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HVS-4723. AI based next Generation Industrial Weather Monitoring System with Remote Access Predictive Analysis

6,000.00

The system utilizes an Arduino UNO microcontroller as the central processing unit, interfaced with various sensors: DHT-11 for measuring temperature and humidity, BMP180 for barometric pressure and altitude, MQ-136 for detecting harmful air pollutants (hydrogen sulfide), and MQ-3 for sensing alcohol or gas presence in the atmosphere.

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In the era of Industry 4.0, real-time and intelligent environmental monitoring is critical for optimizing industrial operations and ensuring safety. This project presents an AI-based next-generation industrial weather monitoring system that integrates sensor technology, remote access, and cloud-based analytics. The system utilizes an Arduino UNO microcontroller as the central processing unit, interfaced with various sensors: DHT-11 for measuring temperature and humidity, BMP180 for barometric pressure and altitude, MQ-136 for detecting harmful air pollutants (hydrogen sulfide), and MQ-3 for sensing alcohol or gas presence in the atmosphere.

Sensor readings are displayed locally on an LCD for on-site monitoring. Additionally, the system uses an ESP8266 Wi-Fi module to transmit the data to the ThingSpeak IoT cloud platform, enabling remote access and real-time data visualization from any location. An LED indicator provides immediate visual alerts in case of abnormal conditions.

The cloud platform facilitates long-term data storage and is compatible with AI-based predictive analytics for forecasting environmental trends and detecting anomalies. This scalable and low-cost system is suitable for industrial environments where proactive environmental management is essential.

   

Objectives:  

  To monitor industrial environmental parameters such as temperature, humidity, pressure, and gas levels in real time.

  To detect harmful gases and unsafe atmospheric conditions using MQ-136 and MQ-3 sensors.

  To display sensor readings locally on an LCD for easy on-site monitoring.

  To transmit environmental data wirelessly using the ESP8266 Wi-Fi module.

  To store and visualize data on the ThingSpeak cloud platform for remote monitoring.

  To provide alert indications using LEDs during abnormal environmental conditions.

  To support AI-based analysis for predicting environmental changes and detecting anomalies.

  To develop a low-cost, scalable, and smart industrial weather monitoring system for Industry 4.0 applications.    

The major building blocks of this project are:  
  • ARDUINO UNO Microcontroller.
  • DHT-11
  • BMP-180.
  • MQ-136.
  • MQ-3.
  • LCD display.
  • ESP8266 WI-FI module.
  Software’s used:
  • Embedded C programming.
  • Arduino UNO for dumping code into Micro controller.
  • Express SCH for Circuit design.
  Regulated Power Supply:

         

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