TempAI

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  This is the dashboard of our project tempAI

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  The program of the project in vscode

Inspiration

We’ve all had fevers — sometimes mild, sometimes serious — and we often don’t know when to take them seriously. Many people self-medicate or wait too long before seeing a doctor, which can make things worse. We wanted to create something that helps people understand their symptoms better and make smarter, safer health decisions using AI. That’s how TempAI was born.

What It Does

TempAI is your personal AI-powered fever assistant. It helps you log your temperature, describe your symptoms, and instantly get insights like:

What might be causing the fever

How severe it could be

What actions to take next (home care or medical attention)

It even works with IoT thermometers to track temperature changes in real time and shows your health trends through simple visual charts.

How We Built It

We built TempAI using:

React for the frontend to make it clean, simple, and mobile-friendly.

Flask + MongoDB for the backend to handle user data and predictions.

Machine Learning models trained on fever and symptom data to predict cause and severity.

Recharts for data visualization.

And for extra innovation, we tested an IoT setup using an ESP32 sensor to automatically collect temperature data.

Challenges We Ran Into

We faced a few real challenges:

Finding reliable medical datasets for fever symptoms and outcomes.

Training models to stay accurate with limited data.

Getting the IoT sensor and backend to communicate smoothly.

And of course, racing against time to make everything come together before the deadline!

Accomplishments We’re Proud Of

We’re really proud that TempAI actually works — it can predict severity and give guidance in real time. We also managed to:

Combine AI and IoT in one system.

Design a user interface anyone can use easily.

Hit around 85% accuracy in severity prediction.

Work together as a team and bring this idea to life in just a few days.

What We Learned

This project taught us so much — from data preprocessing and model tuning to designing for accessibility. We also learned how to balance innovation with simplicity, and how AI can make real differences in personal healthcare.

What’s Next for TempAI

We’re planning to take TempAI beyond the hackathon. Next steps include:

Integrating wearable devices like smartwatches for continuous monitoring.

Building a doctor dashboard for early outbreak detection.

Expanding the model to cover other conditions like flu and infections.

And developing a full mobile app so everyone can have TempAI in their pocket.

Built With

• flask
• ml
• react