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Artificial Intelligence & Environment

Forest Health Assessment Through CNN

A drone-based NDVI imaging system for environmental health monitoring, integrating a Raspberry Pi with CNN-based analysis.

Role
Lead Software Developer
Dates
June 2023 — August 2024
Capabilities
Computer vision · Raspberry Pi / embedded systems · NDVI remote sensing · CNN model development

01

Problem / Opportunity

Ground-based forest health assessment is slow and hard to scale — remote imaging paired with automated analysis can cover more ground faster.

02

Role & Team

Lead Software Developer — imaging pipeline and CNN analysis.

EDIT: Add this detail once available.

03

Process & Timeline

Integrated a Raspberry Pi with a drone-mounted imaging setup to capture NDVI data, then built a CNN pipeline to analyze the imagery for environmental health indicators.

04

Technical Approach

Raspberry Pi–based drone imaging system feeding NDVI imagery into a CNN model for automated environmental health analysis.

05

Key Decisions

EDIT: Add this detail once available.

06

Challenges & Iteration

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07

Results & Outcomes

Built and integrated a full drone-to-CNN monitoring pipeline

EDIT: Add this detail once available.

08

Reflection

EDIT: Add this detail once available.

Contact

Building something
ambitious?

I'm up for conversations about technical opportunities, AI and data projects, early-stage startups, research collaborations, product experimentation, and mission-driven technology.

I'm always interested in thoughtful people, difficult problems, and ideas worth building.

Or send a message directly

© 2026 Navya RawalSan Francisco, California