Raspberry Pi 5 edge build
Developed on a Raspberry Pi 5 as a local cockpit and edge runtime, close to the vehicle systems rather than as a pure cloud demo.
AI Lab & Operating Layer
Cerbo AI: a real machine project for energy-autonomous operating intelligence.
This is not a purchased dashboard or a detached AI demo. It grew out of the Concorde modernization and the question of how surplus energy, local compute, weather, geolocation and vehicle state can be turned into a safe operating layer.
The system was developed directly on the edge device, using AI co-agents from idea and concept through implementation, review, project support and safety logic. The core method: compare expected PV yield with real consumption and route context, then guide the vehicle like a digital energy engineer.
Edge architecture
Built where the vehicle actually operates.
Bluetooth BMS telemetry
Battery and power-state data are read via Bluetooth BMS interfaces and combined with PV yield, load and forecast models.
Sensor and safety context
Smoke-alarm notes, temperature sensors and Bluetooth-connected IoT signals can be evaluated alongside energy and weather data.
AI co-agent governance
Concepts, implementation tasks, reviews, project support and backup or safety logic are developed with AI co-agents under explicit human decision control.
Operating model
Fold 01
Autonomous energy base
The Concorde modernization created the technical base for operating the vehicle as independently as possible from external energy infrastructure.
Fold 02
Forecast logic
Geolocation, weather forecasts and PV yield models are compared with expected consumption to understand the next hours and days before decisions are needed.
Fold 03
Energy flow management
The operating layer translates battery state, solar potential, loads and comfort needs into clear recommendations for intelligent energy use.
Interface evidence
Real dashboards, real operating constraints.
Forecast and load planning
PV forecast, appliance load planning and state-of-charge projection in one energy decision view.
Travel cockpit state
Weather, indoor/outdoor conditions, battery state and power flows shown against the vehicle context.
Logic layer
From cockpit display to AI-assisted operating layer.
System state
Energy, weather, tanks, automation and vehicle status in one cockpit view.
Prediction
PV yield, consumption and location context translated into practical operating forecasts.
Control
Future AI recommendations for load timing, climate, warm water and energy reserves.
Role signal
AI learned in the operating layer.
Cerbo AI is not positioned as a finished product launch. It is a serious build project for understanding AI systems where UX, data, forecasts, automation and real-world operating constraints meet.
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