The need for streamlining precision agriculture data in Africa View Full Text


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Article Info

DATE

2022-06-14

AUTHORS

Tegbaru B. Gobezie, Asim Biswas

ABSTRACT

In the era of digital agriculture, Precision agriculture (PA) data sources are diverse in terms of the range of technology options and the type of data they generate. Government institutions, scientists, and the private sectors generate much of the PA data at the innovation, validation, and dissemination phases. At scale-up phases, farmers also generate tremendous amounts of data that might have privacy and ownership concerns. There remains the possibility of a better way to integrate PA data continent-wide in Africa. Data privacy and ownership issues must be addressed while still maintaining the integration of PA data at scale. The objective of this paper is to review the major challenges of PA data harmonization in Africa and discuss the existing opportunities in relation to technological advancements in PA data applications to address data sharing without compromising data privacy, ownership, and stewardship. Finally, a new PA data sharing and reward model—‘PrecisioNexion’ is proposed to rationalize data network systems by establishing a robust and self-sustaining business model. The model uses AI and blockchain technology to track and stamp PA data using unique dataset_IDs or PrecisionPrint (like a fingerprint), determining credit amounts using ‘pVouchers’ (like eVouchers) and distributing credits between PA data owners or ‘PrecisionProprietor’, data clients or ‘PrecisionClient’ and funders or ‘PrecisionPatron’. The proposed system provides a foundation for win–win–win PA data sharing and self-sustaining business models for data owners, technology solutions providers and funders, while ensuring a strong partnership between farmers’ cooperatives, private sector, scientists, governments, and financial institutions, and countries. More... »

PAGES

1-9

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11119-022-09928-w

DOI

http://dx.doi.org/10.1007/s11119-022-09928-w

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1148655515


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