Exploring the Potential of Deep Learning in Overcoming Challenges Faced by Rural Kutch

Registration ID: IJNRD_196209

Published ID: IJNRD2305577

DOI: Click Here to Get

Bhaveshbhai Rameshbhai Maheshwari

Kutch, Deep Learning, Machine Learning, Prediction, Agriculture, Healthcare, Earthquake, Handicraft.

Deep learning is a powerful subset of machine learning that has gained considerable attention in recent years due to its ability to solve complex problems. In this paper, I discussed about how deep learning can possibly use to some major problems in rural Kutch like predicting crop yield, seismic activity, spread and impact of diseases, performance of small and medium size business and ground water quality. I conducted a comprehensive review of existing literature on deep learning applications in solving problems like mentions above and analyzed the feasibility of implementing such solutions in Kutch. This study suggest that deep learning can significantly improve to solve rural Kutch’s problems to estimation, crop yield, early earthquake identification, helping gain more handicraft business and finding better ground water reservoirs. This paper states how integrating technologies like deep learning with local knowledge and participatory approaches to enhance the sustainability of solving major problems in rural Kutch.

Published Paper   E-Certificate

Bhaveshbhai Rameshbhai Maheshwari (May-2023). Exploring the Potential of Deep Learning in Overcoming Challenges Faced by Rural Kutch. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(5), f524-f527. https://ijnrd.org/papers/IJNRD2305577.pdf

Volume 8 Issue 5, May-2023

Pages : f524-f527

Paper Reg. ID: IJNRD_196209

Published Paper Id: IJNRD2305577

Downloads: 000121985

Research Area: Information Technology 

Country: Bharuch, Gujarat, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2305577.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2305577

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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