Real-Time Climate Monitoring and Disaster Early Warning Algorithm Based on Sensor Network and Cloud Computing
Cai Ren, C. Joanna Su · 2024
With the increasing frequency of climate change and the continuous occurrence of disaster events, real-time climate monitoring and disaster early warning have become important measures to ensure social security. Based on the combination of sensor network (SN) and cloud computing, this study proposes an algorithm for real-time climate monitoring and disaster early warning. Firstly, this paper designs a meteorological data acquisition system based on SN, and uploads the data to the cloud computing platform for real-time processing and analysis. Secondly, the paper proposes a real-time climate monitoring algorithm based on machine learning, which can effectively monitor meteorological changes and extract key features. On this basis, this paper designs a disaster early warning algorithm, which can timely warn potential disaster risks through the analysis and comprehensive evaluation of real-time meteorological data. Through the design and deployment of the system and the optimization and verification of the algorithm, the paper verifies the feasibility and effectiveness of the real-time climate monitoring and disaster early warning algorithm combining SN with cloud computing in practical application. The experimental results show that the algorithm can realize accurate monitoring of meteorological changes and timely warning of disaster risks in a short time, which provides important support for meteorological disaster prevention and emergency response.