I. Product Overview

The Corn Northern Leaf Blight Automatic Monitoring and Early Warning System relies on an IoT cloud platform and integrates meteorological and soil analysis modules to automatically collect and process environmental data from corn planting areas. The system has a built-in disease prediction model that combines corn growth characteristics and environmental data to accurately monitor and forecast the trends of northern leaf blight occurrence. It provides farmers with a scientific basis for prevention and control, reduces yield losses, and promotes the intelligent development of agriculture.

II. Technical Parameters

1. Complies with the GB/T 24689.6-2009 standard (Plant Protection Machinery—Agricultural and Forestry Microclimate Information Collection System).

2. Data processing function: The system automatically generates prediction curves for the probability of corn northern leaf blight occurrence and simultaneously plots microclimate environmental data curves. By displaying dual curves side by side, users can visually analyze the correlation between environmental factors and the trend of northern leaf blight occurrence, providing data support for agricultural research and precise prevention.

3. Data acquisition host: Capable of collecting data such as air temperature, air humidity, wind speed, wind direction, light intensity, rainfall, soil temperature, and soil humidity; supports Modbus 485 sensor expansion; features real-time clock and time calibration functions.

4. Communication method: Supports 4G full-netcom.

5. Power supply method: Supports AC 220V or solar power DC12V (40W, 20Ah solar power system).

6. Device operating power: ≤ 3W.

7. Low power consumption: Can operate continuously for ≥45 days in overcast and rainy conditions.

8. Operating temperature: -20 to 70°C.

9. GPS positioning: Built-in GPS positioning function, allowing users to view device station data on GIS maps.

10. Sensors: Utilizes multi-parameter ultrasonic sensors with high-precision measurement performance, supports operation without startup wind speed restrictions, and operates stably under zero wind speed conditions. 360°全方位無角度限制，可同時(shí)獲得風(fēng)速風(fēng)向數(shù)值。

11. Data upload: Default upload interval is 60 minutes, with 24 uploads per day; upload frequency can be adjusted as needed.

12. Remote viewing: Supports mobile App and Web-based remote access to device information such as online status, signal strength, voltage information, historical data queries, and remaining data usage.

13. Remote maintenance: Enables remote updates via the cloud platform, allowing system maintenance and upgrades without leaving home.

14. Software functions:

(1) Fault alarm: Includes device displacement alarm function.

(2) Real-time upload: Monitoring data is uploaded to the cloud platform in real time for backup, ensuring no data loss.

(3) Data query and export: Allows screening of monitoring data by time period as needed; monitoring data can be viewed and exported in the form of graphs or Excel spreadsheets.

(4) WeChat alerts: Device-related warning information can be pushed to users via WeChat official accounts, enabling timely responses and serving a preventive and early warning role.

(5) Threshold settings: Supports setting thresholds for different sensors to achieve data monitoring and early warnings.

15. Main technical specifications of sensors:

(1) Air temperature: Measurement range: -40 to 80°C; resolution: 0.1°C; accuracy: ±0.5°C.

(2) Air humidity: Measurement range: 0 to 100% RH; resolution: 0.1%; accuracy: ±5% RH.

(3) Wind speed: Measurement range: 0 to 60 m/s; resolution: 0.01 m/s; accuracy: ±0.3 + 3% FS.

(4) Wind direction: Measurement range: 0 to 359°; resolution: ±3°; accuracy: 1°.

(5) Light intensity: Measurement range: 0 to 200,000 Lux; resolution: 10 Lux; accuracy: ±7%.

(6) Rainfall: Measurement range: 0 to 8 mm/min; resolution: 0.01 mm; accuracy: ±10%.

(7) Soil temperature: Measurement range: -40 to 80°C; resolution: 0.1°C; accuracy: ±0.5°C.

(8) Soil humidity: Measurement range: 0 to 100%; resolution: 0.1%; accuracy: ±3%.