Digital Regenerative Farming

Project Info

Team 1Six1Six thumbnail

Team Members


Nicolas , Daryl , Isabella Mandic , Adam , Tys

Project Description


Making farms more productive and sustainable by quantifying soil carbon with digital farmhands


#agribusiness #iot #field robots #carbon emissions #soil erosion #soil sequestration #soil organic carbon #circular economy

Data Story


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.


Evidence of Work

Video

Team DataSets

Open Datasets - Land Information New Zealand (LINZ)

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).

Data Set

CSIRO Australian Soil Resource Information System

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).

Data Set

Soil and land information - mapped by eSPADE

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).

Data Set

United Nations Global Soil Organic Carbon Database

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.

Data Set

Challenge Entries

Hack for a Circular Economy

In order to build a more sustainable community, how might we redesign, rethink, repair and repurpose spaces, places, materials, and digital infrastructure, systems and policies within cities in order to progress social, natural and economic development?

Eligibility: Must use at least one open dataset.

Go to Challenge | 14 teams have entered this challenge.

The digital future of agriculture

How might we use data and digital technology to make agriculture more sustainable, more ethical, and more efficient?

Eligibility: Must use at least one open dataset.

Go to Challenge | 16 teams have entered this challenge.

IoT insights for better regional agribusiness at scale

How might we harness open data and IoT insights in near-real-time to enable local agribusiness and farms in our regions be more productive and sustainable at scale? How can we share private IoT data and regional open data for an overall more productive and sustainable agribusiness?

Go to Challenge | 13 teams have entered this challenge.