An AIoT Wildlife-Smart Camera for Biodiversity Monitoring

TL;DR — I delivered an AIoT wildlife-smart camera that monitors biodiversity in remote, off-grid regions while running for long periods on limited power, thanks to on-device AI.

The Problem

Conservation teams need eyes in places where power and connectivity are scarce. Streaming raw video from remote forests simply isn't viable.

What I Built

• On-device AI ran inference locally to detect and classify wildlife, transmitting only meaningful events.
• This drastically cut bandwidth and energy use — critical for low-power, off-grid deployments.
• Azure Cloud handled aggregation, storage, and analytics, giving researchers a dashboard view of species activity across many devices.

Why It Matters

The architecture balanced edge intelligence with cloud insight — a recurring theme across my IoT work — bringing data-driven monitoring to environments previously too remote to instrument.

The Tech Behind It

Azure Cloud · On-Device AI · Edge Inference · Low-Power Firmware · IoT Telemetry