Projects / Local Chapter Project

Supplement Disaster Detection using Social Media

Start Date: October 24, 2022 | 4 years ago


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Challenge Background

Australia has gone through several Disaster events in recent years , The floods in July 2022 Australia are some of the worst the country has ever experienced and have caused widespread devastation.. These are the same communities where we saw massive bushfires in 2019 and 2020 which resulted in the loss of shrubs and trees setting the scene for extreme flooding. Tens of thousands of Australians have had to evacuate their homes after devastating floods struck the eastern part of the country, resulting in several millions of dollars in damage

Experts say climate change is fuelling an increase in extreme weather across Australia, threatening to make bushfires, floods and droughts more common.

A report published last month by the United Nations Environment Programme (UNEP) and GRID Arendal predicts that wildfires will become more frequent and intense, with a global increase of extreme fires by 50 per cent by the end of the century. The increase in wildfires renders land barren, which leads to increased run-off and, therefore, floods and, later, drought.

AI and Machine Learning can play crucial roles in the forecast and monitor and manage these disaster events. While several technologies and mechanisms is already in place , one area that can significantly supplement and improve the efficiency of these managing these disaster events is leveraging Social media

Project Timeline

1

Collection of Dataset (Tweets, Images, Public Data sets related to Disaster events)

2

Collection of Dataset (Tweets, Images, Public Data sets related to Disaster events)

3

Data Pre processing

4

Data Preprocesisng

5

Model Building

6

Model Validation & Fine tuning

7

Reporting and final Packaging

8

Wrapup

What you'll learn

NLP Processing and Segmentation, Twitter Text Extraction, Classification Models, Reporting

First Omdena Local Chapter Project?

Beginner-friendly, but also welcomes experts

Education-focused

Duration: 4 to 8 weeks

Open-source



Your Benefits

Address a significant real-world problem with your skills

Build your project portfolio

Access paid projects (as an Omdena Top Talent)

Get hired at top organizations



Requirements

Good English

Suitable for AI/ Data Science beginners but also more senior collaborators

Learning mindset



Application Form

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