Team 1Six1Six
Making farms more productive and sustainable by quantifying soil carbon with digital farmhands
Our solution combines onsite collected soil organic carbon readings with farm operations information from autonomous robots and the farm’s own management software data stores (such as Apunga). In order to inform farmers on carbon as a tonnage per hectare sequestered, this will then be streamed to an Azure cloud environment through Telstra NB-IoT Infrastructure, where it will be combined with data vectors retrieved from Government data sources.
In addition, we will train an ML model on the large United Nations Global Soil Organic Carbon Database to advise farmers on changes to the farms’ operations that would deliver better carbon sequestration results. Our solution will produce a report and advice for farmers to measure, forecast, and monetise soil carbon outcomes from regenerative farming practices.
IoT insights for better regional agribusiness at scale:
Rewarding farmers with carbon credits for regenerative farming makes farms more sustainable and financially productive. Our solution uses LPWAN and NB-IoT networks for autonomous field vehicles to transmit carbon data and created accurate analysis of soil organic carbon improvements on farms.
The digital future of agriculture:
Rewarding farmers with carbon credits for regenerative farming makes farms more sustainable and financially efficient. Our solution combines field robotics with Microsoft Azure cloud platforms to farmers to measure, forecast, and monetise soil carbon outcomes from regenerative farming practices.
Hack for a Circular Economy:
Regenerative farming techniques help farms store more carbon in the land, prevents wasteful soil erosion, improves the groundwater, and reduces pesticide requirements. Our solution incentivises regenerative farming by addressing practical pain points involving farmers being rewarded with carbon credits for their improved practices.
Description of Use This dataset is needed to convert CO2 Soil Organic Carbon measurements into carbon capture per hectare in NZ. Whenever a soil sample is taken, we will receive GPS coordinates that can be matched to S-Map map, which gives us soil composition attributes (i.e. soil bulk density).
Description of Use This dataset is needed to convert CO2 SOC measurements into carbon capture per hectare at the national-level. Whenever a soil sample is taken, we will receive GPS coordinates that can be matched to Australian Soil Resource Information System (ASRIS), which gives us soil composition attributes (i.e. soil bulk density).
Description of Use This dataset is needed to convert CO2 SOC measurements into carbon capture per hectare at the NSW state-level. Whenever a soil sample is taken, we will receive GPS coordinates that can be matched to eSPADE’s map, which gives us soil composition attributes (i.e. soil bulk density).
Description of Use This dataset will act as a training set for a ML model that would be able to advise farmers how changes in farming practice would lead to higher carbon capture.
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