Optimise energy and water resource planning
Optimise energy and water resource planning
Go to Challenge | 32 teams have entered this challenge.
Team Name:
ARIVS
Team Members:
NextCrops
Project Info
Team Name
ARIVS
Team Members
Jack and 1 other member with an unpublished profile.
Project Description
Next Crops is a cloud based native Android app developed by team ARVIS. It helps farmers in Australia to make big decision on the next generation crops to grow on their farm land. We have crafted a cloud application that untilise a bunch of data sets such as Agriculture Victoria Soils API, Irrigation system allocations, SALI soil chemistry API, SALI land suitability API and Annual rainfall, SILO climate API. Infused with Google Vision AI, machine learning model, our solution is able to give farmers the knowledge to better understand the soil of their land, what to grow to achieve the balance among ecological environment, water usage and land sustainability. The AI algorithm used to judge the growing crops are that if the corps are suitable for growing on the soil composition, the impact on the soil of the fertiliser used on the crops, the average water quantity required, if there is any irrigation system available or just use the rain fall.
Team DataSets
SILO climate API
Description of Use The climate data helps to decide which crops to grow in certain land areas
SALI soil chemistry API
Description of Use The soil chemistry data helps to select the crops to grow on the land
SALI land suitability API
Description of Use The land suitability data helps to decide if crops are suitable to grow on the land
Irrigation system allocations
Description of Use The irrigation system allocations data helps to decide the crops to grow on the land where irrigation systems are around.
Groundwater and surface water monitoring Queensland web map service
Description of Use The location based groundwater and surface water data is feed into our machine learning as one of the judging criteria to help select crops that require water
Water monitoring network - surface water quantity - Queensland
Description of Use The surface water quantity data is feed into our machine learning as one of the judging criteria to help select crops that require water
SoE2017: Annual rainfall
Description of Use The annual rainfall data is feed into our machine learning as one of the judging criteria to help select crops that require water
Agriculture Victoria Soils API
Description of Use The location based soil data is used to help the farmer to choose the best crops to grow on their farm land.
Challenge Entries
Waterwise
How can we protect and preserve our water resources?
Go to Challenge | 22 teams have entered this challenge.
Innovative ways to be efficient with water
Innovative ideas about water efficiency. Climate change means that we will have more unpredictable weather. Some of Australia is in drought and some areas have plenty of water. That changes each year. Water efficiency was a focus around the millennium drought. We want new, innovative and untapped ideas on ways to be efficient with water use. These ideas could include how we use water, how we can save water, how we waste water, how everyone can make a difference in using water wisely, water rules and ideas on saving water for the future.
Go to Challenge | 26 teams have entered this challenge.
🌟 Small Business; Big Decisions
Where you choose to open a business plays a big role in whether you succeed or fail in small business. Many business owners make these decisions based on gut-feel or by doing extensive desk-research. How might open data help small business make better decisions?
Go to Challenge | 13 teams have entered this challenge.
Queensland OpenAPI
Create a project using one or more of Queensland's Open-API’s
Go to Challenge | 39 teams have entered this challenge.
🌟 Visualising the soil quality of Victoria
Agriculture Victoria have years of meticulously collected soil quality information. This wealth of data is an incredibly rich resource for farmers, industry and researchers who make decisions based on what’s on, or under, the ground. This might include ecological planning, bushfire mapping or deciding on next generation crops. How would you represent this data to help decision makers?
Go to Challenge | 5 teams have entered this challenge.