This abstract has been accepted at the 2024 DHIS2 Annual Conference
Boosting sustainability and profit: The data-driven future of carbon farming
Agrovar, a start up based in Sofia Bulgaria, has developed a software platform that integrates deep tech neural network and machine learning to support important carbon capture and credit initiatives. Agrovar is already supporting over 20 farm companies with plans for expansion with the following: (1) the software supports field mapping and sampling (2) through tracking adoption of regenerative practices and soil samples before and after, data gathered supports farm enrollment in carbon programs (selling credits) and (3) the software suggests carbon crops and conservation practices (regenerative agriculture) for adoption based on unique characteristics of land and conditions. This project introduces a data repository system (DHIS2) designed to accelerate the shift towards sustainable agriculture for farmers. By facilitating the transition and enhancing climate change resilience, the project offers a win-win for both farmers and the environment. The core of the project is a data and metadata repository that integrates field and lab analyses. The project goes beyond data management by incorporating rigorous standards for carbon credit generation. This transparency allows international auditors easy access to crucial information, incentivizing sustainable practices through financial rewards. Ultimately, acting as a catalyst for a more sustainable future for agriculture. Farmers gain access to data-driven decision-making tools, climate resilience, and carbon credit generation opportunities, paving the way for positive environmental impact.
Primary Author: Kristiyan Panayotov
Keywords:
Sustainable Agriculture, Data Repository, Machine Learning, Environment & Climate
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