Smart agriculture
Designing systems to monitor and automate crops.
- Analysis of a crop's agronomic needs
- Choice of sensors and control logic
- Systems designed to fit the project's scale
Artificial intelligence
AI agents, environmental data analysis, decision systems and optimization.
- AI agents for agronomic decision support
- Time-series analysis of sensor data
- Traceable, supervisable decision systems
IoT & sensors
Sensor integration, telemetry, data acquisition and connected infrastructure.
- Selection and integration of environmental sensors
- Continuous telemetry and data reporting
- Reliable connected infrastructure in the field
Automation
Control of irrigation, ventilation, lighting, heating and other equipment.
- Control of irrigation, ventilation, lighting, heating
- Control logic with safety guardrails
- Integration with existing equipment
Computer vision
Visual tracking of plants, image analysis and change detection.
- Visual tracking of crop growth
- Image analysis and change detection
- Feeding AI agents with visual signals
Technology prototyping
Raspberry Pi, electronics, sensors, embedded systems and prototype development.
- Prototypes on Raspberry Pi and embedded systems
- Electronics and wiring of sensors / actuators
- Fast hardware-to-software iterations
Monitoring platforms
Interfaces to visualize data, AI decisions, equipment, alerts and history.
- Visualization of data and AI decisions
- Equipment status and action history
- Alerts and a system-wide overview
A need that spans several of these areas?
That's often the case: our projects combine sensors, AI and automation. Let's talk about your context.