Drone Surveillance for Wildlife

Problem

Wildlife monitoring over large landscapes is expensive when it depends only on patrols. Aerial imagery can help if models survive canopy, dust, and the rarity of the animals that matter.

Context

Applied aerial computer vision for wildlife detection and monitoring over large landscapes.

Dataset

Drone imagery from conservation monitoring contexts.

Methodology

Aerial computer vision for detection and monitoring, with spatial context retained rather than discarded.

Model / architecture

Detection models over aerial frames.

Results

Applied vision system for conservation-adjacent monitoring.

Evaluation metrics

Modality · unverified

Aerial imagery

Challenges

Small-object detection, extreme class imbalance, and operational constraints on drone flight.

Impact

A conservation-adjacent application of the same vision and spatial toolkit used in agriculture and health.

Tools / technology

• Python
• Computer vision
• Spatial analytics