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@TruGanic

TruGanic

AI-enhanced blockchain system for transparent organic food traceability using Zero Trust and IoT.

🌿 TruGanic

AI-Enhanced Blockchain System for Transparent and Scalable Organic Food Traceability

TruGanic is a decentralized ecosystem designed to solve the "trust deficit" in organic supply chains. By integrating Hyperledger Fabric, IoT-driven AI, and Zero Trust security, we provide a tamper-proof record of food from the farm to the consumer's hand.


🚀 The Problem

  • Trust Deficit: There is a pervasive lack of authenticity and consumer trust in organic food systems.
  • Traceability Gap: Current data suggests that 40% of organic products cannot be traced back to their source.
  • Systemic Vulnerabilities: These gaps undermine the growth and global integrity of the entire organic sector.

🛠️ Research Pillars & Solution Overview

Our solution bridges four critical research gaps through a multi-layered architecture:

1. Novel Architecture with Zero-Trust Security

  • Developer: Weerapperuma W. D. Y. C.
  • Focus: Novel Architecture with Zero-Trust Security and Dynamic Plugin Management.
  • Contribution: Ensures every service-to-service interaction is authenticated, eliminating implicit trust in distributed systems.

2. AI-Powered Soil Anomaly Detection Engine

  • Developer: Thilakarathna S. N. R. W. W. C. N.
  • Focus: Addressing the Data Veracity Gap via IoT field monitoring.
  • Contribution: Detects chemical fertilizer usage through real-time soil property analysis and cross-references farmer logs.

3. Offline-First Blockchain with IPFS Integration

  • Developer: Alwis D. A. C.
  • Focus: Solving the Connectivity and Scalability Gap.
  • Contribution: Implements an edge-based blockchain to handle offline logistics caching and ensure data integrity in "dead zones".

4. Machine Learning and Augmented Reality Visualization

  • Developer: Rashmina W. W. K.
  • Focus: Closing the Usability Gap.
  • Contribution: Translates raw blockchain records into consumer-friendly insights using an ML insight engine and AR applications.

🎯 Key Performance Objectives

Metric Goal
Fraud Detection Accuracy >95% with <2-hour alert latency
System Availability >99.5% with near-zero downtime using Decentralized Identifiers
Data Integrity Close to 0% data loss in edge cases
System Latency <3 seconds for real-time consumer trust badges

📈 Commercialization & Value Proposition

  • Target Markets:
    • Premium Organic Producers & Cooperatives.
    • Logistics & Cold-Chain Providers.
    • High-End Retail Chains.
    • Regulatory & Certification Bodies.
  • Value Proposition:
    • Elimination of "Trust Fraud": Data-backed verification of organic status.
    • Uninterrupted Data Integrity: Reliable tracking even without internet connectivity.
    • Consumer-Ready Intelligence: Direct, visual proof of food quality via AR.
  • Financial Feasibility:
    • Initial Setup: Estimated between $5,000 – $15,000.
    • Operational Costs: Low per-batch cost (~$0.50 – $2.00).
    • Scalability: High feasibility with horizontal scaling capabilities.

⚙️ System Workflow

  1. Security Management: System admin initiates and manages service-to-service security using zero trust architecture.
  2. Origin Logging: Farmer data flows to the blockchain while certification bodies receive real-time alerts.
  3. Logistics Tracking: Transport agents log trip data with specialized handling for offline edge cases.
  4. Consumer Verification: Consumers access data via the ML insight engine and AR application.

Adoption Plan:

  • Phase 1: Controlled Pilot (Months 1-4).
  • Phase 2: B2B Integration & Certification (Months 5-10).
  • Phase 3: Consumer Rollout (Months 11+).

Pinned Loading

  1. service-blockchain-network service-blockchain-network Public

    Infrastructure configuration for the Blockchain network. Contains docker-compose files, channel artifacts, crypto-material generation, and deployment scripts for Hyperledger Fabric.

    Shell

  2. client-transport-agent client-transport-agent Public

    Edge based mobile solution for prioritizing the offline-first archtiecture.

    TypeScript

  3. soil-anomaly-detection-engine soil-anomaly-detection-engine Public

    Python-based anomaly detection service for organic soil verification.

    Python

  4. client-farmer client-farmer Public

    A React Native mobile app for comprehensive farm management, including planting, input tracking, and harvest logging

    JavaScript

  5. platform-core platform-core Public

    Enterprise core platform providing zero-trust security framework with DID/Verifiable Credentials authentication and zero-downtime deployment capabilities. Features canary deployments, traffic split…

    TypeScript

  6. ar-ml-client-interface ar-ml-client-interface Public

    Wolfram Language

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