Save Lives With Data
How can we use data and technology to better the health of the Australian population, and what could be the economic impacts?
Go to Challenge | 35 teams have entered this challenge.
Team Name:
Team 200
Team Members:
Clean city
Project Info
Team Name
Team 200
Team Members
6 members with unpublished profiles.
Project Description
We are designing an app that combines spatial information about several sorts of waste management facilities in one easily accessible spot on your phone.
The app inlcudes the location of:
- publically accessible bins (green, recycling and landfill)
- publically accessible toilets
- bin collection days for your home address
- automatic calender reminders the night before bin collection of your home address
- drop off locations for the future SmartWaste system
future implementations:
- locations of recycling and green waste drop off location
- Bar code scanning of items to recieve information on what type waste it is. (Does it go into recycling, green waste or landfill)
- Accessing information on the producer and distributor of items and packaging by scanning the bar code of an item. This will allow investigation about where rubbish comes from.
Data Story
Open source sunshine coast council data was used for this project.
The following data sets were used:
- Public bin locations
- Public toilet loactions
- Bin collection days
- SmartWaste drop off locations
The datasets were downloaded and critical data extracted and saved as csv files. The csv files were layed over google maps. Our app links dirctly to this map including all information.
Team DataSets
Locations of publically accessible
Description of Use The raw dataset was exported in a .ArcGIS JSON file type. It was then converted to a .GeoJSON as raw data. The data was then input into QGIS as a layer. The layer was then exported as a .GeoJSON file. Then it was converted to a CSV file. The data was then cleaned. The clean CSV file was then overlayed on top of google mymaps.
Bin collection days by street
Description of Use The csv file of the data was downloaded and the required data was extracted and uploaded to a googlemap. This map is liked to our app so the data can be displayed in it.
SmartWaste Location Datasets
Description of Use The raw dataset was exported in a .ArcGIS JSON file type. It was then converted to a .GeoJSON as raw data. The data was then input into QGIS as a layer. We then exported the layer as a .GeoJSON file. Then it was converted to a CSV file. The data was then cleaned. The clean CSV file was then overlayed on top of google mymaps.
Locations of publically accessible toilets
Description of Use The raw data was downloaded to GPS for Google Earth. The data was saved as a google earth kml file and converted to a CSV file so it could be filtered. The filtered data was imported to google maps (my maps) and the URL for the map was linked to the app. The user of the app is linked to the created map and can search and obtain directions for public toilets in close proximity.
Challenge Entries
Litter Challenge
How might we prevent littering of fast food packaging?
Go to Challenge | 16 teams have entered this challenge.
Sunshine Coast Community
How can we raise the social capital of the Sunshine Coast?
Eligibility: Must use at least one Sunshine Coast region data set.
Go to Challenge | 14 teams have entered this challenge.
Sunshine Coast Sustainability
How can we preserve our great Sunshine Coast for the next generation?
Eligibility: Must use at least one Sunshine Coast region data set.
Go to Challenge | 12 teams have entered this challenge.
Healthy Communities Challenge
How might we assist councils to build healthier and stronger communities?
Go to Challenge | 49 teams have entered this challenge.