Solana Emotional Metadata

This repository contains the Solana Foundation grant implementation for high-performance emotional data tracking with 90%+ compression.

Project Overview

We propose developing a high-performance Solana program for efficient on-chain storage and validation of real-time creative metadata. Using Solana's State Compression and innovative data structures, this module will record live parameters from creative performances - including emotional states, shader seeds, and performance data - enabling the tokenization of ephemeral live art that was previously impossible to capture on-chain.

Features

• Real-time Emotional Data Tracking: Live recording of emotional states with 90%+ compression
• State Compression: Novel algorithms for affective computing data
• High Throughput: Thousands of parameter updates per minute
• Solana Integration: Native Solana program with Anchor framework
• Practical Emotional Input: Multiple input methods including camera-based facial expression analysis

Getting Started

Prerequisites

• Rust and Cargo
• Node.js and npm
• Solana CLI
• Anchor framework
• Phantom wallet (for testing)

Installation

# Install CLI tools
./scripts/install-cli-tools.sh

# Build the project
./build-solana-grant.sh

Building

# Build Solana program
cd src/solana-client
anchor build

# Run tests
anchor test

Deployment

1. Deploy program to Solana devnet
2. Update program ID in test-website configuration
3. Serve test-website on a web server

Practical Emotional Input Methods

Our system implements multiple practical approaches for collecting emotional data that work without specialized hardware:

1. Manual Input Methods (Primary Approach)

   • Simple slider controls for valence, arousal, and dominance
   • Works on any device with a browser
   • No special hardware required

2. Camera-Based Analysis (Enhancement)

   • Facial expression analysis using standard webcams
   • Local processing for privacy
   • Real-time emotional state detection

3. Interaction Pattern Analysis (Passive Collection)

   • Keyboard typing rhythm analysis
   • Mouse movement dynamics
   • Subtle emotional inference from user behavior

4. Voice Tone Analysis (Audio Input)

   • Microphone-based emotional inference
   • Local processing for privacy
   • Real-time analysis during creative sessions

5. EEG/BMI Integration (Future Enhancement)

   • Compatible with consumer biometric devices
   • Advanced emotional state detection
   • Research-grade precision for specialized applications

Directory Structure

├── src/
│   ├── solana-client/      # Solana program and client code
│   └── rust-client/        # Core Rust library (shared dependency)
├── test-website/           # Browser-based frontend
├── scripts/                # Utility scripts
├── build-solana-grant.sh   # Build script
└── README.md              # This file

License

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

Contact

• Website: https://compiling-org.netlify.app
• GitHub: https://github.com/compiling-org
• Email: kapil.bambardekar@gmail.com, vdmo@gmail.com