EcoVoice an AI powered Environmental Reporter for Underserved Communities

Source: Dev.to

What it does

EcoVoice is an AI‑powered mobile/web platform that:

• Records & transcribes oral testimonies about local environmental issues (e.g., pollution, deforestation) via voice input.
• Analyzes sentiment & keywords to identify urgent themes (e.g., “toxic water,” “illegal logging”).
• Geotags & visualizes stories on an interactive map, revealing regional hotspots.
• Generates advocacy briefs—automatically converting narratives into shareable reports for NGOs, journalists, and policymakers.
• Connects users to local environmental organizations for direct action.

Example: A fisher in Bangladesh records a declining catch due to river pollution → EcoVoice maps the issue, alerts nearby NGOs, and compiles data for a UN environmental report.

How I built it

Frontend: React Native (mobile) + Next.js (web) for cross‑platform accessibility.

Backend: Firebase (real‑time DB, auth) + Node.js.

AI/ML:

• Whisper API for multilingual speech‑to‑text (supports 50+ languages).
• Custom NLP model (spaCy + BERT) trained on environmental justice datasets to classify issues and sentiment.

Geospatial: Mapbox for map visualisation.

Ethical design: On‑device processing for sensitive data + user‑controlled privacy settings (opt‑in data sharing).

Challenges I ran into

• Noise‑robust transcription – Field recordings often had background noise (traffic, wind).
  Solution: Implemented audio preprocessing filters and fine‑tuned Whisper on noisy environmental datasets.

• Bias in AI analysis – Early models misclassified Indigenous land‑rights narratives as “low urgency.”
  Solution: Partnered with environmental‑justice groups to co‑train the NLP model on diverse cultural contexts.

• Offline accessibility – Many users lack stable internet.
  Solution: Added offline‑first functionality; stories sync when connectivity resumes.

Accomplishments that I’m proud of

• ✅ Real‑world impact: Piloted in 3 communities (Philippines, Kenya, Brazil), leading to 2 local policy reviews on waste management.
• ✅ Ethical AI recognition: Won “Best Social Impact” at [Hackathon Name] for our bias‑mitigation framework.
• ✅ Scalable architecture: Handles 10k+ stories with “EcoVoice turns unheard environmental stories into unstoppable movements.”