Design and application of an intelligent monitoring and early warning system for bioremediation of coking contaminated sites

Abstract

The soil bioremediation process of coking sites is complex, the site environment is harsh, and the project period is long. Compared with the fields of water and air pollution monitoring, the informatization level of soil bioremediation project is low, and it is urgent to improve the digitalization and intelligence. Through the design of an online monitoring and electronic inspection system for the bioremediation process of coke contaminated soil and the development of intelligent early warning software, a study of information-specific technologies and data models for coke contamination remediation has been conducted. This paper focuses on three core elements of this field, including multidimensional data collection technologies such as Internet of Things and image recognition, big data processing technologies realized by relying on communication modules and cloud platform databases, and the construction of a neural network computational model for the soil bioremediation process. The information system has been tried out in the pilot process of soil bioremediation, realizing information management functions such as monitoring the operation status of sensors, inspection management, equipment's own status management, online monitoring and alarming of soil bioremediation parameters, and trend prediction of future soil parameters, forming a new generation of intelligent supervision system for soil bioremediation sites.