Team Name:
11one1!
Team Members:
11one1!
The ‘Unity Water Mid Field Monitoring Program Water Quality’ and ‘Ecosystem Health Monitoring Program - Water Quality’ (EHMP) datasets were used to create an app called RiverMate for recreational Pine River fishers. The temperature, turbidity, pH, nitrate and oxygen fields were taken from these data sets and used in a cluster method using AI machine learning. This was done to broadly identify good, okay, and poor Pine River conditions for recreational users.
RiverMate gives local fishers a place to check the river conditions but also to chat and post stories regarding their experiences on the river. For example, users can post the dimensions and species of their catch to the platform, and the best catch of the month is presented on the homepage to all users.
Whilst RiverMate is a useful hub for local fishers, it also aims to enhance the existing datasets from Unity Water. Users can report fish size and species. Additionally, RiverMate contains an option to share boat sounder data with the app, recording temperature, pH levels and more. Unity Water currently gathers data bi-monthly from the river, so RiverMate provides a timelier and community driven means of data collection.
In the future RiverMate could be expanded to more rivers and provide detail for more communities, providing engagement and better data for more river systems.
Description of Use We used table 6. Page 33 to determine cut off points for displaying water health from the perspective of acceptability for good fish health.
Description of Use Unfortunately we didn't get any working code within the competition time.
Description of Use We subset and cleaned the data for our project but unfortunately didn't get any working code within the competition time.
Go to Challenge | 9 teams have entered this challenge.
