AgroBot: Smart Agriculture Intelligent Robot

Smart Agriculture AI Leaf Health Recognition × Mobile Environmental Monitoring × Precision Application

Traditional manual pesticide spraying not only consumes labor and chemicals, but also exposes farmers to potential occupational hazards from inhaling pesticides. In addition, farmers with limited experience often struggle to accurately identify pests and diseases, affecting decisions on pesticide type and dosage.

MIC Meter’s AI autonomous equipment enables the following in smart agriculture scenarios:

• AI leaf image recognition: pest and disease identification accuracy reaches over 89.3%, enabling real-time assessment of crop health and triggering precision spraying immediately upon detecting disease symptoms.

• Integrated greenhouse environmental sensing: measures temperature, humidity, atmospheric pressure, CO₂, and photosynthetic photon flux density (PPFD), and calculates DLI and VPD to support irrigation and environmental control decisions.

• Mobile, height-adjustable sensing design: measurement positions maintained 10–15 cm above the crop canopy, ensuring accurate and professional environmental data collection.

• Non-fixed monitoring: all data and AI-analyzed abnormal images are fully uploaded to the cloud.

• Mobile app integration: the same AI model can be deployed on smartphones, supporting instant leaf health analysis via photo capture.

• Optional wind speed sensing: automatically activates measurement when the equipment is stationary, supporting advanced applications.

The system also includes:

• Ultra-Wideband (UWB) positioning base stations (four units)

• Battery charging function, enabling up to 7 hours of operation per charge

• Front-end monitor and 2D LiDAR: automatically stops when encountering obstacles

• Charging port and warning lights: indicate equipment status, low battery, or other errors

• Self-diagnostics: monitors CPU system, battery status, and vehicle posture, with results returned in real time.