BREATHE:

AIR MONITORING

IoT PROJECT

Analysis by the British Heart Foundation (BHF) shows that London residents are breathing in toxins equivalent to 160 cigarettes a year. The effects of air pollution in the circulatory and pulmonary systems can be devastating, especially for young children.

 

While many of us avoid traffic-heavy areas when cycling and fear the outdoors; have we ever thought about how stagnated air indoors can affect our family?

This project studies the number of toxic air particles while also considering environmental factors like temperature and humidity. Sensors were placed both indoors and outdoors.

Electronics
Prototyping
Python
HTML
Google API
Healthcare
IoT Smart Home

 Pilar Zhang Qiu 

 

01 TIMELINE

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SENSOR DATA COLLECTION, STORAGE AND VISUALISATION
- Communication Protocols
- Data Collection Code
- Data Storage (Google API) 
- Data Visualisation
  (Web App Integration)
IDEATION, SYSTEM DESIGN AND HARDWARE
- Product Design and
  Planning
- Component Order
- Hardware Development:
  circuit design, soldering
  and testing
 

Main tasks: 

Technical skills

Ordering Components
Circuit Design
Project Planning

Design skills

Web App Design and Development
Soldering
Sensor Selection
Raspberry Pi
Python
HTML
CSS
Google API
 
 

02 SYSTEM & HARDWARE SET-UP

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The hardware set-up consists of a:

  • Raspberry Pi Model 3B+

  • Two temperature and humidity (DHT22) sensors

  • Two air particle (MQ-135) sensors

  • One ADS1115 analog-to-digital converter module

A set of DHT22 and MQ-135 was installed both inside and outside my bedroom.

 

The collected data is processed to calculate PPM (Particle per Million) values of hazardous air particles.

 

Data is then stored in a Google Sheet through an API. 

 

The website then reads the data from the spreadsheet and plots it automatically in graphs.

03 WEB APP - DATA VISUALISATION

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A web app was created to present the collected air quality (PPM), temperature and humidity data in simplified graphs. This can be accessed by selecting a specific date range or by choosing the live data feed.


This web app was hosted for local networks by using the Apache software in the Raspberry Pi.

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04 TECHNICAL REPORT - PDF