Real-Time AQI App using MATLAB and Raspberry Pi

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Valutazione

Difficoltà
5/5
Tempo stimato
Più di una settimana
Idoneità per principianti
12/100
Tipo di issue
Funzionalità
Chiarezza
Da chiarire
Stato di attività
Tranquilla
Stack tecnologico
matlab, raspberry-pi
Ambito
cloud, data, embedded-iot

Direzione di ricerca

The issue links to the project repository and a presentation, but does not identify files, tests, or a specific change to make. Start by reviewing the linked repository and presentation to understand the project; the issue does not define a completion criterion.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Descrizione

Dear Professors,

I would like to share our project developed using MATLAB, Raspberry Pi, and a Nova PM Sensor as part of our academic and practical learning activities in IoT, environmental monitoring, and real-time data analytics.

GitHub Repository:
https://github.com/vedantjoliya/AQI

Project Overview

AQI-Real-Time-App.pptx

The primary objective of this project was to design and implement an IoT-based environmental monitoring system capable of continuously measuring and analyzing air quality parameters in real time. The system acquires PM2.5 and PM10 particulate matter data using a Nova particulate matter sensor connected to a Raspberry Pi, while MATLAB is used for data acquisition, processing, visualization, and cloud integration.

The project demonstrates the integration of embedded hardware systems with software-based analytical tools to create a real-time AQI monitoring platform.

Implemented Features

Real-time PM2.5 and PM10 monitoring
AQI calculation and visualization
Raspberry Pi serial communication with sensor hardware
MATLAB-based live dashboard and graphical plotting
Automated Google Sheets cloud logging using Google Apps Script APIs
Continuous real-time environmental data acquisition
Error handling for stable monitoring operation

Technologies Used

MATLAB
Raspberry Pi
Nova PM Sensor
IoT Communication
Google Apps Script
Google Sheets API
Serial Communication Protocols
Learning Outcomes

Through this project, we gained practical experience in:

IoT system development
Embedded sensor integration
Real-time data processing
MATLAB programming and visualization
Cloud-based data logging systems
Hardware-software communication
Environmental analytics and monitoring systems

This project also helped us better understand how intelligent monitoring systems can contribute to smart environmental solutions and real-time analytics applications.

Teammates:
TAUSIF AHMED
DHRUV DANGI
PRIYANSHU VISHNOI

We sincerely thank @MarcoRianiUNIPR, @Asadunipr , @GianlucaMorelliUNIPR, and @AldoCorbelliniUNIPR for their valuable guidance, continuous support, and for providing us the opportunity to present and work on this project.

Thank you.

Lingua principale
MATLAB
Stelle
30
Fork
1
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Preparare l'ambiente

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Come iniziare

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  2. Commenta sulla issue per dire che te ne occupi tu — evita che due persone facciano lo stesso lavoro.
  3. Fai un fork del repository e lavora su un branch.
  4. Apri una pull request che faccia riferimento al numero della issue.

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