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Project Talaria is a smart shoe module powered by ESP32, integrating motion tracking (MPU6050) and heart rate monitoring (MAX30102) to provide real-time insights into gait, fitness, and cardiovascular health.

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Project Talaria

In the legends of Greek mythology, the god Hermes was gifted the Talaria—golden winged sandals that granted him the power of flight, swiftness, and the ability to journey between worlds. They symbolized speed, agility, and the divine gift of connection.
Project Talaria carries this spirit into the modern age. Just as Hermes used the Talaria to bridge the realms of gods and mortals, this innovation bridges the gap between human movement and deeper self-awareness. By embedding intelligence into footwear, Project Talaria transforms every step into insight—tracking motion, stride, and heart rhythm to empower individuals with knowledge about their health, vitality, and performance.
Project Talaria is more than technology; it is a call to elevate human potential. It embodies the timeless pursuit of strength, speed, and balance, inspiring us to not only move forward but to move with purpose. Through every stride, it reminds us that like Hermes, we too can transcend limits and walk closer to greatness.

Talaria Documentation

This directory contains comprehensive documentation for the Talaria project.


Documentation Index

Getting Started

Document Description When to Read
SETUP.md Complete setup instructions First time setup
DEPLOYMENT.md Deploy to production (Vercel) When deploying

Architecture & Design

Document Description When to Read
ARCHITECTURE.md System architecture & design Understanding the codebase
ML_MODELS.md Machine learning integration Working with predictions

Reference

Document Description When to Read
CHANGELOG.md Version history & updates Tracking changes

Quick Links

For Developers

  1. New to the project? → Start with SETUP.md
  2. Understanding the code? → Read ARCHITECTURE.md
  3. Working with ML? → Check ML_MODELS.md
  4. Deploying? → Follow DEPLOYMENT.md

For Contributors

For DevOps


Documentation Structure

docs/
├── README.md              # This file - documentation index
├── SETUP.md               # Setup guide (Firebase, Vertex AI, local dev)
├── DEPLOYMENT.md          # Vercel deployment & production checklist
├── ARCHITECTURE.md        # System architecture & tech stack
├── ML_MODELS.md           # ML integration & API documentation
└── CHANGELOG.md           # Version history & updates

Common Tasks

Initial Setup

# 1. Read SETUP.md
# 2. Configure Firebase
# 3. Set up environment variables
# 4. Run npm install
# 5. Start dev server: npm run dev

Deploy to Production

# 1. Read DEPLOYMENT.md
# 2. Connect GitHub to Vercel
# 3. Configure environment variables in Vercel
# 4. Deploy

Understanding ML Integration

# 1. Read ML_MODELS.md
# 2. Set up Vertex AI credentials
# 3. Test predictions locally
# 4. Deploy with service account

Getting Help

Common Issues

Issue Solution Document
Setup problems SETUP.md - Troubleshooting
Deployment errors DEPLOYMENT.md - Troubleshooting
ML predictions not working ML_MODELS.md - Troubleshooting
Architecture questions ARCHITECTURE.md

Additional Resources


Contributing to Docs

When updating documentation:

  1. Keep it current - Update docs when code changes
  2. Be clear - Use simple language
  3. Add examples - Include code snippets and screenshots
  4. Test instructions - Verify setup steps work
  5. Update README - Keep this index current

Documentation Guidelines

  • Use Markdown formatting
  • Include code examples with syntax highlighting
  • Add table of contents for long documents
  • Use emojis sparingly for visual cues
  • Keep line length reasonable (80-100 chars)
  • Update "Last Updated" date when editing

Documentation Lifecycle

When to Update Docs

Event Update Required
New feature added CHANGELOG.md, ARCHITECTURE.md
Deployment process changes DEPLOYMENT.md
Setup steps change SETUP.md
ML model updated ML_MODELS.md
Dependencies updated SETUP.md, package.json
API changes ML_MODELS.md, ARCHITECTURE.md

Documentation Maintenance

Last Full Review: October 2025

Questions? Open an issue on GitHub or contact the development team.

Last Updated: October 2025

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Project Talaria is a smart shoe module powered by ESP32, integrating motion tracking (MPU6050) and heart rate monitoring (MAX30102) to provide real-time insights into gait, fitness, and cardiovascular health.

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