80 ANU students. 30 college students. 24 hours. One ANU Innovation Challenge!

80 ANU students. 30 college students. 24 hours. One ANU Innovation Challenge!
80 ANU students. 30 college students. 24 hours. One ANU Innovation Challenge!

On Friday 16 and Saturday 17 September, ANU students, college students and ANU academics formed teams, working together to find solutions to problems within the humanitarian, health and data analysis fields.

Teams presented an innovation which addressed their selected problem at the end of the Challenge.

Year 12 students Harman, Georgia and Maddy from Merici College in Canberra took time out from their busy study schedule to participate.

“I want to study engineering next year, so I though the Innovation Challenge could give me an idea of what it might be like” said Harman.

“It seemed like a fun and interesting idea, something that I wanted to give a go.”

The team – Merici Gals – chose to undertake the humanitarian challenge. In this challenge, students were required to find a way to source clean, drinkable water without electricity. The girls’ innovation was a water filter.

“This was not like anything you do at school; I enjoyed problem solving to tackle this challenge,” said Harman.

The Challenge also allowed the girls to form networks with other ANU students and academics.

“Aside from working on the Challenge, it was good to meet people studying or working in the field to get their perspectives, and it was an opportunity to learn from academics and students,” said Georgia.

Participating in the challenge has cemented their vision to study engineering, to solve problems that affect people.

“Once I finish year 12, I want to study engineering, in particular humanitarian engineering. I’d love to participate in Engineers Without Borders” said Maddy.

The winning team from the university division, Chaminnovation, combined their backgrounds studying advanced computing, science, mathematics and engineering to tackle the Big Data Challenge.

“The aim of the challenge was to tackle the issue of making large datasets (either numbers, pictures or words) more understandable and readily communicable. We chose to make use of a dataset comprised of words. We developed a program which could analyse the text of a book and return a few key metrics” said Logan, the team leader.

The team tested the program they developed on 3,000 books available on the online database Project Gutenberg, and the results were uploaded into a fully interactive website.

Key metrics the program could display included the length of the book, the number of words, the most frequently occurring words, an approximate reading level.

“Most excitingly, the program returned what we called the ‘semantic index’ of the book. This program took every sentence of the book and was able to determine whether the sentence had positive or negative connotations. The program returned a value between -1 and 1 to tell us whether the book was overall positive, negative or neutral.”

The group were surprised by the range of solutions that each team presented for challenges; each team thought about the problem in a completely different way.

“As a team, we had plenty of good ideas and our combined coding skills to get a working prototype for the project done in less than 24 hours was absolutely amazing. Hopefully some of the computer science students within our group might have an opportunity to build on this idea in the later years of their degree.”

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