Description:

With the recent weather events in Auckland, and many other recent disasters around the world, there has lacked a central online place where those affected can go to find out specific, up-to-date information (for example, a map of flooding-affected areas and road closures). This information exists online but is often in a variety of formats and in multiple locations.

In this project, you will investigate the use of modern data gathering and analysis techniques to automatically (as much as possible) curate and summarize important information related to disasters. The ideal end goal will be a prototype app or website where users can go to be presented with the most relevant, up-to-date information based on their location.

We already have a prototype of such an app from a previous part-4 project. This project will focus on applying more techniques, such as machine learning and data mining, to provide the prototype app with more accurate / useful news information.

Type:

Undergraduate

Outcome:

The research outcomes of the project are as follows:

1. A literature review into techniques for gathering and analyzing information from disparate online sources;
2. Analysis of one or more algorithms / techniques for such data gathering & analysis;
3. Incorporation of at least one such algorithm / technique into an existing prototype app

 

Prerequisites

None

Specialisations

• Software Engineering

Categories

• AI & Machine learning
• Smart Phone & Tablet Applications

Supervisor

• Andrew Meads

Co-supervisor

• David Huang

Team

• Grant Liu
• Wen Jie See

Lab

Computer Science (303S.499, Lab)