For the soil remediation project, monitoring and management are conducted through twin big data methods to achieve real-time control of the site. And the digital management and control platform automatically monitors and controls the treatment plan, equipment status and personnel security, which ensures the smooth implementation of environmental remediation and treatment project. After the final restoration, the site meets the relevant national standards, eliminates or reduces environmental risks, and restores the reuse value of the remediated land.
With the acceleration of industrialization and urbanization, environmental pollution issues have become increasingly severe. In terms of soil pollution, a large number of polluted land sites left by chemical enterprises are in urgent need of remediation, with varying degrees of pollution in industrial land use. The situation of water pollution is also not optimistic, as many rivers and lakes have deteriorated water quality and impaired ecological functions. During the process of environmental remediation projects, efficient and precise intelligent systems are required to improve the effectiveness of environmental remediation.
Data integration challenges
Environmental remediation involves various sources and types of data, such as soil, water quality, meteorological conditions, etc. However, existing software is inefficient in integrating these complex datasets, leading to a lack of comprehensive basis for decision-making.
Insufficient real-time monitoring
The inability to provide real-time monitoring of environmental parameters makes it difficult to promptly detect and respond to sudden situations during the remediation process. For example, in soil remediation, the spread trend of pollutants cannot be identified in a timely manner.
Low prediction accuracy
The prediction accuracy of the repair effect is not high, affecting the optimization of the repair scheme.
Lack of intelligent decision support
Unable to provide intelligent decision-making suggestions based on data analysis, still relying on manual experience judgment.
Value Empowerment
Provide corresponding value to the industry, empower development, and facilitate transformation.
Improved efficiency and precision
Quickly processing and analyzing a large amount of environmental data, accurately assessing the degree and scope of pollution, and providing precise basis for the formulation of remediation plans. Through analysis, the delimitation error of polluted areas can be controlled within an extremely small range.
Real-time monitoring and early warning
Implement real-time monitoring of the repair site, promptly identify abnormal situations and issue warnings to prevent problems from escalating.
Simulation of prediction effect
Simulate the effects of different repair schemes to assist in selecting the optimal scheme and improve the success rate of repairs.
Facilitate project management
Comprehensively manage the progress, quality, and cost of repair projects to ensure timely and high-quality completion.
Core Features
Oriented by the "teaching, learning, practicing, training, and testing" five-in-one training philosophy
Automatically collect environmental data from various monitoring devices (such as sensors, detection instruments, etc.), including soil, water quality, air, and other aspects. Integrate and standardize these scattered and heterogeneous data to ensure accuracy and consistency.
Based on the collected data, professional algorithms and models are used to comprehensively assess and deeply analyze the degree, type, source, and potential risks of pollution.
Based on the pollution assessment results, simulate the effects of different remediation technologies and strategies, and provide users with optimized remediation scheme suggestions through comparative analysis.
Real-time tracking of various stages of repair projects, including task allocation, work progress, resource usage, etc., and generating detailed reports and charts to facilitate management personnel to grasp project dynamics in time and adjust plans and resource allocation accordingly.
Visualize complex environmental data and analysis results in intuitive charts, maps, etc., to provide decision-makers with clear and understandable information, assisting them in making scientific and accurate decisions.
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