Remote Industrial Monitoring via AWS

Overview

This project implements a cloud-based industrial monitoring system using AWS serverless services and IoT devices. It enables real-time monitoring of industrial parameters such as temperature and vibration and provides automated alerts for abnormal conditions.

Problem Statement

Manual monitoring of industrial equipment is inefficient and may lead to delayed fault detection, increased downtime, and safety risks.

Solution

An IoT-enabled monitoring solution that collects sensor data from industrial equipment, processes it in the cloud, and triggers real-time alerts using AWS services.

Architecture

• ESP32 with industrial sensors
• AWS S3 for centralized data storage
• AWS Lambda for serverless data processing
• AWS SNS for real-time alert notifications

Workflow

1. Sensors collect temperature and vibration data.
2. ESP32 sends data to the cloud.
3. Data is stored in AWS S3.
4. AWS Lambda evaluates sensor readings.
5. AWS SNS sends alerts when thresholds are exceeded.

Technologies Used

• AWS S3
• AWS Lambda
• AWS SNS
• ESP32
• Python (MicroPython)

Outcome

• Real-time industrial equipment monitoring
• Automated alerting for abnormal conditions
• Reduced downtime and improved operational safety

Future Enhancements

• Integration with dashboards for visualization
• Predictive maintenance using analytics
• Expansion to multiple industrial units