Machine Analytics Dashboard – Real-Time Monitoring & Sensor Insights

Monitoring and analyzing machine performance data is crucial for industrial efficiency and predictive maintenance. Machine Analytics Dashboard is a multi-page web application designed to give engineers, technicians, and managers a real-time overview of machine health, detailed sensor insights, and actionable analytics — all in one intuitive interface.

Project Overview

The dashboard provides a centralized platform to monitor machine status, analyze sensor data, and track key performance metrics. By combining interactive visualizations, detailed machine insights, and time-series sensor analysis, the platform helps teams identify issues early, optimize operations, and reduce downtime.

Key Features

Dashboard Overview: KPI cards, machine status pie charts, and search/filter controls for quick insights.

Machine Details: Drill down into individual machines to view sensors, bearings, and performance metrics.

Sensor Analysis: Time-series visualizations for individual sensors, helping detect anomalies and trends.

Responsive Design: Clean UI optimized for desktop and tablet usage.

Tech-Forward Stack: Built using Next.js, React, TypeScript, FastAPI, and Supabase for a modern, scalable solution.

Technology Stack

Frontend: Next.js 15, React 19, TypeScript, ECharts

Backend: Python FastAPI with Supabase integration

Database: Supabase (PostgreSQL)

Styling: Custom CSS with responsive design

My Role

I was responsible for frontend development and API integration, creating interactive dashboards, dynamic charts, and detailed machine views. I collaborated on backend API design and ensured smooth communication between frontend components and Supabase database.

Why We Built It

Industrial operations generate massive amounts of sensor data, but visualizing and analyzing this data in real time is often challenging. Machine Analytics Dashboard simplifies this process, providing actionable insights, reducing downtime, and helping teams make data-driven decisions.

Future Enhancements

Add user authentication and role-based access control

Integrate real-time updates with WebSockets

Implement advanced data visualizations and predictive analytics

Enable export of reports in CSV/PDF formats

Optimize fully for mobile and tablet devices

Add unit and integration testing for reliability

Deploy to a production environment for real-world usage

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