go-plotly

go-plotly

go-plotly is a simple, free to use plotting microservice. Connect to go-plotly with a gRPC connection and plot graphs in real time. I made this service in response to the lack of anything offering similar functionality, particularly for Go, at the time of writing.

Summary

go-plotly is built on top of plot.ly and offers similar functionalities to it’s API, without their restrictions. go-plotly uses a combination of gRPC and websocket technology to create an easy to use, reliable microservice that delivers near instantaneous transmission of data between a client and a graph and overcomes the 50ms throttle imposed by plot.ly.

Plus, did I mention that it is COMPLETELY free? For usage details, please refer to the documentation. Here’s an example client written in Go.

GovHack 2017

Participated in GovHack 2017

Bin Wasting Space

binwasting.space is a small utility application that sends text messages to remind you when your trash days are depending on your locality.

The Pitch

Have you been bin wasting your trash space? Have you been forgetting which week recycling is?

With data from the Hobart City Council and the Launceston City Council, we have created a small utility application that would allow you to subscribe to a text messaging service that reminds you when the bin days, recycling days, and green waste days are.

To make it more accessible, the simple signup process only requires your name, phone number and address. Our application creates a set of polygons which maps the different geographical regions to their respective collection days based on type. We will then dereference your address into a set of coordinates and identify which region to subscribe you to.

The application will send out text messages to remind you which bins to take out when.

With this application, we aim to reduce the amount of recycling that would otherwise go into landfills because of missed recycling days.

Datasets Used

GovHack 2017

GovHack is an open data hackathon, run annually by volunteers, focussed on unlocking the value in open data published by government. It has been run by a team of volunteers and grown from a small data mashup event to an international competition that brings over 3000 people together to innovate, collaborate and apply their creative skills to open government data. GovHack is for coders, designers, story tellers, activists, analysts, journalists and anyone that wants to tap into the vast amount of information made available by governments.

GovHack celebrates technical and creative capacity, opens the door to collaboration with governments, and has helped to advance the cause of open data to drive social and economic value. Learn more about GovHack here.

Non-defunct resources

uHack 2016

Awarded 1st runner-up (Open Division) for Shop Smart

Shop Smart

Shop Smart is a shopping list app that compares Coles & Woolworths prices & gives advice on where to shop to save the most money!

The Pitch

Using a social enterprise model, we’re creating a shopping list app, which will not only save people money while helping them buy healthier food, but will also collect data about their shopping habits, which, when linked with their postcode and household income, will hopefully allow researchers to better understand some of the correlations between eating habits and health outcomes.

We appreciate that one of the big issues with data collection is getting people to regularly and reliability fill in whatever form/survey you’re looking for them to complete - the recent Census is a perfect example of that! What we’re hoping to create is a product that gives users a very clear ‘What’s in it for Me’ by providing an easy to use, intuitive shopping app that can be accessed by the whole family or business, which lets them know how much they can save each time they complete a shopping list, providing a running tally of the amount they’ve saved to date using the app, tracking specials, telling them when they should or shouldn’t buy specific products based on their price history, and offering them tailored sale advice, based on their buying habits.

If we do this properly, by providing users with a free, accessible, intuitive and easy to use app that genuinely saves them money and makes their lives easier, we hope that people will be more likely to use the app regularly enough to provide real, usable data that can then be passed on to UTas and other appropriate research bodies to help inform health research.

We plan to start simple and small, only releasing the app on Android initially, only including products from the two big supermarket chains (Coles and Woolworths), and only providing a fairly limited set of core functionalities in the first instance, including taking a list of products from the user, and returning advice re how much they would save if they chose to shop at Coles or Woolworths, or if they were prepared to split their shop between the two stores. It would tell them how much they’ve saved to date using the app, and show a shopping history. It would track items they wanted to ‘watch’, to see when they came on sale, and would offer advice on when and where they should buy certain items on their list, e.g. we all know that you should never buy Vitamin tablets at full price, as they go for 50% off regularly! Basically, we aim to help people shop the bargains more often than not! As an added benefit, we hope that by saving money on their grocery budget, people will have more ‘disposable’ money to spend on perceived ‘expensive’, healthier foods, including fresh fruit and veggies. We hope that the app may also help to break down some of the, often false, perceptions that eating healthy is more expensive.

Looking to the future, we would plan to expand the functionalities to include other shops beyond ‘the big two’, e.g. IGAs and other smaller supermarkets and local producers. We would make the specials more tailored, integrate suggested recipes based on people’s product history, and continue to improve the machine learning element of the project. We would push the app onto IOS, as well as launch a web platform. Once we started to get some credibility and traction with users we may also look at asking some extra questions, like whether you got the flu this winter, and how often you eat out or buy take away food, to try and further increase the value of the data being collected.

In a nutshell, our goal is to create a product that not only improves people’s health, and helps them make ends meet, but also, potentially, will help to inform health research into the future.

UHack Research Themes

  • Better Health: This project aims to collect authentic, real-world data on what food people are buying, linked with their annual household income, number of household members and location. Data on what people eat is famously hard to collect, and though this project doesn’t provide information on exactly what individuals are eating, it does provide a different set of data, connecting location, income and food in potentially previously unexplored ways. We anticipate that this data could be used to further research particularly in the areas of policy and prevention.
  • Data, Knowledge & Decisions: Not only are we collecting data in new and innovative ways, but we hope that the research conducted using this data may inform evidence-based policy in the health area into the future.

uHack 2016

UHack is Tasmania’s innovation hackathon competition - run for student and public innovators - by students and staff from the University of Tasmania. Learn more about uHack here.

Final Year Project

Fly Stay Play

Fly Stay Play is a web application that acquires travel related data from multiple service providers and automatically generates heuristically optimized travel itineraries based on user preferences.

The Pitch

Fly Stay Play is a proof of concept web application pitched by Dr. James Montgomery and Dr. Saurabh Garg, with the aim to bring together different travel and event application programming interfaces (API) to create complete travel plans. The user is able to input a variety of preferences to customize the travel plans to their individual needs.

Once these constraints are entered, Fly Stay Play will generate a series of travel plans for the user, which they will be able to edit so the system can further improve the plans to suit the user. The user can then save and book their travel plans, with the ability to edit the plans later, even during the trip.

The Software

The backbone of the application is built on top of data acquired from numerous service providers including Eventful, Expedia, Factual, Google’s QPX Express and Maps. This allows Fly Stay Play to heuristically optimize travel itineraries based on the users’ hotel, flight, event, budget and transport preferences. The heuristic optimization engine is a proprietary swap-based set-optimization algorithm developed specifically to for this application.

For Fly Stay Play to create travel plans, the user must enter a set of dates, an origin and a destination. The application will then have the minimum amount of data required to generate an itinerary based on those constraints. Users then have the option to input additional constraints, including budget, flight preferences, transport preferences and upcoming events located near the destination.

When Fly Stay Play returns its travel plans, users will be able to view and edit any itinerary they like. They will have the ability to “lock” down any events, activities, flight and hotels they like and reject the ones that they do not. From there, the user can then have the system regenerate a new set of itineraries based on the latest constraints.

Extensibility

Fly Stay Play has been constructed to be modular and scalable. As such, as many or as little new modules can be added and deleted as is needed. This means that the system has been built to be highly extensible for future development. More services can be integrated to get more data sources for the system to consume in the optimization process.

Also, due to the modularity of the system, the proprietary heuristic optimization engine can help with decisions beyond travel in the future and possibly allow for the system to make decisions in completely removed paradigms, such as finance, education, and so on.

Non-defunct resources