🌍 GheiaGrid

A decentralized, zero-trust bio-economic grid for urban farming.

The GheiaGrid is an IoT-driven, AI-powered platform designed to securely ingest distributed urban farming node data, archive it immutably, and reward ecological action. This platform bridges the gap between biological systems, machine-to-machine agents, and the blockchain using enterprise-grade zero-trust principles.

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⚡ Architecture & Tech Stack

This project features a highly decoupled, modern tech stack designed for security, scale, and interactivity:

• Frontend: Next.js 15 (App Router), React 19, Tailwind CSS v4, and Framer Motion for a highly reactive, physics-based UI.
• Theme: "Sleek Interface" (Cyberpunk-meets-nature aesthetic, Inter & JetBrains Mono typography).
• Identity & Access (Zero-Trust): Secures the grid using Auth0 Machine-to-Machine (M2M) authentication. The backend dynamically downloads Auth0 JWKS to mathematically verify the RSA signature and enforce write:sensor_data scopes before dropping the payload.
• Data Lake (Snowflake): Built to handle massive streams of continuous telemetry (moisture, ambient CO2, temperature) via the Snowflake SDK. Extracts raw device telemetry into flexible VARIANT columns without breaking database schemas.
• Data Provenance (Solana): Integrates Solana web3.js to autonomously generate SHA-256 hashes of incoming data and authorize them to the Devnet ledger, providing mathematical proof against data tampering.
• AI Engine (Google Gemini): Utilizes @google/genai (Gemini 3.1 Pro) for multimodal plant health diagnostics. Upload plant photos to autonomously identify chlorosis and nutrient deficiencies directly in the browser via streamed markdown parsing.

🚀 Key Features

• Real-time HUD Dashboard: A tactical command center with animated entrances, live global ticking network stats, and dynamic progress bars.
• Live Sensor Feed: The UI actively polls and syncs with local temporary memory—flashing the Data Lake Analytics UI and swapping active Urban Farm nodes dynamically when pinged.
• Automated Diagnostics: Seamless integration with Google's state-of-the-art vision models to prescribe organic, urban-farming-compliant treatments.
• Immutable Ledger Recording: Live feed of simulated Solana transactions securely logging data payload proofs.

🛠️ Getting Started

Prerequisites

Ensure you have Node.js 20+ installed. You will also need active accounts and API configurations for:

• Google Gemini API
• Auth0 (M2M Application Setup & Tenant Domain)
• Snowflake (Warehouse, Database IOT_DB, Schema PUBLIC)
• Solana (Devnet configuration is mocked locally unless private keys are provided)

Installation

1. Clone the repository

   git clone https://github.com/kheai/gheia.git
   cd gheia

2. Install dependencies

   # If on an older Mac, run: npm install --ignore-scripts
   npm install

3. Environment Variables Copy .env.example to .env and populate your secrets:

   cp .env.example .env

   Ensure GEMINI_API_KEY, AUTH0_ keys, and SNOWFLAKE_ credentials are set.

🧪 Testing the Live Pipeline

We built a standalone edge-device simulator to prove the end-to-end Zero-Trust pipeline.

1. Boot the Backend / UI Open Terminal 1 and start the Next.js server:

   npm run dev

2. Fire the Edge Sensor Open Terminal 2 and trigger the backend M2M script:

   npm run mock-sensor

3. Verify the Magic

   • Terminal 2 requests a token from Auth0 and POSTs the encrypted payload.
   • Terminal 1 mathematically verifies the Token, pushes the VARIANT JSON to Snowflake, generates an SHA-256 hash, and mocks the Solana confirmation.
   • The Browser UI (http://localhost:3000) actively detects the new payload, increments the Data Lake sync count with a glowing pulse, and updates the Node Grid with live simulated moisture data!

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.