MicroTrack AI

AI-Powered Microplastics Exposure & Health Risk Analyzer

MicroTrack AI is a data-driven platform designed to estimate human exposure to microplastics and assess potential health risks using AI and analytics. It transforms complex environmental and scientific data into actionable insights to help users make informed lifestyle decisions.

Problem Statement

Microplastics—tiny plastic particles less than 5mm in size—are now found in air, water, and food, entering the human body through ingestion, inhalation, and skin contact. Research suggests these particles may accumulate in organs and potentially impact human health, though long-term effects are still being studied.

Solution

MicroTrack AI analyzes exposure patterns and estimates microplastic ingestion levels to provide:

• Personalized exposure insights

• Health risk indicators

• Preventive recommendations

Key Features

• AI-based microplastic exposure estimation

• Data analysis of ingestion patterns (~50,000–100,000 particles/year estimates)

• Risk assessment based on environmental and lifestyle factors

• User-friendly dashboard for insights and recommendations

Tech Stack

• Frontend: HTML, CSS, JavaScript

• Backend: Python

• Libraries/Tools: Pandas, NumPy, Machine Learning models

• Data Sources: Environmental datasets, research-based estimates

How It Works

1. Collects user/environmental data

2. Analyzes exposure sources (food, air, water)

3. Estimates ingestion levels using data models

4. Generates risk insights and recommendations

Impact

• Raises awareness about microplastic exposure

• Simplifies complex scientific research

• Helps users take preventive actions

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Future Scope

• Real-time environmental data integration

• Advanced ML models for prediction

• Mobile application support

• Personalized health tracking

Contributing

Contributions are welcome! Feel free to fork the repo and submit pull requests.

⭐ Show Your Support

If you like this project, give it a ⭐ on GitHub!