Farmhand AI
Autonomous rover that monitors livestock, tracks anomalies, and captures agronomy data with onboard computer vision.
I design and deploy AI that thrives in the real world—where bandwidth is scarce, safety matters, and operations teams need explainable telemetry.
Safety & Mobility
Wildfire, utilities, micromobility
Stack
YOLOv8 · TensorRT · Jetson · WebRTC
Focus Areas
Computer Vision · Sensor Fusion · Accessibility
Engagements
Rapid prototyping → Enterprise rollouts
Edge AI drone detection platform
Dronevade is an in-progress platform that couples custom computer vision, RF sensing, and thermal imaging to help wildfire, utilities, and public safety teams detect unauthorized drones in real time.
Edge-ready pipelines
Quantized models, remote updates, observability hooks
Pilot-ready
Site surveys and demo deployments underway with wildfire agencies
Secure architecture
Air-gapped inference + encrypted telemetry
Autonomous rover that monitors livestock, tracks anomalies, and captures agronomy data with onboard computer vision.
Predictive safety radar that blends sensor fusion with ML to warn cyclists about vehicles, near misses, and hazardous routes.
Spatial captions for XR platforms that keep deaf and hard-of-hearing users inside the conversation in virtual spaces.
Thermal anomaly detection that helps wildfire crews and utilities identify hotspots before ignition or equipment failure.
Clear phases keep AI work grounded in measurable outcomes while giving product, engineering, and operations teams full visibility into progress.
Feed user interviews, field studies, and feasibility prototypes into a concise technical charter and ROI model.
Ship iterative releases that pair robust ML pipelines with test harnesses, telemetry, and stakeholder demos.
Operationalize the solution with playbooks, alerting, and continuous feedback loops to keep accuracy high post-launch.
Real-time detection, tracking, and geospatial analytics for mission-critical video.
Model prototyping, MLOps pipelines, and predictive systems aligned to business outcomes.
Deployments on Jetson, Raspberry Pi, and embedded hardware with low-latency inference.