Case Study • IOT

Smart Factory IoT Monitoring System

Real-time industrial monitoring with predictive maintenance reducing downtime by 73%.

73%
Downtime Reduction
94%
Predictive Accuracy
$2.4M
Annual Savings
200+
Connected Machines

The Story

We designed and deployed a comprehensive IoT monitoring solution for a manufacturing plant with 200+ machines. The system collects real-time data from sensors, predicts equipment failures, and automates maintenance scheduling.

Challenges

  • 1Legacy equipment with no digital connectivity
  • 2Unplanned downtime costing $50,000 per hour
  • 3No visibility into equipment health
  • 4Scattered data across multiple systems

Solutions

  • Retrofitted sensors for legacy equipment monitoring
  • Built edge computing nodes for local processing
  • Developed ML models for failure prediction
  • Created unified dashboard for plant-wide visibility

Technology Stack

Tools and technologies used in this project

ESP32MQTTAWS IoT CoreTensorFlowInfluxDBGrafana
"The predictive maintenance system pays for itself every month. Downtime is now a planned event, not a crisis."
Michael Torres
Plant Manager

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