Gov Hack 2020 Raw Onion

Theme: Plan your way to vote – how can we assist voters to identify ways of voting that are convenient for them and match their circumstances?

I recently spent my weekend with govHack. See project video, description below and github repo for details. It was a tiring two day sprint, but a pleasurable (and learning) experience to work with awesome people remotely! Use lots of react.js, Google maps API, some GeoJson, tied together by AWS Amplify. Shout out to my teammates, to the devs whom I spent a lot of time working in parallel, Mahesh, Chilumba, Sachi, and the story teller side Brett (also the leader), Navida, Liana, and Malgosia.

Voting can be a hassle. However, it does not need to be. As of 2020, 16.6 million Australians are enrolled to vote, which shows just how important it is to make voting easier. Our team's mission is to make voting as easy as it can be. We will deliver this effect through an integrated app & web-based platform to match voters with their voting type intent, preferred/available date and time, accessible voting location/s. We will also provided voice access via AWS Lex (e.g., mobile call) to our system for users who prefer dial in access. To address the recent public health situation related to COVID, we will also help ensure physical distancing are heeded by promptly informing the voters of where the COVID hotspots are and about proper voting hygiene practices. Additionally, our solution will incorporate pre-voting and on-the-day functionality with realtime monitoring (i.e. length of time to vote, length of time to purchase a democracy sausage) via AEC/WAEC/Lions Club, staff information inputs, and/or video-based hardware/software solution. This solution has application beyond Australia's shores and the US elections are one major potential target (aside from State-based hackers). There is potential to incorporate blockchain for genuine early voters and other functionality.

Luke Sy
PhD Candidate

My research interests include state estimation, robotics, wearable sensors, machine learning, and biomedical engineering.