Forest fire weather station, fire prevention, observation of ecology

The occurrence of forest and grassland fires is closely linked to meteorological conditions, and they are one of the key factors triggering disasters. Therefore, accurate prediction of the meteorological level of fire risk in forests and grasslands is crucial for fire prevention.

By analysing historical fire records, remotely sensed high-temperature data, vegetation and terrain information, as well as taking into account human and lightning activities, a model capable of fine-tuning the prediction of forest and grassland fire risk has been developed by using meteorological big data and artificial intelligence techniques. This system can now provide fire danger level forecasts updated every 24 hours for the next three days, which is a significant improvement in the frequency and real-time nature of the forecasts compared to the previous irregular and monthly forecasts.

Using an accurate weather monitoring and warning system for forest and grassland fires, it is possible to create a real-time updated weather risk level map of the province. The system identifies various types of surface features, such as farmland and woodland, and assesses the extent of fire impacts with the help of AI technology. It can also quickly detect high-temperature anomalies in meteorological satellite data and report this important information to the Fire Command and relevant agencies in a timely manner, providing strong technical support for fire prevention and suppression in the province.

Forest fire weather stations are installed in forested areas to monitor key meteorological data such as temperature, humidity and wind speed to help predict fire risk. The stations detect fires in a timely manner through remote sensing and video monitoring technology and transmit information in real time to the command centre through a wireless network to support rapid fire response.

Not only fire prevention, but also ecological observation.

By continuously observing meteorological elements such as wind, temperature, light, humidity, barometric pressure, rainfall and soil temperature in typical areas of the forest, we can understand the distribution characteristics of climatic factors in the forest and the differences between microclimates. These data help to reveal microclimate characteristics and their variations, and provide support for analysing the role of microclimate in forest ecology.

The system is designed for long-term stable monitoring, with high stability and fast response sensors, as well as abundant storage space. Through the RS232 or 485 serial port, the system can be connected to a computer and use the data transfer software to manage the information efficiently. Users can choose to match the various types of sensors according to the actual needs of the system, the configuration of the system is highly flexible. For outdoor installation, the system is equipped with a rugged protective housing to withstand harsh environments. In addition, the system is solar-powered for unsupervised automatic operation and can transmit data via GPRS wireless network.