Features
Human-in-the-loop write command approval
Real-time equipment monitoring with sub-second queries
Tamper-evident audit logging with HMAC chaining
Multi-protocol support: MQTT, Sparkplug B, OPC-UA, Modbus, BACnet/IP
Natural language query of live sensor data
Autonomous anomaly detection and alerts via Telegram, Slack, or web dashboard
GDPR compliant by design: zero data leaves facility
24/7 continuous threshold monitoring
Integration with Siemens, Rockwell Automation, Allen-Bradley, ABB, Schneider Electric
Shift report generation via natural language
Web dashboard for monitoring and control
Solar-powered rover with controlled illumination
Per-plant high-resolution imaging across growing season
AI-powered pest, weed, and disease detection per plant
Real-time plant growth monitoring
Automated yield forecasting from imagery and environmental data
Crop phenotyping via computer vision (leaf size, biomass)
Quality inspection for fruits and vegetables
Food waste reduction analytics
Integration of satellite, weather, and soil data layers
Multi-angle image capture with controlled rolling speeds
Machine learning to identify plant-environment interaction patterns
Data collection in muddy fields and bright sunlight
Terabyte-scale image datasets per field
Controlled rolling speeds and sophisticated sensors
