Data Transparency & Ethics
Privacy Policy
Last Updated: July 2026 • AgriBoost Academic Beta Project (KNUST)
Academic Project Notice: AgriBoost is a final-year graduation capstone project at Kwame Nkrumah University of Science and Technology (KNUST), Kumasi, Ghana, authored by Etornam and Doreen. Any data submitted during beta testing is handled responsibly and strictly for testing platform features and AI diagnostic capabilities.
1. Information We Collect
When you register or interact with the AgriBoost beta web platform, we may collect the following limited information:
- Account Credentials & Profile: Full name, email address, user role (Farmer or Buyer), and optional farm location.
- Farm & Agricultural Data: Parcel acreage, crop varieties, planting schedules, and projected harvest logs.
- Diagnostic Images: Crop leaf images uploaded for AI plant disease analysis and model accuracy evaluation.
- Marketplace Postings: Produce listings, price quotes, unit sizes, and order records created during transactions.
2. How We Use Your Information
Because AgriBoost is an academic research prototype, collected data is used exclusively to:
- Provide essential web platform features (dashboard logging, simulated escrow payments, and produce catalogs).
- Train, validate, and evaluate deep learning image diagnostic models for tropical crop health as part of our KNUST project deliverables.
- Analyze aggregated system interactions to optimize offline PWA performance and usability.
3. Data Protection & Non-Commercialization
We prioritize responsible data ethics:
- No Commercial Monetization: We do not sell, rent, or trade personal or farm data to commercial advertisers or data brokers.
- Aggregated Metrics: Public analytics (such as total acreage or diagnostic volume) are displayed strictly as anonymized totals.
- Cloud Protection: Authentication and database storage are protected with Supabase Row Level Security (RLS).
4. Data Deletion & Inquiries
Users participating in our beta test may request deletion of their account or farm logs at any time during the evaluation phase.