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🧾 AidVerify – AI-Powered Transparent Aid Distribution Platform

Building trust through technology — making every donation count.
AI + Blockchain for transparent, fraud-free humanitarian aid.

🔹 Project Title & Summary

Title: AidVerify – Blockchain & AI-Powered Transparent Aid Distribution Platform

Summary:
Fraud and mismanagement in humanitarian aid systems often prevent donations from reaching real beneficiaries. AidVerify is an AI + Blockchain-powered platform that brings transparency, trust, and traceability to aid distribution.

The system uses AI-based face recognition to verify beneficiaries in real time, ensuring that no person receives duplicate or unauthorized aid. All NGO applications and donation records are securely stored on the blockchain, offering immutable transparency for donors and administrators.

An integrated AI NGO Verification API authenticates NGOs through document OCR and online cross-verification, ensuring that only legitimate organizations are approved.

Donors can monitor campaign progress, transaction hashes, and fund utilization reports — guaranteeing end-to-end visibility.

With FastAPI-based AI microservices, Ethereum smart contracts, and a React + Node.js architecture, AidVerify showcases how emerging technologies can restore public trust in social welfare systems — truly making every donation count.

🔹 Problem Statement

Billions of dollars in humanitarian aid are lost annually due to fraudulent claims, identity manipulation, and opaque fund distribution.

Existing platforms lack reliable identity verification mechanisms, resulting in duplicate beneficiaries and unverified NGOs. This erodes public confidence, discourages donations, and leaves genuine victims unsupported.

AidVerify addresses this global challenge by:

Verifying beneficiaries through AI-powered face recognition
Auditing NGOs via AI document validation
Recording all aid transactions on the blockchain for permanent transparency

🔹 Target Audience / Beneficiaries

💰 Donors: Individuals, corporations, and institutions seeking transparent charity impact.
🏢 NGOs: Verified organizations managing legitimate aid campaigns.
👨‍👩‍👧‍👦 Beneficiaries: Genuine recipients of humanitarian support.
🏛️ Government/Regulators: Oversight bodies ensuring fairness and compliance in aid distribution.

🔹 Proposed Solution

AidVerify guarantees that aid reaches the right people through a three-tier verification pipeline:

🧠 AI Face Verification: Real-time beneficiary identification with liveness detection and duplicate prevention.
📑 AI NGO Verification: Automatic document scanning, OCR-based authenticity checks, and cross-referencing with public records.
⛓️ Blockchain Transparency: Immutable logs of donations, fund utilization, and NGO approvals for complete auditability.

Its modular AI microservices and Ethereum smart contracts form a unified, fraud-resistant, and scalable ecosystem.

🔹 Technical Approach & Tech Stack

🖥️ Frontend

React 19.1.1
Vite, TailwindCSS, Radix UI
Clerk Authentication

⚙️ Backend

Node.js, Express.js
MongoDB, Cloudinary
JWT Authentication, Multer

🤖 AI/ML Services

FastAPI, InsightFace, YOLOv8/v11
ONNX Runtime, OpenCV, OCR (Tesseract)

⛓️ Blockchain

Solidity (v0.8.18), Ethereum Network
Truffle, Web3.js, IPFS

Approach Justification:

FastAPI + ONNX Runtime ensures low-latency AI inference.
Ethereum provides decentralized and verifiable transparency.
Microservice architecture enables modular scalability and independent upgrades.
Cloudinary + IPFS securely manage images, proofs, and documents.

🔹 Impact & Feasibility

🌍 Transparency: Every donation is publicly traceable on the blockchain.
🔒 Fraud Reduction: Prevents fake NGOs and duplicate aid claims through AI-based verification.
⚡ Scalability: Cloud-native microservices allow easy deployment across regions.
❤️ Social Value: Restores confidence in humanitarian systems and optimizes real-world impact.

AidVerify is deployable on AWS or GCP, using MongoDB Atlas and Smart Contracts on Testnet/Mainnet, making it ready for NGO pilots and CSR initiatives.

🔹 Challenges & Learnings

🚧 Challenges

Handling low-quality mobile face captures during real-world verification.
Synchronizing AI inference latency with blockchain transactions.
Managing large-scale document datasets during OCR-based NGO validation.

🎓 Learnings

Integrating AI and Blockchain can create scalable, trust-driven ecosystems.
Emphasized the importance of data preprocessing and model optimization.
Gained deeper understanding of ethical AI design, prioritizing fairness and privacy.