Environmental Safety Monitoring System Based on Microservice Architecture and Machine Learning

Abstract

The monitoring systems of various industries have various types and different structures. There are problems of “data chimney” and “information islands”. Monitoring data is difficult to be effectively utilized and cannot provide reliable data information to support for environmental security. In this end, an environment monitoring system based on micro-service architecture is designed. The information management and automatic monitoring business systems are unified into a flexible, robust and efficient system platform to adapt to the big data analysis and the mining applications. Using Hadoop to build environment monitoring big data platform, distributed storage, selective extraction and efficient calculation of the massive environment monitoring data can be achieved. By integrating the detection and monitoring data of the ecological environment and in-depth mining it, a neural network model is established to automatically identify potential safety hazards and recommend corresponding treatment measures, so to assist in the comprehensive research and scientific decision-making of environmental safety and promote intelligent management of safety.