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predictmaintenance

Predictive Maintenance with AI

Hackathon Project: Real-time failure prediction for connected devices

🚀 Problem Statement

Equipment failures disrupt services and incur high repair costs. By predicting failures in advance, businesses can schedule maintenance, reduce downtime, and save costs.

🌟 Solution

This AI-powered tool predicts device health using network logs (CPU usage, memory usage, error count). It includes:

  • A machine learning model for real-time failure prediction.
  • A REST API to serve predictions.
  • An interactive dashboard for end-users.

💻 Features

  1. Predict device health (Healthy or Fail).
  2. Real-time inputs via the dashboard.
  3. REST API for seamless integration.

🛠 Tech Stack

  • Backend: Python, Flask
  • Frontend: Streamlit
  • Machine Learning: scikit-learn
  • Deployment: Docker-ready

📂 File Structure

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