Smart Environment (Eco-Environmental) Visualization-Chengdu Sefon Software Co., Ltd.

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Application scenario

Smart Environment (Eco-Environmental) Visualization

Mature Application: Compared with big data applications in other industries, big data in environmental protection has inherent advantages; its overall analysis and application have the relevant elements of a big data system from the very beginning.
Clear System: The environmental protection big data system can conduct clear-system-context big data analysis for a certain aspect from the very beginning, without data network association, and can directly sort out relevant analysis for a type of data; the construction process is intuitive and the construction difficulty is low.
Urgent Need: Compared with the management department of pollution-generating enterprises, the environmental protection department is relatively weak, and more urgently needs scientific and correct data to state facts, clarify rights and responsibilities, and conduct environmental protection rectification and adjustment. Therefore, it is more dependent on big-data-based informationization support.

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Facing challenges

It involves the collection of various systems and information data such as environmental protection internal and external units, a large number of real-time data from online monitoring systems, and internet public opinion data, with very wide sources.
It includes various structured database data including Oracle and SQL Server, various data documents such as Excel and XML, and unstructured data including video and pictures, which puts great pressure on collection and storage.
The multi-source of data collection causes data quality problems; duplicate data items and data compliance under various complex rules all have content that needs to be investigated and adjusted.

Solution

Environmental Carrying Capacity Analysis

Environmental carrying capacity refers to the size of the population scale and economic scale that environmental resources can accommodate within a certain period under the premise of maintaining relative stability. Comprehensive environmental carrying capacity is a comprehensive analysis after synthesizing relevant carrying capacity analyses such as land environmental protection carrying capacity and fresh water environmental protection carrying capacity. It is necessary to determine the weight of sub-module content according to the specific situation of each city and determine the final environmental carrying capacity indicator.
Pollution-Meteorology Relationship Analysis

The relationship between pollution and meteorology mainly focuses on using big data technology to study the diffusion, transport, migration, and transformation of pollutants in the atmosphere, which has a very close relationship with the spatial distribution of wind direction and wind speed and temperature, atmospheric turbulent motion, solar radiation, humidity, clouds, precipitation, and other meteorological conditions. It mainly refers to the meteorological processes, meteorological conditions, and meteorological parameters related to the movement and transformation of pollutants in the atmosphere, and also includes the meteorological effects caused by the increase of pollutants in the atmosphere.
Environmental-Economic Relationship Analysis

The most famous evaluation system for environmental-economic analysis is the Kuznets curve, mainly used to explain the theory of the relationship between environmental quality and income. When the economic development level is low, the degree of environmental pollution is light, but with the increase of per capita income, environmental pollution tends from low to high and gradually intensifies; after economic development reaches a certain critical point or "inflection point", environmental pollution tends from high to low, its degree gradually slows down, and environmental quality gradually improves. Seeking this "inflection point" through big data analysis is a key point of current scientific environmental protection analysis.
Pollutant Big Data Analysis

Through big data analysis of major pollutants, clarify pollution sources, understand and master the types, quantities, methods, and paths of pollutants discharged from pollution sources and the types and locations of pollution sources, which are directly related to the objects, scope, and degree of harm. Furthermore, find out the main pollution sources and main pollutants within a certain range, and the current status of utilization of resources, energy, and water resources. Point out the direction for enterprise technical transformation, pollution control, comprehensive utilization, and strengthening management; provide a basis for regional environmental management, environmental planning, and environmental scientific research.
Environmental Protection Early Warning and Prediction

Based on big data technology, integrate past historical pollution data and related production and life activity information, predict the upcoming changes and their impacts according to relevant formulas and mathematical models, and issue early warnings based on the prediction results, which will effectively help select appropriate strategies for pollution prevention or minimize the losses caused by pollution.
Pollutant Emission Control

Pollutant emission control is the treatment and control behavior for the pollution situation where various exogenous substances emitted by humans enter the regulated object and exceed the range it can bear. The main control methods include emission trading and emission permits. Among them, emission trading refers to the mutual adjustment of emission amounts between various internal pollution sources through monetary exchange within a certain region under the premise that the total pollutant emission does not exceed the allowable emission amount, so as to achieve the purpose of reducing emissions and protecting the environment.

Overall planning, to build a comprehensive business solution

Smart Environment (Eco-Environmental) Visualization

Application value

High-Quality Collection of Environmental Protection Data

To meet the needs of environmental quality evaluation, assessment, and early warning, integrate data from multiple monitoring points including the natural environment and key pollution-discharging enterprises, and integrate them into the big data ecosystem with high quality and speed.

Efficient Sharing of Related Data

Build a unified data collection and transmission method and standard, and realize effective integration, interconnection, and sharing of ecological environment monitoring data of various departments.

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