Artificial Intelligence for Sustainable Agriculture: A Comprehensive Review of AI-Driven Technologies in Crop Production
COMSATS University Islamabad · National University of Computer and Emerging Sciences · +2 more institutions
Abstract
Smart farming leverages Artificial Intelligence (AI) to address modern agricultural sustainability challenges. This study investigates the application of machine learning (ML), deep learning (DL), and time series analysis in agriculture through a systematic literature review following the PRISMA methodology. The review highlights the critical roles of ML and DL techniques in optimizing agricultural processes, such as crop selection, yield prediction, soil compatibility classification, and water management. ML algorithms facilitate tasks like crop selection and soil fertility classification, while DL techniques contribute to forecasting crop production and commodity prices. Additionally, time series analysis is…
Citation impact
- FWCI
- 67.20
- Percentile
- 100%
- References
- 87
Authors
5Topics & keywords
- Production (economics)
- Agriculture
- Crop production
- Sustainable agriculture
- Sustainable production
- Emerging technologies
- Agricultural engineering
- Engineering