Course Content

Introduction:

In modern industries, continuous monitoring of various parameters such as temperature, humidity, gas leakage, machinery status, and electrical variables is essential for ensuring safety, productivity, and predictive maintenance. The Internet of Things (IoT) has revolutionized this by enabling real-time remote monitoring, data logging, and control over industrial environments.
This project aims to design an IoT-based industrial monitoring system that collects sensor data and uploads it to a cloud platform, allowing users to visualize, analyze, and act upon this data from anywhere.

Working Principle:

The system works on the principle of sensor-to-cloud communication:

• Multiple sensors are connected to a microcontroller (like ESP32 or Arduino + Wi-Fi module).

• These sensors continuously collect real-time data from the industrial environment.

• The microcontroller processes and sends this data to an IoT cloud platform (like ThingSpeak, Blynk, or Firebase) via Wi-Fi.

• The data is visualized on dashboards and notifications/alerts are triggered if any parameter exceeds predefined thresholds.

Methodology:

1. Sensing Stage:

   • Sensors (like temperature, gas, vibration, humidity) are deployed at critical locations.

2. Data Acquisition:

   • A microcontroller collects real-time data from these sensors.

3. Processing & Upload:

   • Data is processed and formatted, then transmitted via Wi-Fi to the cloud server.

4. Cloud Integration:

   • Platforms like ThingSpeak, Blynk, or Adafruit IO store, display, and analyze data.

   • Dashboards and mobile apps allow users to monitor conditions live.

5. Alert Mechanism:

   • When abnormal values are detected, SMS/email/app notifications are triggered using IFTTT, Blynk, or similar services.

6. Data Logging & Analysis:

   • Historical data is stored for trend analysis and maintenance planning.

Components Used: