Iot Based Indoor Air Pollution Monitoring Using Raspberry Pi

Also Available Domains IOT|Industrial Automation

Project Code :TEMBRE19_860

Abstract

This paper proposes an approach to monitor Air pollution parameter using the Raspberry-Pi. The system is designed using the python coding language. The monitored values can be accessed from the Internet of Things platform. The air pollution parameters are taken from the low cost gas sensors. The parameters include: concentrations of smoke, carbon monoxide and nitrogen-di-oxide, temperature and humidity. Also an alarm is triggered to indicate high concentrations of emissions. This acts as a warning to the authorities about the air pollution rate. A graph is plotted using the monitored values using Thing speak platform.

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

Block Diagram

Raspberry pi, DHT11, LM35, MQ7, Mics 2714, MQ2

Specifications

Raspberry pi, DHT 11 Humidity Sensor, LM 35 Temperature Sensor, MQ 7 Sensor, Mics 2714 NO2 Sensor, MQ 2 Sensor, Power Supply

Learning Outcomes

  • Raspberry pi pin diagram and architecture
  • How to install Raspberry pi IDE software
  • Setting up and installation procedure for Raspbian
  • Basic coding in Raspbian
  • Basic of python language
  • Working of DHT 11 SENSOR
  • How to interface MQ2 Sensor with Raspberry pi?
  • Working of LM32 Sensor
  • How to interface MQ7 Sensor with Raspberry pi?
  • About Project Development Life Cycle:
    • Planning and Requirement Gathering (software’s, Tools, Hardware components, etc.,)
    • Schematic preparation 
    • Code development and debugging
    • Hardware development and debugging
    • Development of the Project and Output testing
  • Practical exposure to:
    • Hardware and software tools.
    • Solution providing for real time problems.
    • Working with team/ individual.
    • Work on Creative ideas.
  • Project development Skills
    • Problem analyzing skills
    • Problem solving skills
    • Creativity and imaginary skills
    • Programming skills
    • Deployment
    • Testing skills
    • Debugging skills
    • Project presentation skills
    • Thesis writing skills

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