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Commit d3ba16d5 authored by Yechen Deng's avatar Yechen Deng
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Update README.md

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This project leverages cloud computing to develop an in-depth correlation study of urban transportation in Victoria, focusing on five key scenarios: pedestrian distribution, regional population density, usage per station, traffic congestion, and social media activity. The project utilizes the Melbourne Research Cloud (MRC) and integrates various technologies and tools to collect, process, analyze, and visualize data.
## Software Stack Installation and Required Pre-configuration
The detailed pre-requirements, client configuration, Kubernetes architecture design, and deplyments of Fission, ElasticSearch, Kibana, Kafka can be referred to the linke below:
The detailed pre-requirements, client configuration, Kubernetes architecture design, and deplyments of Fission, ElasticSearch, Kibana, Kafka, and other usage can be referred to the linke below:
https://gitlab.unimelb.edu.au/feit-comp90024/comp90024/-/tree/master
Detialed list of functions and triggers can be found in the Appendix in the report under the folder Docs.
## Technology Stack
1. Back-end: Kubernetes, Helm, Fission, Elasticsearch, Kafka
2. Front-end: Jupyter Notebook, Folium, Seaborn, Matplotlib, ipywidgets
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