Scheme Introduction:

Building a visual system for monitoring and early warning of forest and grass fire risk factors based on big data analysis and artificial intelligence through cloud platform, which is refined, localized, and self-learning

The system is based on the B/S architecture, using domestic operating systems and database software to form an efficient, loosely coupled, robust, and unified business analysis platform for big data applications

The system platform receives information reported by front-end perception devices and is closely integrated with geographic information systems to present the information in full screen

By utilizing big data analysis and artificial intelligence technology, a comprehensive analysis is conducted to form a fire hazard index and level with the characteristics of forest and grassland fire prevention industry, generate forest fire hazard situation, and sustainably optimize early warning models, providing application services for command and decision-making

Implement services such as fire risk factor monitoring and analysis, fire risk level assessment, and fire risk warning.

Advantages of the plan:

1. Comprehensive monitoring of various forest and grassland fire risk factors, including meteorological data, vegetation data, etc., to provide comprehensive data support for fire risk warning

2. Intelligent model prediction algorithm, using advanced fire hazard level prediction models and machine learning algorithms, can provide early warning and prediction of fire hazard levels, timely issue alarm information, and remind relevant departments and personnel to take corresponding preventive measures.

3. Real time monitoring and warning, monitoring stations collect and upload data in real time, software platforms can analyze data in real time, timely release fire danger warning information, and provide timely support for fire prevention work.

4. Visual analysis, the platform provides intuitive data visualization functions, making it easy for users to analyze fire hazards and develop targeted fire prevention measures.

5. Meteorological data sharing allows for the sharing of meteorological factor data with models such as the spread of wildfires in the vast sea. During the firefighting command process, one can easily associate meteorological data from forest and grassland fire risk monitoring stations around the fire site, generate fire spread analysis data, and provide decision-making and command basis for firefighting

6. Joint data complementarity between land and ground, the Haohai scheme integrates satellite remote sensing forest fire monitoring and meteorological factor data from forest and grassland fire risk monitoring stations, providing more accurate forest fire risk level prediction data from small to large ranges, and providing more effective support for fire prevention and emergency management.

Flexible product&service models:

1. Forest and grass fire risk factor data collection+data analysis+fire risk level prediction and evaluation+fire risk warning and forecasting

2. Forest and grass fire risk factor data collection+data analysis+fire risk level prediction and evaluation results+integration with third-party platforms

3. Forest and grass fire risk factor data collection+integration with third-party platforms