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HVS-3546. IOT based real-time Air quality monitoring and prediction system using random forest and decision
HVS-3546. IOT based real-time Air quality monitoring and prediction system using random forest and decision
HVS-3546. IOT based real-time Air quality monitoring and prediction system using random forest and decision
HVS-3546. IOT based real-time Air quality monitoring and prediction system using random forest and decision
HVS-3546. IOT based real-time Air quality monitoring and prediction system using random forest and decision

HVS-3546. IOT based real-time Air quality monitoring and prediction system using random forest and decision

₹14,500.00

The project aims at designing real time environment monitoring and prediction system. So, an Internet of Things and algorithms-based monitoring system is being proposed here, using Raspberry pi microcontroller based embedded system, where each sensor gives different parameters which are used to monitor the condition of environment using two different algorithm and finally able to say which algorithm gives us more accurate result between them

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The project aims at designing real time environment monitoring and prediction system. So, an Internet of Things and algorithms-based monitoring system is being proposed here, using Raspberry pi microcontroller based embedded system, where each sensor gives different parameters which are used to monitor the condition of environment using two different algorithm and finally able to say which algorithm gives us more accurate result between them.   Urbanization promises a very high standard of life at the expense of deterioration in the environment and air quality. The extensive use of fossil-fuel-powered cars and machines everywhere releases a massive number of harmful gases and particulate matter into our air. Air is a crucial component of life on Earth for every being: a plant, an animal, or a human alike. Air pollution undermines the wellbeing and development of those living creatures directly. Lately, because of that rapid urbanization, air quality is declining quickly.   Initially, the sensors DHT11, MQ-7 and MQ-135 are used to get humidity, temperature, C02 and air quality values. DHT 11 is interfaced to raspberry pi directly as it gives digital values which could be read by Raspberry Pi ZERO 2W. MQ7 and MQ135 are interfaced to a nano board which converts analog values to digital values and then to serial values which could be read by raspberry pi. Raspberry Pi 3 processes the data and then displays that data on to the ThingSpeak using Wi-Fi module ESP8266. The same is displayed on LCD. There are also 2 switches to select which algorithm we prefer between Random Forest and Decision Tree algorithms.  

The features of the project are:
  1. Development of air quality monitoring system.
  2. Implementation of Random Forest and decision tree algorithm.
  3. Using IOT technology.
  4. Using Raspberry pi to achieve this task.
  The Major building blocks of this project are:
  1. Regulated Power Supply.
  2. Raspberry Pi ZERO 2W.
  3. DHT11 Sensor.
  4. MQ-7 Sensor.
  5. LCD display.
  6. MQ-135 Sensor.
  7. ESP 8266.
  8. Nano Board.
  Software’s used:  
  1. Embedded Linux programming.
  2. Express SCH for Circuit design.
             

Regulated Power Supply:    

                     

Block Diagram:  

video:

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