Smart Agriculture for Renewable energy Integration Using Cloud and Big Data Analysis

Smart agriculture, often known as precision farming, is a fast-expanding multidisciplinary topic that combines expertise from agriculture, technology, data science, and environmental research. As the population grows and food demand rises, sustainable agriculture requires efficient use of water and energy resources. An integrated and cost-effective Smart Agriculture solution. Small and medium farmers struggle to accept commercial solutions due to their high cost. Renewable Energy Consolidation helps for Advance energy cost-effective agriculture by reducing reliance on fossil fuels for water table pumping. The proposed solution revolves around the cloud as it is crucial in smart farming as it stores key characteristics that are compared to field data. Wireless sensors linked to the cloud collect data from the ground. Machine learning algorithms study the data in real time. This analysis helps farmers understand the status of their crops. Big data provides complete information on rainfall patterns, water cycles, and fertilizer levels. Farmers can use this content to make informed conclusion about crop selection, soil fertility, and harvest regulation. Smart farming uses IoT, cloud computing, and big data analysis to optimize agricultural yields. This helps in enhancing sensors to be more affordable and versatile in data collection, along with advancing computer capabilities for better data analysis and predictions.

Authors

Publication Details

Journal
Journal of Information Systems Engineering & Management
Published
2025-04-18
DOI
https://doi.org/10.52783/jisem.v10i37s.6384
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
0.00
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article

Smart Agriculture for Renewable energy Integration Using Cloud and Big Data Analysis

G. Shaheen Firdous
Journal of Information Systems Engineering & Management
Smart Agriculture and AI
article

Smart Agriculture for Renewable energy Integration Using Cloud and Big Data Analysis

G. Shaheen Firdous
article en

Abstract

Smart agriculture, often known as precision farming, is a fast-expanding multidisciplinary topic that combines expertise from agriculture, technology, data science, and environmental research. As the population grows and food demand rises, sustainable agriculture requires efficient use of water and energy resources. An integrated and cost-effective Smart Agriculture solution. Small and medium farmers struggle to accept commercial solutions due to their high cost. Renewable Energy Consolidation helps for Advance energy cost-effective agriculture by reducing reliance on fossil fuels for water table pumping. The proposed solution revolves around the cloud as it is crucial in smart farming as it stores key characteristics that are compared to field data. Wireless sensors linked to the cloud collect data from the ground. Machine learning algorithms study the data in real time. This analysis helps farmers understand the status of their crops. Big data provides complete information on rainfall patterns, water cycles, and fertilizer levels. Farmers can use this content to make informed conclusion about crop selection, soil fertility, and harvest regulation. Smart farming uses IoT, cloud computing, and big data analysis to optimize agricultural yields. This helps in enhancing sensors to be more affordable and versatile in data collection, along with advancing computer capabilities for better data analysis and predictions.

Journal of Information Systems Engineering & ManagementVol. 10(37s)
Openalex Percentile: Top 94%
Smart Agriculture and AI
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