From cb1b4bf9aa894f503fa925e7fe404b93c341dea0 Mon Sep 17 00:00:00 2001 From: Rafsan Al Mamun Date: Fri, 1 Nov 2024 22:17:15 +1100 Subject: [PATCH] Update README.md --- README.md | 26 ++++++++++++++++++-------- 1 file changed, 18 insertions(+), 8 deletions(-) diff --git a/README.md b/README.md index 02d94ec..de39864 100644 --- a/README.md +++ b/README.md @@ -1,12 +1,9 @@ - FOR COMP90024 ASSIGNMENT 2 - BY TEAM 45: - William Chen 1400081 - Petr Andreev 1375858 - Rafsan Al Mamun 1407776 - Ojaswi Dheer 1447227 +# Analysing the Relationship Between Air Quality and Lung Disorder in Australia -# COMP90024_Assignment-2 -This repo contains the assignment 2 files for COMP90024: Cluster and Cloud Programming at the University of Melbourne. +## Project Overview +This project demonstrates the use of cloud computing for data analysis, focusing on understanding critical aspects of life in Australia. Specifically, it explores the relationships between air quality and lung-related disorders, and the influence of weather patterns on mental health. Built on a robust cloud stack, this project leverages a scalable and event-driven architecture to ingest, process, and analyze large datasets related to health, weather, and public sentiment. + +**[YouTube Video Overview](https://youtu.be/fhftcsxGKWA)** ## Admins William Chen wilchen2@student.unimelb.edu.au @@ -14,6 +11,19 @@ This repo contains the assignment 2 files for COMP90024: Cluster and Cloud Progr Rafsan Al Mamun ralmamun@student.unimelb.edu.au Ojaswi Dheer ojaswi.dheer@student.unimelb.edu.au +## Key Features +- **Cloud Infrastructure**: Hosted on the Melbourne Research Cloud, utilizing OpenStack and Kubernetes to manage efficient data processing and resource allocation. +- **Data Processing and Storage**: Serverless functions managed by Fission for event-based data processing, with ElasticSearch providing large-scale data storage and quick data retrieval. +- **Scenarios Analyzed**: + - **Air Quality and Lung Disorders**: Analyzes correlations between PM2.5 levels and lung disease rates, offering insights for policymakers and public health. + - **Weather and Mood**: Examines potential links between weather patterns and public mood by analyzing weather data alongside social media sentiment. +- **Interactive Analytics**: Jupyter Notebooks are used as the front-end interface, offering interactive data exploration, visualization, and in-depth analysis. + +## Technology Stack +- **Kubernetes & Fission**: Orchestrates and deploys serverless functions, enabling an event-driven architecture. +- **ElasticSearch**: Indexes and stores large volumes of data for efficient querying and real-time analytics. +- **Jupyter Notebooks**: Allows for interactive data analysis and visualization, ideal for presenting insights and engaging stakeholders. + ## Setup ### Installation - As with the assignment class repository, you should install the below: