Energy AI Project

Embedded Multisensor UAV Imaging System for Environmental Monitoring

Environmental monitoring needs thermal and multispectral images tied to a precise location and time. I built a Raspberry Pi 4 controller that receives ground-station commands, triggers both cameras, and logs GPS data with each capture. The integrated system supports geotagged imagery for wildfire and vegetation research.

What I Learned: I learned to configure a Raspberry Pi and use Python with pymavlink to pass commands from the ground station to the UAV. Connecting camera triggers to GPS timestamps showed me why timing matters when imagery needs accurate location data.

Mavlink Python Raspberry PI 4 Radio Communication RTK GPS System View GitHub Repo
Energy AI Project

Multi-Sensor UAV (Dual Payload)

Wildfire research needs thermal and multispectral views of the same burn site. I built a dual-sensor UAV with FLIR and Altum PT cameras, a lightweight printed mount, and an OrangeCube flight controller. The platform collected imagery over burn sites for fire and vegetation analysis.

What I Learned: I learned to integrate thermal and multispectral cameras with a flight controller for autonomous collection. Iterating on the mount in SolidWorks and using the UAV over burn sites taught me to balance payload stability, weight, and field needs.

3D - Design QgroundControl SolidWorks Mission Planner
Main project image

Motorized 3-Axis Camera Gantry

Imaging work needed repeatable camera movement across three axes. I built an Ethernet-controlled gantry with stepper motors, linear rails, regulated power, and limit switches. It moves the camera along X, Y, and Z while stopping before the rails' physical limits.

What I Learned: I learned to size a power supply for stepper motors, organize their wiring with terminal blocks, and control movement over Ethernet. Adding limit switches and custom acrylic strikers taught me to build safety into the gantry's mechanical design.

StepEva3 Stepper Motors C++ CAN Bus Soldering Designer