CN113343691A - Big data monitoring terminal and application method thereof - Google Patents
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 84
- 238000000034 method Methods 0.000 title claims abstract description 23
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- 238000012216 screening Methods 0.000 claims abstract description 25
- 230000003993 interaction Effects 0.000 claims description 3
- 238000007781 pre-processing Methods 0.000 claims description 3
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Abstract
The invention discloses a big data monitoring terminal and an application method thereof, wherein the big data monitoring terminal comprises a central processing unit, a signal transceiver, a cloud platform, a sub-level receiving station and a monitoring unit: the monitoring units are arranged in a plurality of groups, and the monitoring units in the groups are distributed at the places to be monitored; the monitoring unit is connected with a cloud platform, the cloud platform is connected with a signal transceiver through a wireless signal, and the signal transceiver is interactively connected with the central processing unit; the central processing unit comprises a classification unit, a screening unit, a positioning unit, a processing unit and a scheduling unit; the screening unit is arranged to pre-screen the big data information, a large amount of useless complex data is removed, the data is simplified, a large amount of subsequent useless data screening work is reduced, the screened data is classified according to the preset distinguished entry information by matching with the classification unit, effective data is monitored in a targeted mode, and favorable prepositive requirements are provided for follow-up people on big data monitoring.
Description
Technical Field
The invention relates to the technical field of big data monitoring and processing, in particular to a big data monitoring terminal and an application method thereof.
Background
In modern society, human beings have been inseparable with data density, the composition of mass data really reflects complex things in the real world, but human brains cannot directly convert huge data into effective information, and the data visualization technology is helpful for better managing and understanding the data and discovering deeper connection of the complex data. The professor Jim Thomas in the beginning of the 21 st century proposes that visualization is an indispensable technology in big data mining and analysis, the technology develops from entry-level Excel to professional-level commercial products to date, the technology is mature, and the application of the technology plays an important role in finance, sales, logistics, electric power, traffic, media, medicine, geography and other sciences, and helps people in various fields to find, diagnose and solve problems.
Big data is a data set which cannot be captured, managed and processed by a conventional software tool within a certain time range, and is a massive, high-growth-rate and diversified information asset which can have stronger decision-making power, insight discovery power and flow optimization capability only by a new processing mode.
Large data requires special techniques to efficiently process large amounts of data that are tolerant of elapsed time. Technologies applicable to big data include Massively Parallel Processing (MPP) databases, data mining, distributed file systems, distributed databases, cloud computing platforms, the internet, and scalable storage systems.
The current big data monitoring terminal has some defects in the using process:
the existing big data monitoring terminal is usually only suitable for data monitoring in one field, but in the modern society, in an information explosion era, the data are extremely various, the information acquisition work of people on the specified data is very complicated, a large amount of time is wasted, and the big data monitoring is not facilitated for people.
Disclosure of Invention
The invention aims to provide a big data monitoring terminal and an application method thereof, so as to solve the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme: a big data monitoring terminal comprises a central processing unit, a signal transceiver, a cloud platform, a sub-level receiving station and a monitoring unit:
the monitoring units are arranged in a plurality of groups, and the monitoring units in the groups are distributed at the places to be monitored;
the monitoring unit is connected with a cloud platform, the cloud platform is connected with a signal transceiver through a wireless signal, and the signal transceiver is interactively connected with the central processing unit;
the central processing unit comprises a classification unit, a screening unit, a positioning unit, a processing unit and a scheduling unit;
the central processing unit is used for comprehensively processing the big data acquired by the monitoring unit;
the signal transceiver is used for providing data interaction signals for the cloud platform and the central processing unit;
the cloud platform is used for building a virtual network platform and forwarding and collecting monitoring data;
and the monitoring unit is used for acquiring data information.
Preferably: the screening unit is connected with the classifying unit;
the screening unit is used for pre-screening the big data information after the signal transceiver sends the data to the central processing unit so as to distinguish a large amount of useless data;
and the classification unit is used for classifying the screened data according to preset distinguishing entry information.
Preferably: the preset distinguished entry information is set by self-definition, and in the process of self-definition setting, an expected value obtained by expected input is taken as a reference.
Preferably: the expected value is any one or more of a number interval, character information and a fluctuation threshold value.
Preferably: the classification unit is connected with a plurality of processing units which are arranged in number and are respectively matched with the classification types of the classification unit;
and the processing unit is used for processing the classified data and independently marking the data needing to be monitored.
Preferably: the processing unit is connected with the positioning unit, and the positioning unit is connected with the scheduling unit;
the positioning unit is used for positioning the source position of the independent mark data;
and the scheduling unit is used for sending the independently marked data to the appointed sub-stage receiving station.
Preferably: the cloud platform is connected with a sub-level receiving station, and the sub-level receiving station is connected with a monitoring unit.
An application method of a big data monitoring terminal comprises the following steps:
the method comprises the following steps: laying sub-level receiving stations at required places, connecting monitoring units below the sub-level receiving stations, defining a special code for each individual monitoring unit, wherein the special code consists of English, symbols and Arabic numerals and is orderly arranged;
step two: the monitoring unit collects data, sends the data to the cloud platform, conducts preprocessing through the cloud platform and transmits the data to the signal transceiver, and the signal transceiver sends signals to the central processing unit;
step three: the data information received by the central processing unit is firstly pre-screened by the screening unit to distinguish a large amount of useless data;
step four: the screening unit sends the screened data to the classifying unit, the classifying unit classifies the data according to the information of the set distinguishing entry, the big data is sent to the processing unit after classification, and the processing unit processes the classified data and independently marks the data needing to be monitored;
step five: the positioning unit positions the source position of the independent mark data and sends the independent mark data to a designated sub-level receiving station, and the sub-level receiving station determines the data condition and processes the data.
Preferably: and before the classification unit classifies, entries are distinguished according to monitoring information input.
Compared with the prior art, the invention has the beneficial effects that:
the large data information is pre-screened by the screening unit, a large amount of useless complex data is removed, data are simplified, a large amount of subsequent useless data screening work is reduced, the screened data are classified according to preset distinguished entry information by matching with the classifying unit, and effective data are monitored in a targeted manner, so that favorable prepositive requirements are provided for subsequent people on large data monitoring, the time for monitoring a large amount of subsequent data is reduced, and the data monitoring efficiency is improved;
the source position of the independently marked data is positioned by arranging the positioning unit, the independently marked data is sent to the appointed sub-level receiving station by the scheduling unit, the sub-level receiving station determines the data condition and processes the data, the efficiency of targeted data processing is improved, and the timeliness of big data monitoring is enhanced;
thirdly, the sub-level receiving stations are arranged at the required places, the sub-level receiving stations are connected with the monitoring units, each single monitoring unit defines a special code, the special codes are composed of English, symbols and Arabic numbers and are sequentially and orderly arranged, the data monitoring distinguishability is improved, and before the classification units classify, entries are input and distinguished according to monitoring information, so that the data is pertinently monitored according to the complexity of the data explosion era, and the data monitoring efficiency is improved.
Drawings
Fig. 1 is a schematic block diagram of a monitoring terminal according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Examples
Referring to fig. 1, the present invention provides a technical solution: a big data monitoring terminal comprises a central processing unit, a signal transceiver, a cloud platform, a sub-level receiving station and a monitoring unit:
the monitoring units are arranged in a plurality of groups, and the monitoring units in the groups are distributed at the places to be monitored;
the monitoring unit is connected with the cloud platform, the cloud platform is connected with the signal transceiver through a wireless signal, and the signal transceiver is in interactive connection with the central processing unit;
the central processing unit comprises a classification unit, a screening unit, a positioning unit, a processing unit and a scheduling unit;
the central processing unit is used for comprehensively processing the big data acquired by the monitoring unit;
the signal transceiver is used for providing data interaction signals for the cloud platform and the central processing unit;
the cloud platform is used for building a virtual network platform and forwarding and collecting monitoring data;
and the monitoring unit is used for acquiring data information.
In this embodiment, specifically: the screening unit is connected with the classifying unit;
the screening unit is used for pre-screening the big data information after the signal transceiver sends the data to the central processing unit so as to distinguish a large amount of useless data;
and the classification unit is used for classifying the screened data according to preset distinguishing entry information.
In this embodiment, specifically: the preset distinguishing entry information is set by self-definition, and in the process of self-definition setting, expected values obtained by expected input are taken as a reference.
In this embodiment, specifically: the expected value is any one or more of a number interval, character information and a fluctuation threshold value.
In this embodiment, specifically: the classification unit is connected with the processing units, the processing units are arranged in a plurality, and the processing units are respectively matched with the classification types of the classification unit;
and the processing unit is used for processing the classified data and independently marking the data needing to be monitored so as to distinguish data information sources.
In this embodiment, specifically: the processing unit is connected with the positioning unit, and the positioning unit is connected with the scheduling unit;
the positioning unit is used for positioning the source position of the independent mark data;
and the scheduling unit is used for sending the independently marked data to the appointed sub-stage receiving station.
In this embodiment, specifically: the cloud platform is connected with the sub-level receiving station, and the sub-level receiving station is connected with the monitoring unit.
An application method of a big data monitoring terminal comprises the following steps:
the method comprises the following steps: laying sub-level receiving stations at required places, connecting monitoring units below the sub-level receiving stations, defining a special code for each individual monitoring unit, wherein the special code consists of English, symbols and Arabic numerals and is orderly arranged;
step two: the monitoring unit collects data, sends the data to the cloud platform, conducts preprocessing through the cloud platform and transmits the data to the signal transceiver, and the signal transceiver sends signals to the central processing unit;
step three: the data information received by the central processing unit is firstly pre-screened by the screening unit to distinguish a large amount of useless data;
step four: the screening unit sends the screened data to the classifying unit, the classifying unit classifies the data according to the information of the set distinguishing entry, the big data is sent to the processing unit after classification, and the processing unit processes the classified data and independently marks the data needing to be monitored;
step five: the positioning unit positions the source position of the independent mark data and sends the independent mark data to a designated sub-level receiving station, and the sub-level receiving station determines the data condition and processes the data.
In this embodiment, specifically: and before the classification unit classifies, the entries are distinguished according to the monitoring information input.
Working principle or structural principle: the screening unit is arranged to pre-screen the big data information, a large amount of useless complex data is removed, the data is simplified, a large amount of subsequent useless data screening work is reduced, the screened data is classified according to the preset distinguished entry information by matching with the classification unit, and effective data is monitored in a targeted manner, so that favorable prepositive requirements are provided for subsequent people on big data monitoring, the time for monitoring a large amount of subsequent data is reduced, and the data monitoring efficiency is improved;
according to the invention, the source position of the independently marked data is positioned by arranging the positioning unit, and the independently marked data is sent to the appointed sub-level receiving station by the scheduling unit, so that the sub-level receiving station determines the data condition and processes the data in a specific way, the efficiency of processing the specific data is improved, and the timeliness of monitoring the big data is enhanced;
according to the invention, the sub-level receiving stations are arranged at required places, the monitoring units are connected below the sub-level receiving stations, each single monitoring unit defines a special code, the special codes consist of English, symbols and Arabic numbers and are sequentially and orderly arranged, the data monitoring distinguishability is improved, and before the classification units classify, entries are distinguished according to the input of monitoring information, so that the data is pertinently monitored according to the complexity of the data explosion era, and the data monitoring efficiency is improved.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (9)
1. The utility model provides a big data monitoring terminal, includes central processing unit, signal transceiver, cloud platform, sublevel receiving station and monitoring unit, its characterized in that:
the monitoring units are arranged in a plurality of groups, and the monitoring units in the groups are distributed at the places to be monitored;
the monitoring unit is connected with a cloud platform, the cloud platform is connected with a signal transceiver through a wireless signal, and the signal transceiver is interactively connected with the central processing unit;
the central processing unit comprises a classification unit, a screening unit, a positioning unit, a processing unit and a scheduling unit;
the central processing unit is used for comprehensively processing the big data acquired by the monitoring unit;
the signal transceiver is used for providing data interaction signals for the cloud platform and the central processing unit;
the cloud platform is used for building a virtual network platform and forwarding and collecting monitoring data;
and the monitoring unit is used for acquiring data information.
2. The big data monitoring terminal according to claim 1, wherein: the screening unit is connected with the classifying unit;
the screening unit is used for pre-screening the big data information after the signal transceiver sends the data to the central processing unit so as to distinguish a large amount of useless data;
and the classification unit is used for classifying the screened data according to preset distinguishing entry information.
3. The big data monitoring terminal according to claim 2, wherein: the preset distinguished entry information is set by self-definition, and in the process of self-definition setting, an expected value obtained by expected input is taken as a reference.
4. The big data monitoring terminal according to claim 3, wherein: the expected value is any one or more of a number interval, character information and a fluctuation threshold value.
5. The big data monitoring terminal according to claim 1, wherein: the classification unit is connected with a plurality of processing units which are arranged in number and are respectively matched with the classification types of the classification unit;
and the processing unit is used for processing the classified data and independently marking the data needing to be monitored.
6. The big data monitoring terminal according to claim 1, wherein: the processing unit is connected with the positioning unit, and the positioning unit is connected with the scheduling unit;
the positioning unit is used for positioning the source position of the independent mark data;
and the scheduling unit is used for sending the independently marked data to the appointed sub-stage receiving station.
7. The big data monitoring terminal according to claim 1, wherein: the cloud platform is connected with a sub-level receiving station, and the sub-level receiving station is connected with a monitoring unit.
8. An application method of a big data monitoring terminal is characterized by comprising the following steps:
the method comprises the following steps: laying sub-level receiving stations at required places, connecting monitoring units below the sub-level receiving stations, defining a special code for each individual monitoring unit, wherein the special code consists of English, symbols and Arabic numerals and is orderly arranged;
step two: the monitoring unit collects data, sends the data to the cloud platform, conducts preprocessing through the cloud platform and transmits the data to the signal transceiver, and the signal transceiver sends signals to the central processing unit;
step three: the data information received by the central processing unit is firstly pre-screened by the screening unit to distinguish a large amount of useless data;
step four: the screening unit sends the screened data to the classifying unit, the classifying unit classifies the data according to the information of the set distinguishing entry, the big data is sent to the processing unit after classification, and the processing unit processes the classified data and independently marks the data needing to be monitored;
step five: the positioning unit positions the source position of the independent mark data and sends the independent mark data to a designated sub-level receiving station, and the sub-level receiving station determines the data condition and processes the data.
9. The application method of the big data monitoring terminal according to claim 8, wherein: and before the classification unit classifies, entries are distinguished according to monitoring information input.
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