CN114662840A - Carbon neutralization digital analysis large-screen visualization algorithm based on Internet of things - Google Patents
Carbon neutralization digital analysis large-screen visualization algorithm based on Internet of things Download PDFInfo
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Abstract
The invention discloses a carbon neutralization digital analysis large-screen visualization algorithm based on the Internet of things, which comprises the following steps: the first step is as follows: building a model, namely building an economic system model, an energy system model and an environmental system model according to big data of the Internet of things; the second step is that: through basic level data access, the collected data are subjected to fusion analysis, including data integration, conversion, evaluation, prediction and the like; the third step: and configuring a model selection unit on a screen interface, and displaying the model by using modules such as data overview, a distribution map, related index analysis, trend data analysis and the like on a screen after selecting a corresponding model. The invention visually represents relatively complex and abstract data through an algorithm, and enables people to more intuitively understand the relevant data analysis of carbon neutralization through converting the data into a graph or a table and the like.
Description
Technical Field
The invention relates to a carbon neutralization digital analysis large-screen visualization algorithm based on the Internet of things.
Background
Global warming is a consequence of earth climate change caused by human behavior. "carbon" is a natural resource composed of carbon elements such as petroleum, coal, wood, etc. The "carbon" is much more consumed and the very "carbon dioxide" that causes global warming is also much more produced. With human activities, global warming is also changing (affecting) people's lifestyle, bringing about more and more problems. Therefore, in order to cope with global environmental problems, the world is striving to achieve carbon neutralization, which is offset by forms of afforestation, energy saving and emission reduction, etc. by discharged carbon dioxide or greenhouse gas. And as a means for carbon neutralization, it is necessary to visually display the carbon neutralization condition in each region through a large screen.
With the development of the internet of things and the improvement of big data, the carbon neutralization data analysis is realized based on the internet of things and is shown to the front of people through a big screen. In order to realize complete and visual embodiment of various carbon neutralization data, a large-screen visualization algorithm is designed, and the method has a wide market application prospect.
Disclosure of Invention
The invention provides a carbon neutralization digital analysis large-screen visualization algorithm based on the Internet of things, which aims at the problem of carbon neutralization analysis visualization.
In order to achieve the purpose, the invention provides the following technical scheme: a carbon neutralization digital analysis large-screen visualization algorithm based on the Internet of things comprises the following steps:
the first step is as follows: building a model, namely building an economic system model, an energy system model and an environmental system model according to big data of the Internet of things;
the second step: performing fusion analysis on the collected data through basic level data access, including data integration, conversion, evaluation, prediction and the like;
the third step: and configuring a model selection unit on a screen interface, and displaying the model by using modules such as data overview, a distribution map, related index analysis, trend data analysis and the like on a screen after selecting a corresponding model.
In order to ensure the integrity of data and have real reference value, further, the model building adopts technical means such as big data, internet of things and a carbon emission calculation model, and a model covering comprehensive dimensions such as regional population composition, energy production structure, terminal consumption, key industry, scale and above enterprise carbon emission, user carbon footprint, carbon transaction and carbon absorption is built by combining national policy and local characteristics.
When selecting the basic data, the factors of each social level are considered, and the basic data preferably comprises government end data, enterprise end data and natural person data.
In order to facilitate visual operation and observation, the screen interface is built by adopting a dragging type operation, relative layout and hierarchy nesting are supported, and width self-adaption is supported. Of course, other conventional technical solutions for visualization screens can be adopted to further improve the present invention.
In order to make visualization more intuitive and make the user clear the data at a glance, the screen interface presents the data in various icon forms, including bar charts, biaxial charts, funnel charts, pareto charts, administrative maps, natural maps, and the like. Of course, the embodiment form of the data can be selected by the user according to the needs.
For better human-computer interaction interface operation, the screen interface supports dynamic analysis operations such as drilling, linkage and the like, and data are analyzed layer by clicking one key.
The invention has the beneficial effects that:
the invention visually represents relatively complex and abstract data through an algorithm, and enables people to more intuitively understand the relevant data analysis of carbon neutralization through converting the data into a graph or a table and the like. The invention effectively expresses some unintelligible data by a graphical means, accurately, efficiently, concisely and comprehensively transmits useful information, and even helps to discover certain rules and characteristics and mine the value behind the data. The invention can also directly drag the components to be presented to the canvas for free configuration and layout according to the needs of the user, and the sequence of the layers can be adjusted by clicking and dragging, and graphical editing operation is carried out in the whole process. The user can customize any canvas size according to the actual screen size. The large screen is previewed and released in a webpage form, software does not need to be additionally installed, and the browser can be used for flexibly releasing various screen terminals. Multiple data access is supported.
Drawings
FIG. 1 is a schematic diagram of the present invention;
FIG. 2 is a large screen interface display diagram according to the present invention.
Detailed Description
The invention will be described in detail below with reference to the accompanying drawings 1 and 2:
the large-screen data visualization is a data visualization design with a large screen as a main display carrier. The Internet of things technology and big data are used as supports, and the data are visually embodied on a large screen through a series of algorithms, so that a user can quickly and directly find important data from complex business data, and a decision maker can be assisted.
Specifically, the carbon neutralization digital analysis large-screen visualization algorithm based on the Internet of things comprises the following steps:
first, model building is performed in the first step. And building an economic system model, an energy system model and an environmental system model according to the big data of the Internet of things. In order to ensure the integrity of data and have real reference value, further, the model building adopts technical means such as big data, internet of things and a carbon emission calculation model, and a model covering comprehensive dimensions such as regional population composition, energy production structure, terminal consumption, key industry, scale and above enterprise carbon emission, user carbon footprint, carbon transaction and carbon absorption is built by combining national policy and local characteristics. When selecting the basic data, the factors of each social level are considered, and the basic data preferably comprises government end data, enterprise end data and natural person data.
The economic system model is based on the most major macro variables of population, capital and technology level of regions, a future increase path of the total value of domestic production is envisioned, and the total value path of the total value of domestic production is further decomposed into economic activities of various departments, and mainly comprises three parts of industry, traffic and building. The data can be obtained through statistics and summarization of relevant departments. The traffic comprises the kilometers of various logistics transportation, public and private transportation, and the data can be obtained by obtaining the running conditions of traffic vehicles in various industries by using a big data platform. The building comprises electric appliances, heating, refrigerating, hot water and other demands of commercial and residential departments, and the part can be obtained by summarizing data of all relevant departments. The energy system model comprises demand and supply, and the result (energy service demand) of the economic system model is used as input to obtain the final energy demand. Therefore, the annual demand is changing, the efficiency and the energy utilization structure of an energy system are changing, and the finally obtained energy consumption and the brought carbon emission of various varieties are changing. By summing up the energy demands of three departments of industry, traffic and building, a total demand path of various energy varieties is obtained. The supply side model of the energy system calculates how to expand the unit and the transmission and distribution network, and minimizes the total cost under the condition of meeting the energy demand and emission constraint.
And after the model is built, performing fusion analysis on the collected data through basic level data access in the second step, wherein the fusion analysis comprises data integration, conversion, evaluation, prediction and the like. Various data resources from the fields and departments of electric power, petroleum, natural gas, new energy, environmental protection, forestry, the Internet, government agencies and the like are fully integrated by utilizing advanced technical means, and professional data management and data fusion analysis are realized through big data technologies and tools. A carbon distribution analysis view is constructed from dimensions such as energy structure composition, yield trend, consumption change and the like, and multiple views such as the industry, type, time, area and the like of comprehensive energy, so that analysis of all directions, multiple dimensions and multiple views is realized. And by combining with the technical information of the replacement of clean energy, performing correlation analysis and correlation mining on clean energy consumption data, non-fossil energy consumption data, population carbon footprint, energy-saving and emission-reducing policies, energy-saving consciousness, forest coverage and the like, and mining key factors influencing carbon emission reduction. And C, monitoring and decarbonization potential analysis of carbon emission in key industries, carbon trading carbon pricing analysis and the like are performed, comprehensive dimension analysis of regional whole carbon production, consumption, replaceable resources, carbon reduction channels and the like is realized, and situation perception and accurate prediction are performed on future trends.
And finally, configuring a model selection unit on a screen interface, and displaying the model on a screen by using modules such as data overview, a distribution map, related index analysis, trend data analysis and the like after selecting a corresponding model. In order to facilitate visual operation and observation, the screen interface is built by adopting a dragging type operation, relative layout and hierarchy nesting are supported, and width self-adaption is supported. Of course, other conventional technical solutions for visualization screens can be adopted to further improve the present invention. In order to make visualization more intuitive and make the user clear the data at a glance, the screen interface presents the data in various icon forms, including bar charts, biaxial charts, funnel charts, pareto charts, administrative maps, natural maps, and the like. Of course, the embodiment form of the data can be selected by the user according to the needs. For better human-computer interaction interface operation, the screen interface supports dynamic analysis operations such as drilling, linkage and the like, and data are analyzed layer by clicking one key.
Compared with the traditional chart and data instrument panel, the large screen for data visualization monitoring can break through data isolation, visual and real-time data visualization is achieved through data acquisition, cleaning and analysis, and business insights hidden behind transient and numerous and complicated data are presented in real time. Enterprise data are monitored in real time through an interactive real-time data visualization large screen, the operation growth is known, and intelligent and efficient decision making is assisted.
As shown in fig. 2, by taking a carbon neutral and large screen visualization interface in the city of grade, the left side of the page is sequentially analyzed from top to bottom for a region profile, a terminal energy consumption structure, and indexes related to coal fuel and environmental pollution, wherein the region profile includes a total population (ten thousand people), a clean energy consumption (ten thousand tons of standard coal), a total regional production value (hundred million yuan), a green coverage area (hectare), a total energy consumption (ten thousand tons of standard coal), a forest area (hectare), and the like, and the module directly embodies related data in a digital manner. The terminal energy consumption structure comprises coal fuel, oil fuel, natural gas, electric power, heat and the like, and the module embodies data in the form of a histogram and a graph. The coal fuel and environmental pollution related index analysis comprises fuel, inhalable particulate annual daily average value, sulfur dioxide annual daily average value and the like, and the module is embodied in the form of a bar chart and a curve chart. The middle position of the interface is a regional population distribution map and the total energy consumption of each region, and the total energy consumption of each region is reflected by a curve graph. The rightmost part of the interface comprises a terminal consumption and policy correlation analysis module for various types of energy, a main energy daily average consumption and a permanent population average energy consumption analysis module, and the modules in the area adopt a curve graph and a histogram to embody data. In the whole interface, the data display modes can be switched as required, for example, the graph can be converted into a bar chart or a pie chart. And will not be described in detail herein, and can be set as desired by those skilled in the art.
It should be noted that, in the invention, the data acquisition may be implemented by using the existing means and the existing internet of things technology. In the present description, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
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 (6)
1. A carbon neutralization digital analysis large-screen visualization algorithm based on the Internet of things is characterized by comprising the following steps:
the first step is as follows: building a model, namely building an economic system model, an energy system model and an environmental system model according to big data of the Internet of things;
the second step is that: through basic level data access, the collected data are subjected to fusion analysis, including data integration, conversion, evaluation, prediction and the like;
the third step: and configuring a model selection unit on a screen interface, and displaying the model on a screen by using modules such as data overview, a distribution map, related index analysis, trend data analysis and the like after selecting a corresponding model.
2. The carbon neutralization digital analysis large-screen visualization algorithm based on the internet of things as claimed in claim 1, wherein the model building adopts technical means such as big data, the internet of things and a carbon emission calculation model, and a model covering comprehensive dimensions such as regional population composition, energy production structure, terminal consumption, key industry, scale and enterprise carbon emission, user carbon footprint, carbon transaction and carbon absorption is built by combining national policies and local characteristics.
3. The internet-of-things-based carbon neutralization digital analysis large-screen visualization algorithm as recited in claim 1, wherein the underlying data comprises government-side data, enterprise-side data and natural human data.
4. The internet-of-things-based carbon neutralization digital analysis large-screen visualization algorithm is characterized in that the screen interface is built by adopting a drag operation, relative layout and hierarchy nesting are supported, and width self-adaptation is supported.
5. The internet-of-things-based carbon neutralization digital analysis large-screen visualization algorithm as claimed in claim 1, wherein the screen interface embodies data in the form of a plurality of icons, including bar charts, biaxial charts, funnel charts, pareto charts, administrative maps, natural maps and the like.
6. The internet-of-things-based carbon neutralization digital analysis large-screen visualization algorithm is characterized in that a screen interface supports dynamic analysis operations such as drilling and linkage, and layer-by-layer analysis data is realized by one-click.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114993977A (en) * | 2022-07-19 | 2022-09-02 | 中科海慧（北京）科技有限公司 | Garden carbon monitoring system and method based on Internet of things sensing |
| CN115759788A (en) * | 2023-01-05 | 2023-03-07 | 碳阻迹（北京）科技有限公司 | Enterprise carbon data comprehensive intelligent management and control system based on big data analysis |
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2021
- 2021-12-20 CN CN202111558543.1A patent/CN114662840A/en not_active Withdrawn
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114993977A (en) * | 2022-07-19 | 2022-09-02 | 中科海慧（北京）科技有限公司 | Garden carbon monitoring system and method based on Internet of things sensing |
| CN115759788A (en) * | 2023-01-05 | 2023-03-07 | 碳阻迹（北京）科技有限公司 | Enterprise carbon data comprehensive intelligent management and control system based on big data analysis |
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Application publication date: 20220624 |