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Efficient agricultural disaster financing using satellite data and artificial intelligence.
- Source :
-
Computers & Electrical Engineering . Oct2022, Vol. 103, pN.PAG-N.PAG. 1p. - Publication Year :
- 2022
-
Abstract
- • The proposed study investigates the consequences of smallholder economic growth during the agricultural crisis. • The proposed model combines the satellite data and artificial intelligence to analyze the agricultural promotion of inclusive finance during the disaster. • Based on satellite data and artificial intelligence, we build an application system for inclusive financing of small farmers in agricultural disasters. • The proposed study validates the impact of an application system for small farmer inclusive finance based on satellite data and artificial intelligence in agricultural catastrophes. Investigating the consequences of smallholder economic growth amid the agricultural emergency is essential. In this paper, we evaluate the agricultural promotion of inclusive financing during the disaster using satellite data. We use inclusive finance to improve the income of small farmers during agricultural disasters, improve satellite remote sensing data analysis algorithms through neural networks, and combine satellite data and Artificial Intelligence (AI) to process data during agricultural disasters. Additionally, we construct an application system for inclusive finance of small farmers in agricultural disasters based on satellite data and AI. The proposed study verifies the effect of the application system for inclusive finance of small farmers based on satellite data and AI in agricultural disasters. The study's findings indicate that an inclusive finance system for small farmers in agricultural disasters based on satellite data and AI has a role in boosting smallholder economic development during the crisis. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00457906
- Volume :
- 103
- Database :
- Academic Search Index
- Journal :
- Computers & Electrical Engineering
- Publication Type :
- Academic Journal
- Accession number :
- 159600450
- Full Text :
- https://doi.org/10.1016/j.compeleceng.2022.108394