Multi-sensor embedded integration
Camera sensor boards, custom stereo depth modules, ADC temperature sensing, DAC LED current control — photometric calibration and acquisition synchronization across the full optical chain.
Problem
Quantitative optical measurement is only as good as the hardware that produces the raw data. A device that infers absolute optical properties needs its cameras, illumination, and sensors to behave predictably and in lockstep — otherwise the physics downstream is fitting to artifacts of an uncalibrated, unsynchronized acquisition.
That means bringing a heterogeneous set of components into one coherent optical chain: imaging sensors, depth sensing, temperature, and controllable illumination, each with its own timing and calibration requirements, all on embedded compute.
Approach
I integrated the multi-sensor hardware end to end — camera sensor boards, custom stereo depth modules, ADC temperature sensing, and DAC-based LED current control — so illumination, imaging, and sensing operate as one system rather than a bag of parts. The stereo modules add depth to the capture; the ADC and DAC paths let the system read its own state and drive the light sources precisely.
On top of that I built photometric calibration and acquisition synchronization across the full optical chain, so measurements are comparable frame to frame and the illumination, capture, and sensor reads line up in time. This integration work runs on the same embedded targets as the inference pipeline, which is what lets calibrated capture and on-device analysis coexist.
What shipped
The optical chain is integrated and calibrated end to end — stereo vision plus photometric calibration and acquisition synchronization across cameras, illumination, and sensors — giving the models upstream a clean, synchronized signal to work from.
It is the foundation the rest of the stack stands on: every coefficient the pipeline recovers traces back to a capture that this layer made trustworthy.