply; Efficient water use
- Y02A20/20—Controlling water pollution; Waste water treatment
Abstract
The present invention provides a kind of pollution of waterhead data processing systems based on block chain technology, including headend, wireless sensor network and the data check center being made of multiple data check nodes；Wireless sensor network is for being monitored pollution of waterhead, obtaining pollution of waterhead concentration data and being sent to headend；Headend is forwarded to the data check center after the pollution of waterhead concentration data that receives that treated；Multiple data check nodes in data check center are responsible for that the pollution of waterhead concentration data that the headend forwards is verified and preserved；Each data check node is block chain node, and multiple data check nodes form a distributed data base；Further include data processing centre, data processing centre for pre-processing the pollution of waterhead concentration data after verification successively, clustering processing and outlier detection are handled, and database is stored in after the abnormal point detected is marked.
Description
Technical field
The present invention relates to air monitering technical fields, and in particular at a kind of pollution of waterhead data based on block chain technology
Reason system.
Background technology
Through the method frequently with manual sampling lab analysis when being monitored in the prior art to pollution of waterhead.This side
Method can only obtain the monitor value in certain time in pollution of waterhead monitoring region, can not be monitored in real time, monitoring result is by people
For influence it is very big.
Internet of Things needs the various needs of object of monitoring, connection, interaction by various information sensing devices, in real time acquisition
Information is combined the huge network to be formed with internet.The purpose is to realize object and object, object and people, all article and net
The connection of network facilitates identification, management and control.Operation related with data all is being carried out all the time in Internet of things system,
Including links such as data acquisition, data transmission and data storages.Data are easy to be by malicious attack and non-in each link
Method distorts operation.Link is acquired in data, illegal node can pretend to be or attack legitimate node to carry out illegal sensing data
It uploads；In data transmission link, on the one hand it may cause error code since channel quality is bad, on the other hand since data are being transmitted
The data for being easy to be eventually led to by malicious modification upload in the process are illegal etc..Therefore, advance row data check is stored in data
It is essential operation.The purpose of data check be in order to prevent illegal node pretend to be with attack, prevent data and exist
Be maliciously tampered in transmission process, ensure authenticity, legitimacy and the integrality of data.
Invention content
In view of the above-mentioned problems, the present invention provides a kind of pollution of waterhead data processing system based on block chain technology.
The purpose of the present invention is realized using following technical scheme：
Provide a kind of pollution of waterhead data processing system based on block chain technology, including headend, wireless biography
Sensor network and the data check center being made of multiple data check nodes；The wireless sensor network is used for water
Source pollution is monitored, and is obtained pollution of waterhead concentration data and is sent to headend；The headend is receiving
After treated the pollution of waterhead concentration data, it is forwarded to the data check center；It is more in the data check center
A data check-node is responsible for that the pollution of waterhead concentration data that the headend forwards is verified and preserved；Respectively
The data check node is block chain node, and multiple data check nodes form a distributed data base；Further include
The data processing centre being connect with data check center, the data processing centre are used for the pollution of waterhead concentration numbers after verification
According to pre-processed successively, clustering processing and outlier detection processing, be stored in data after the abnormal point detected is marked
Library.
Preferably, the wireless sensor network includes base station and multiple sensor nodes, and sensor node is for adopting
Collect water source pollution concentration data, and the pollution of waterhead concentration data of acquisition is transmitted to base station by parallel multipath routing mode；
Base station receives and the pollution of waterhead concentration data of processing sensor node output, and pollution of waterhead concentration data passes by treated
Transport to headend.
Further, system further includes authentication center, authentication center to the headend, the sensor node,
Base station and the data check node carry out authorization identifying.
Preferably, sensor node becomes legal sensor node after the authorization identifying by authentication center, and obtains
Unique sensor node digital certificate and symmetric key；Base station becomes legal base after the authorization identifying by authentication center
It stands, and obtains unique base station digital certificate and symmetric key；The headend is in the authorization identifying by authentication center
Afterwards, unique headend digital certificate and symmetric key are obtained；The data check node is in awarding by authentication center
Become valid data check-node after weighing certification, and obtains unique public key, private key, data check node digital certificate and symmetrical
Key；The public key, for wide to the data check center and the wireless sensor network by the headend
It broadcasts；The private key, for by artificially being shared between the data check node.
Beneficial effects of the present invention are：Pollution of waterhead concentration data is obtained using wireless sensor network technology, is not necessarily to cloth
Line uses manpower and material resources sparingly, and scalability is good, is suitble to the large-scale monitoring system of structure, is suitble to promote and apply；Utilize data check
Node completes data check task, and verifying work is distributed to check-node from headend, can overcome due to verification
Task is excessively concentrated and the problems such as the verification efficiency brought is low, speed is slow, propagation delay time is high, vulnerable.
Description of the drawings
Using attached drawing, the invention will be further described, but the embodiment in attached drawing does not constitute any limit to the present invention
System, for those of ordinary skill in the art, without creative efforts, can also obtain according to the following drawings
Other attached drawings.
Fig. 1 is the system structure connection block diagram of an illustrative embodiment of the invention；
Fig. 2 is the structural schematic diagram of the data processing centre of an illustrative embodiment of the invention.
Reference numeral：
Headend 1, wireless sensor network 2, data check center 3, data processing centre 4, preprocessing module 10,
Clustering processing module 20, outlier detection module 30, database 40.
Specific implementation mode
The invention will be further described with the following Examples.
Referring to Fig. 1, a kind of pollution of waterhead data processing system based on block chain technology, including number are present embodiments provided
According to transponder 1, wireless sensor network 2 and the data check center 3 being made of multiple data check nodes；Described is wireless
Sensor network 2 is for being monitored pollution of waterhead, obtaining pollution of waterhead concentration data and being sent to headend 1；Institute
Headend 1 is stated after the pollution of waterhead concentration data that receives that treated, is forwarded to the data check center 3；
Multiple data check nodes in the data check center 3 are responsible for the pollution of waterhead forwarded to the headend 1
Concentration data is verified and is preserved；Each data check node is block chain node, multiple data check node groups
At a distributed data base.
Wherein, the wireless sensor network 2 includes base station and multiple sensor nodes, and sensor node is for acquiring
Pollution of waterhead concentration data, and the pollution of waterhead concentration data of acquisition is transmitted to base station by parallel multipath routing mode；Base
It stands and receives and handle the pollution of waterhead concentration data that sensor node exports, and pollution of waterhead concentration data transmits by treated
To headend 1.
Wherein, the pollution of waterhead concentration data includes the concentration data of each pollution element, and pollution element includes sodium, silicon
The element of equal polluted sources.
Further, as shown in Figure 1 and Figure 2, system further includes the data processing centre 4 being connect with data check center 3,
The data processing centre 4 for being pre-processed successively to the pollution of waterhead concentration data after verification, clustering processing and exception
Point detection process, database is stored in after the abnormal point detected is marked.The data processing centre 4 includes being sequentially connected
Preprocessing module 10, clustering processing module 20, outlier detection module 30 and database 40；Preprocessing module 10 is used for school
Pollution of waterhead concentration data after testing is pre-processed；Clustering processing module 20 is used for pretreated pollution of waterhead concentration numbers
According to progress clustering processing；Outlier detection module 30 is used to carry out at outlier detection the pollution of waterhead concentration data after cluster
Reason is stored in database 40 after the abnormal point detected is marked.
Further, system further includes authentication center, authentication center to the headend 1, the sensor node,
Base station and the data check node carry out authorization identifying.In one embodiment, sensor node is passing through authentication center
Become legal sensor node after authorization identifying, and obtains unique sensor node digital certificate and symmetric key；Base station exists
By becoming legitimate base station after the authorization identifying of authentication center, and obtain unique base station digital certificate and symmetric key；It is described
Headend 1 obtains 1 digital certificate of unique headend and symmetrical close after the authorization identifying by authentication center
Key；The data check node becomes valid data check-node after the authorization identifying by authentication center, and obtains unique
Public key, private key, data check node digital certificate and symmetric key；The public key, for by the headend 1 to
The data check center 3 and the wireless sensor network 2 are broadcasted；The private key, for by artificially in the data school
It tests between node and shares.
The above embodiment of the present invention obtains pollution of waterhead concentration data using wireless sensor network technology, without connecting up,
It uses manpower and material resources sparingly, scalability is good, is suitble to the large-scale monitoring system of structure, is suitble to promote and apply；Utilize data check section
It puts to complete data check task, verifying work is distributed to check-node from headend 1, can overcome since verification is appointed
Business is excessively concentrated and the problems such as the verification efficiency brought is low, speed is slow, propagation delay time is high, vulnerable.
In one embodiment, preprocessing module 10 is for pre-processing pollution of waterhead concentration data, specially：It is right
There are the pollution of waterhead concentration datas of 0 value or negative value to be pre-processed, and 0 value or negative value are replaced with preset substitution value.
The present embodiment can prevent 0 value in pollution of waterhead concentration data or negative value to subsequent pollution of waterhead concentration data clustering processing
It impacts.
In one embodiment, clustering processing module 20 is for gathering pretreated pollution of waterhead concentration data
Class specifically includes：
(1) the pollution of waterhead concentration data of pretreated set period of time is extracted as a pollution of waterhead concentration data
Collection, is set as Y, builds the arest neighbors set of each pollution of waterhead concentration data：To the arbitrary water in pollution of waterhead concentration data collection Y
Source pollution concentration data yi, calculate yiWith the similarity of remaining pollution of waterhead concentration data in pollution of waterhead concentration data collection Y, root
It is ranked up according to the ascending sequence of similarity, μ pollution of waterhead concentration data is as y before selectingiArest neighbors, build water
Source pollution concentration data yiArest neighbors set Wyi, arest neighbors set WyiDescribed in μ pollution of waterhead concentration data according to European
It is ranked up apart from ascending sequence, the pollution of waterhead concentration data by sequence the ρ position is assigned a value of ρ；
(2) in first time iteration, select first unlabelled pollution of waterhead in pollution of waterhead concentration data collection Y dense
Degrees of data is as first cluster central point O1, calculate remaining pollution of waterhead concentration data and cluster central point O1Between it is similar away from
From according to similarity distance distribution principle to pollution of waterhead concentration data yiIt is allocated operation；
(3) it enables iterations λ add 1, selects first unlabelled pollution of waterhead in pollution of waterhead concentration data collection Y dense
Degrees of data is as another cluster central point Oλ+1, calculate remaining pollution of waterhead concentration data and cluster central point Oλ+1Between it is similar
Distance, if pollution of waterhead concentration data yjIt is unmarked, according to similarity distance distribution principle to pollution of waterhead concentration data yjDivided
With operation；If pollution of waterhead concentration data yjIt is marked and can be assigned to cluster central point O according to similarity distance distribution principleλ+1, than
Compared with cluster central point, the cluster central point O of itself and original distributionλ+1Between similarity distance, select similarity distance bigger cluster central point add
Enter cluster；
(4) repeat (3) until iterations λ reach setting threshold value or all pollution of waterhead concentration datas all by
Label.
Wherein, similarity distance distribution principle is：If pollution of waterhead concentration data yiWith between the cluster central point that newly selects
Similarity distance threshold value Z of the similarity distance no more than settingT, not to pollution of waterhead concentration data yiIt is allocated operation；If water source is dirty
Contaminate concentration data yiIt is more than the similarity distance threshold value Z of setting with the similarity distance between the cluster central point that newly selectsT, continue to calculate
Pollution of waterhead concentration data yiWith the similarity distance between the pollution of waterhead concentration data in the arest neighbors set of the cluster central point,
If pollution of waterhead concentration data yiBetween a pollution of waterhead concentration data in the arest neighbors set of the cluster central point, meet
Similarity distance is more than the similarity distance threshold value Z of settingT, then by pollution of waterhead concentration data yiIt is assigned to the cluster central point, and is carried out
Label.
The present embodiment is set carries out clustering processing to the pretreated pollution of waterhead concentration data of data pre-processing unit
Specific mechanism, which can quickly and easily complete the cluster of pollution of waterhead concentration data, need not preassign cluster
Number, wherein innovatively setting similarity distance distribution principle so that only when pollution of waterhead concentration data and cluster central point phase
Like and to one or more of the arest neighbors set of cluster central point pollution of waterhead concentration data it is similar when, pollution of waterhead concentration numbers
According to that could be located at the same cluster with cluster central point, thus relative to traditional clustering algorithm based on similarity, the present embodiment is adopted
With stronger restrictive condition, more suitable for detecting any shape cluster, cluster is efficiently and quality is high.
Wherein, set the calculation formula of the similarity distance between two pollution of waterhead concentration datas as：
In formula, Z (yi,yl) indicate pollution of waterhead concentration data yiWith ylBetween similarity distance, Dyi(yl)Indicate yiIn yl's
Arest neighbors set WylIn position assignment, ifThen assignment Dyi(yl)=ZT；Dyl(yi)Indicate ylIn yiArest neighbors set
WyiIn position assignment, ifThen assignment Dyl(yi)=ZT。
When weighing the distance between two pollution of waterhead concentration datas in the prior art, most common metric form is absolute
Distance, such as Euclidean distance, manhatton distance.The present embodiment innovatively sets a kind of new similarity distance measure formulas,
Relative to absolute distance, the density that can adapt to pollution of waterhead concentration data concentration automatically becomes the calculated similarity distance of the formula
Change so that cluster operation can adapt to the cluster in different densities and scale.
Wherein, the similarity between two pollution of waterhead concentration datas may be used existing similarity function and be counted
It calculates, is measured for example, by using cosine similarity, Pearson correlation coefficient etc..In a preferred embodiment, two water are set
The calculation formula of similarity between the pollution concentration data of source is：
In formula, L (yi,yj) indicate pollution of waterhead concentration data yiWith pollution of waterhead concentration data yjBetween similarity, yiα
Indicate pollution of waterhead concentration data yiα dimension attribute values, yjαIndicate pollution of waterhead concentration data yjα dimension attribute values, β is
The dimension of pollution of waterhead concentration data, U1(yiα,yjα) be setting be minimized function, work as yiα≤yjα, U1(yiα,yjα)=
yiα, work as yiα>yjα, U1(yiα,yjα)=yjα；U2(yiα,yjα) be setting be maximized function, work as yiα<yjα, U2(yiα,yjα)=
yjα, work as yiα≥yjα, U2(yiα,yjα)=yiα。
The present embodiment innovatively sets the calculation formula of similarity, it is proposed that a kind of new measuring similarity mechanism,
The similarity obtained by the calculation formula weighs the similitude between two pollution of waterhead concentration datas, enables to similar
The calculating of degree is not influenced by the dimension of pollution of waterhead concentration data, to avoid any unnecessary data conversion so that right
The cluster of pollution of waterhead concentration data is simpler quick.
In one embodiment, the pollution of waterhead concentration data to after clustering processing carries out outlier detection, specifically
Including：
It (1), should if there are the number threshold value that the pollution of waterhead concentration data number of a cluster is less than setting after cluster
Cluster is considered as abnormal clusters, and all pollution of waterhead concentration datas in abnormal clusters are considered as abnormal pollution of waterhead concentration data；
(2) similarity distance between the cluster central point of other normal clusters and the cluster central point of abnormal clusters is calculated；
(3) it is set if being not more than there are the similarity distance between the cluster central point and the cluster central point of normal clusters of an abnormal clusters
Fixed cluster similarity distance threshold value then using the normal clusters as cluster to be detected, and utilizes the pollution of waterhead concentration data of the abnormal clusters
The pollution of waterhead concentration data in cluster to be detected is detected, if the pollution of waterhead concentration data collection of the abnormal clusters is combined into Ys={ y1,
y2,..,ys, as the pollution of waterhead concentration data y in cluster to be detectedxWhen meeting exceptional condition, by pollution of waterhead concentration data yx
It is considered as abnormal pollution of waterhead concentration data.
Due to comparatively loose between the pollution of waterhead concentration data in the smaller cluster of scale, and relative to other
Pollution of waterhead concentration data is more isolated, therefore the data in the cluster of scale is smaller are usually considered as abnormal number in the prior art
According to.Based on this, the present embodiment carries out outlier detection to the pollution of waterhead concentration data after clustering processing, by the cluster of scale is smaller
It is considered as abnormal clusters, all pollution of waterhead concentration datas in abnormal clusters is considered as abnormal pollution of waterhead concentration data, has certain
Theoretical property.
Wherein, set exceptional condition as：
In formula, WyxFor pollution of waterhead concentration data yxArest neighbors set, WyθFor pollution of waterhead concentration data YsIt is nearest
Neighbour's set, yθ∈Ys, | Wyx∩Wyθ| indicate WyxWith WyθIntersection in pollution of waterhead concentration data number, N be setting number
Threshold value.
The present embodiment is innovatively proposed for detecting whether pollution of waterhead concentration data is abnormal exceptional condition, should
Exceptional condition is according to the water source of the arest neighbors set between pollution of waterhead concentration data and the pollution of waterhead concentration data of abnormal clusters
Pollution concentration data intersection quantity judges whether the pollution of waterhead concentration data is abnormal pollution of waterhead concentration data, has one
Fixed accuracy of detection, detection mode is simple and effective and is not influenced by pollution of waterhead concentration data dimension.
Finally it should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention, rather than the present invention is protected
The limitation of range is protected, although being explained in detail to the present invention with reference to preferred embodiment, those skilled in the art answer
Work as understanding, technical scheme of the present invention can be modified or replaced equivalently, without departing from the reality of technical solution of the present invention
Matter and range.
Claims (6)
1. a kind of pollution of waterhead data processing system based on block chain technology, characterized in that including headend, wireless biography
Sensor network and the data check center being made of multiple data check nodes；The wireless sensor network is used for water
Source pollution is monitored, and is obtained pollution of waterhead concentration data and is sent to headend；The headend is receiving
After treated the pollution of waterhead concentration data, it is forwarded to the data check center；It is more in the data check center
A data check-node is responsible for that the pollution of waterhead concentration data that the headend forwards is verified and preserved；Respectively
The data check node is block chain node, and multiple data check nodes form a distributed data base；Further include
The data processing centre being connect with data check center, the data processing centre are used for the pollution of waterhead concentration numbers after verification
According to pre-processed successively, clustering processing and outlier detection processing, be stored in data after the abnormal point detected is marked
Library.
2. a kind of pollution of waterhead data processing system based on block chain technology according to claim 1, characterized in that institute
The wireless sensor network stated includes base station and multiple sensor nodes, and sensor node is for acquiring pollution of waterhead concentration numbers
According to, and the pollution of waterhead concentration data of acquisition is transmitted to base station by parallel multipath routing mode；Base station receives and processing passes
The pollution of waterhead concentration data of sensor node output, and pollution of waterhead concentration data is transmitted to headend by treated.
3. a kind of pollution of waterhead data processing system based on block chain technology according to claim 2, characterized in that also
Including authentication center, authentication center to the headend, the sensor node, base station and the data check node into
Row authorization identifying.
4. a kind of pollution of waterhead data processing system based on block chain technology according to claim 1, characterized in that pass
Sensor node becomes legal sensor node after the authorization identifying by authentication center, and obtains unique sensor node number
Word certificate and symmetric key；Base station becomes legitimate base station after the authorization identifying by authentication center, and obtains unique base station
Digital certificate and symmetric key；The headend obtains unique data and turns after the authorization identifying by authentication center
Send out device digital certificate and symmetric key；The data check node becomes valid data after the authorization identifying by authentication center
Check-node, and obtain unique public key, private key, data check node digital certificate and symmetric key；The public key, for leading to
The headend is crossed to broadcast to the data check center and the wireless sensor network；The private key, for passing through
Artificially shared between the data check node.
5. according to a kind of pollution of waterhead data processing system based on block chain technology of claim 1-4 any one of them,
Be characterized in, the data processing centre include sequentially connected preprocessing module, clustering processing module, outlier detection module and
Database；Preprocessing module is for pre-processing the pollution of waterhead concentration data after verification；Clustering processing module for pair
Pretreated pollution of waterhead concentration data carries out clustering processing；Outlier detection module is for dense to the pollution of waterhead after cluster
Degrees of data carries out outlier detection processing, and database is stored in after the abnormal point detected is marked.
6. a kind of pollution of waterhead data processing system based on block chain technology according to claim 5, characterized in that institute
It states and outlier detection is carried out to the pollution of waterhead concentration data after clustering processing, specifically include：
(1) if there are the number threshold value that the pollution of waterhead concentration data number of a cluster is less than setting after cluster, which is regarded
For abnormal clusters, all pollution of waterhead concentration datas in abnormal clusters are considered as abnormal pollution of waterhead concentration data；
(2) similarity distance between the cluster central point of other normal clusters and the cluster central point of abnormal clusters is calculated；
(3) if there are the similarity distances between the cluster central point and the cluster central point of normal clusters of an abnormal clusters no more than setting
Cluster similarity distance threshold value then using the normal clusters as cluster to be detected, and is examined using the pollution of waterhead concentration data of the abnormal clusters
The pollution of waterhead concentration data in cluster to be detected is surveyed, if the pollution of waterhead concentration data collection of the abnormal clusters is combined into Ys={ y1,
y2,..,ys, as the pollution of waterhead concentration data y in cluster to be detectedxWhen meeting exceptional condition, by pollution of waterhead concentration data yx
It is considered as abnormal pollution of waterhead concentration data；
Wherein, set exceptional condition as：
In formula,For pollution of waterhead concentration data yxArest neighbors set,For pollution of waterhead concentration data YsArest neighbors
Set, yθ∈Ys,It indicatesWithIntersection in pollution of waterhead concentration data number, N be setting
Number threshold value.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108737512A (en) * | 2018-04-28 | 2018-11-02 | 深圳智达机械技术有限公司 | A kind of pollution of waterhead monitoring system based on block chain technology |
| CN109739838A (en) * | 2018-12-06 | 2019-05-10 | 中科恒运股份有限公司 | Method for processing abnormal data and device |
| CN109819017A (en) * | 2018-12-25 | 2019-05-28 | 中链科技有限公司 | Environmental monitoring and data processing method and device based on block chain |
| CN110347891A (en) * | 2019-07-11 | 2019-10-18 | 华艺生态园林股份有限公司 | Water Contamination Monitor method based on block chain |
| CN110996290A (en) * | 2019-12-18 | 2020-04-10 | 上海无线通信研究中心 | Inland river water pollution monitoring method based on block chain |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103020642A (en) * | 2012-10-08 | 2013-04-03 | 江苏省环境监测中心 | Water environment monitoring and quality-control data analysis method |
| WO2014080324A1 (en) * | 2012-11-26 | 2014-05-30 | Mobile Telephone Networks (Proprietary) Limited | A method of determining network resource congestion and a system therefor |
| CN106469318A (en) * | 2016-09-30 | 2017-03-01 | 华东交通大学 | A kind of characteristic weighing k means clustering method based on the sparse restriction of L2 |
| CN106779418A (en) * | 2016-12-20 | 2017-05-31 | 河海大学常州校区 | Water contamination accident Intelligent Decision-making Method based on neutral net and evidence theory |
| CN107249009A (en) * | 2017-08-02 | 2017-10-13 | 广东工业大学 | A kind of data verification method and system based on block chain |
| CN107831285A (en) * | 2017-01-19 | 2018-03-23 | 江苏省金威测绘服务中心 | A kind of dystrophication monitoring system and its method based on Internet of Things |
-
2018
- 2018-04-02 CN CN201810284502.XA patent/CN108600332A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103020642A (en) * | 2012-10-08 | 2013-04-03 | 江苏省环境监测中心 | Water environment monitoring and quality-control data analysis method |
| WO2014080324A1 (en) * | 2012-11-26 | 2014-05-30 | Mobile Telephone Networks (Proprietary) Limited | A method of determining network resource congestion and a system therefor |
| CN106469318A (en) * | 2016-09-30 | 2017-03-01 | 华东交通大学 | A kind of characteristic weighing k means clustering method based on the sparse restriction of L2 |
| CN106779418A (en) * | 2016-12-20 | 2017-05-31 | 河海大学常州校区 | Water contamination accident Intelligent Decision-making Method based on neutral net and evidence theory |
| CN107831285A (en) * | 2017-01-19 | 2018-03-23 | 江苏省金威测绘服务中心 | A kind of dystrophication monitoring system and its method based on Internet of Things |
| CN107249009A (en) * | 2017-08-02 | 2017-10-13 | 广东工业大学 | A kind of data verification method and system based on block chain |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108737512A (en) * | 2018-04-28 | 2018-11-02 | 深圳智达机械技术有限公司 | A kind of pollution of waterhead monitoring system based on block chain technology |
| CN109739838A (en) * | 2018-12-06 | 2019-05-10 | 中科恒运股份有限公司 | Method for processing abnormal data and device |
| CN109819017A (en) * | 2018-12-25 | 2019-05-28 | 中链科技有限公司 | Environmental monitoring and data processing method and device based on block chain |
| CN110347891A (en) * | 2019-07-11 | 2019-10-18 | 华艺生态园林股份有限公司 | Water Contamination Monitor method based on block chain |
| CN110996290A (en) * | 2019-12-18 | 2020-04-10 | 上海无线通信研究中心 | Inland river water pollution monitoring method based on block chain |
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