Accurate meteorological data is crucial in fields such as scientific research, aviation safety, disaster response, and agricultural production. Whether it's a large-scale environmental monitoring network or a small research meteorological station, reliable meteorological monitoring equipment that provides credible data is needed.
To meet these needs, comprehensive meteorological data acquisition stations are often the first choice, but sometimes other options must be considered due to factors such as equipment size, cost, and ease of operation. The Meteorological Monitoring System is designed to address these challenges.
The Meteorological Monitoring System integrates multiple sensor functions such as temperature and humidity detection, wind speed and direction measurement, noise monitoring, PM2.5 and PM10 concentration detection, carbon dioxide concentration monitoring, and atmospheric pressure measurement, to achieve around-the-clock automatic data collection. The system transmits monitoring results in real-time to a PLC control panel or connects to an environmental monitoring center via the RS-485 communication protocol for data display, summarization, and in-depth analysis.
By integrating terminal devices to control various sensors, a shareable meteorological monitoring network is constructed. This system is easy to operate, adaptable to diverse environmental configurations, and offers greater flexibility in the installation location of meteorological stations, reducing construction costs. Users can also freely expand or modify various components of the system according to their specific needs.
The system introduces real-time database technology to achieve intelligent video monitoring, real-time data monitoring, alarms, and positioning services for various locations and related facilities within an area, providing an efficient management tool for the stable operation of the regional environment and emergency incident handling. Relying on cloud services and big data analysis technology, the system processes and analyzes a large amount of diverse data comprehensively and associatively, maximizing the value of data, thereby enhancing the efficiency and quality of decision-making.
