Back to Projects

Team Name:

Pinecone


Team Members:


Evidence of Work

AutoMate

Project Info

Pinecone thumbnail

Team Name


Pinecone


Team Members


Travis , Jesse , Shannon Roberts , Floyd and 3 other members with unpublished profiles.

Project Description


Team Members

Floyd Watson (Team Captain)
Simon Dolley
Shannon Roberts
Kassian Houben
Keez Eden
Jesse Gray
Travis Falkenberg

Award Categories Entered

Public Transport for the Future
Reducing CBD Traffic Congestion
Combating the Climate Emergency

Problem
Traffic congestion is increasing
People are under utilizing space in their vehicles
Underutilized public transport
Underutilized cycle lanes

Solution
Create an application that allows users to better utilize the current infrastructure.
This will be obtained through a system designed to increase car pooling and inform people about other available forms of transportation. The application consists of a car pooling "request ride" and "provide ride" section which handles the transactional part, and a public transport section. Both are displayed on a map with which the user can interact. The app also keeps track of the users carbon footprint, and the benefits of having used the app.
The future of the app includes providing a broader range of public transport methods including bike tracks and walking paths.


Data Story


The data our team has used in the creation of this project comes from the Auckland transport API. The data comes in a JSON format including the status of the request and any errors that occurred. A major issue while working with this API was figuring it out how to extract what we needed from the JSON format, as we had decided not to store the whole dataset on a local database. In the functional prototype (shown in the video) we are pulling in any data we need directly from the API by querying it with relevant parameters such as the users location (longitude and latitude) and which bus/train stops should appear on the map (calculated by the distance away from the user). A further use case planned for the dataset is to create routes between location and destination, based on different methods of transportation (eg: car sharing, public transport).


Evidence of Work

Video

Project Image

Team DataSets

Auckland Transport API

Description of Use We are utilising the latitude and longitude positioning of current public transport pick up areas, this data will be overlay-ed onto a mapping system allowing users to see nearby available options of travel. Each node will have a useful set of information attached allowing users to see pick up/ drop off times, prices, end of service and a rating that other users can attach to each service.

Data Set

Challenge Entries

Innovate New Zealand

Best innovative hack using Stats NZ data

Go to Challenge | 16 teams have entered this challenge.

Reducing CBD Traffic Congestion

How to reduce traffic congestion or parking problems in CBD?

Go to Challenge | 39 teams have entered this challenge.

Public Transport for the Future

How might we combine data with modern technologies - such as AI/ML, IoT, Analytics or Natural Language interfaces - to better our public transport services. Outcomes could take the form of new commuter experiences, reduced environmental impact, or helping plan for the future.

Go to Challenge | 45 teams have entered this challenge.

Combating the Climate Emergency

Best hack to combat the climate emergency.

Go to Challenge | 6 teams have entered this challenge.