System Features & Capabilities
Discover how COCOFLUX AI combines camera vision, multi-spectral diagnostics, and edge computing.
Camera-Based Coconut Moisture Content Analysis
Utilizes advanced optical computer vision and neural networks to evaluate copra meat translucency, surface sheen, shrinkage folds, and dryness indicators without destructive testing.
UV 365nm Fluorescence Aflatoxin Detection
Detects bright greenish-yellow fluorescence (BGYF) caused by Aspergillus flavus and Aspergillus parasiticus molds, measuring exact mold surface coverage percentage.
Automated Philippine Coconut Authority (PCA) Grading
Instantly classifies copra into Grade A (Superiore / <6-7% MC), Grade B (Corriente / 7-9% MC), Grade C (9-12% MC), or Reject (>12% MC / High Mold).
Raspberry Pi & Edge Compute Integration
Operates seamlessly on Raspberry Pi edge hardware with local camera optics, offline buffer caching, and automatic cloud synchronization.
Bilingual English & Filipino Interface
Designed for Filipino farmers, technicians, and depot operators with full localized terminology in Tagalog and English.
Official Copra Grading & Moisture Standards Matrix
Classifications aligned with Philippine Coconut Authority (PCA) and AI vision standards
Moisture Content ≤ 6.0%, Mold < 5%. Crisp, translucent copra meat with high oil content. Suitable for premium coconut oil extraction.
Moisture Content 6.1% - 8.0%, Mold 5% - 10%. Acceptable commercial copra. May need slight further aeration.
Moisture Content 8.1% - 12.0%, Mold 10% - 18%. High moisture; immediate re-drying in tapahan required to prevent aflatoxin growth.
Moisture Content > 12.0% or Mold > 18%. Severe Aspergillus flavus contamination, hazardous aflatoxin toxins detected. Unsafe for food/feed.