🧠 NeuroMapping: AI & Gemini-Powered Cognitive Safety Hack 🌟

🚀 Executive Summary

NeuroMapping is a cutting-edge AI-driven cognitive safety system designed to empower users aged 13+ with personalized cognitive insights, while fostering open source learning for the wider community 🌍. Built for the MLH Open Source Hackfest, it integrates:

  • CNN + Transformer Hybrid Model for multi-channel EEG analysis 🧠

- Gemini API for human-like interpretive reasoning 💡

Click here to see how I used Gemini and AI models in the NeuroMapping project

  • Fully open-source (MIT License), beginner-friendly, and scalable

Our goal: maximize social impact while staying beginner-friendly and fully aligned with MLH hackathon rules ✅.


🔹 Core Features

  1. Hybrid AI Ensemble 🤖
    • CNN → Spatial feature mapping of EEG signals
    • Transformer → Temporal pattern recognition
  2. Gemini API Integration 💡
    • Converts raw risk scores to digestible insights and proactive interventions
    • Adds personalized social engagement feedback
  3. Interactive Dashboard 🎨
    • Live Cognitive Heatmaps
    • Risk Scores + Confidence Intervals ($\pm 12\%$)
    • Gamified social impact metrics for awareness and education 🏆

🏗 Workflow

Simulated EEG signals ($X$) → Preprocessing (ICA, noise filtering) →
CNN + Transformer Feature Extraction → Weighted Fusion → Cognitive Risk Score →
Gemini API → Dashboard Visualization & Social Engagement


Click me to see my Dashboard

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Where:

$$ \begin{aligned} X &\;=\; \text{multi-channel EEG input (64 channels)} \[1mm] w_C, w_T, w_G &\;=\; \text{learned fusion weights} \[1mm] \mathcal{Z} &\;=\; \text{normalization constant ensuring } 0 \le y \le 100 \[1mm] \mathbf{Risk Flags} &\;\in\; {0,1} \;\text{(output triggers cognitive risk flags)} \[1mm] \text{Gemini API} &\;=\; \text{provides personalized, human-centric insights and recommendations} \end{aligned} $$

  • Gemini API ensures personalized advice, beginner-friendly explanations, and social-good recommendations 🌟

-See how Snowflake and Gemini API are integrated in NeuroMapping: Click here

click to see how to run the NeuroMapping project locally

🎨 Dashboard & Metrics

Metric Status Detail
Cognitive Risk Score ██ 73% Individual baseline + demographic calibration ⚠️
Confidence Interval Medium ±12%
Social Impact Active 47 Awareness Sessions ✅, 12 Peers Educated 🏅

📈 Temporal Risk Evolution (Last 7 Days)
▁▂▃▅▂▁▃▅▇▁▂▃


🌍 Community Engagement & Gamification

  • Awareness Sessions: 47 🏆
  • Peers Educated: 12 👥
  • Risk Assessments Completed: 3 ✅
  • Mini-Challenges for engagement (share story ✍️, complete tutorial 📚)

🔐 Privacy & Security

  • AES-256 encryption 🔒
  • Federated learning for safe AI training 🧑‍💻
  • Local computation to minimize data exposure 🌐

🏁 Hackathon (MLH Open Source Hackfest)

  • Gemini API usage for personalized AI output (Best Use of Gemini API prize focus) 🌟

- Fully open-source, MIT Licensed with documentation & contributing guidelines 📑

NeuroMapping Project Documentation


📘 Full Research Documentation (PDF)

  • Demo video ≤ 2 minutes
  • Public repo requirement ✅
  • No prior work submission; created during hackathon ✅

🚀 Deployment Roadmap

  1. Phase 1: Prototype & synthetic data validation ✅
  2. Phase 2: Community beta testing (n=50–100) 🔄
  3. Phase 3: Public release + social engagement 🌍

NeuroMapping Project – MLH Open Source Hackfest

Repository

Access the full project repository on GitHub:
NeuroMapping GitHub Repository

Key Documentation Files

NeuroMapping: AI + Gemini-powered, beginner-friendly, socially impactful, fully open-source hackathon project designed to maximize learning, engagement, and MLH hackathon prizes! 🌟🧠🌍

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