A Findings and Discussions of the Application of IoT and Machine Learning Towards Shift Agriculture in India

Izna,; Sharma, Anil; Pandey, Rajendra

doi:10.1109/smart55829.2022.10046787

Cited by 2 publications

(2 citation statements)

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“…Researchers have been focusing on efficient resource usage to avoid environmental damage. 74 China is the top producer of fruits, vegetables, poultry, and so on, as per the report submitted by the Food and Agriculture Organization of the United Nations. The top stakeholders in agriculture in China have been investing in sustainable agriculture resources by the adoption of artificial intelligence, internet of things, robotics and drones.…”

Section: Key Insights Of Impact Analysismentioning

confidence: 99%

“…Several Agro‐tech companies have been rising to add more quality to the food chain. Researchers have been focusing on efficient resource usage to avoid environmental damage 74 . China is the top producer of fruits, vegetables, poultry, and so on, as per the report submitted by the Food and Agriculture Organization of the United Nations.…”

Section: Impact Analysismentioning

confidence: 99%

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Information and communication technology in smart agriculture: A scientometric review

Bala,

Kaur

2024

Concurrency and Computation

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SummaryAgriculture has been affected by several global trends raising the concern for food security. Agri‐food demands are amplifying due to the ever‐escalating population numbers. Thus, the notion of extending the use of smart innovative technology in managing agricultural practices has emerged rapidly over the last decade. Technological innovations have contributed significantly to shape modern agriculture as smart agriculture. Smart agriculture unfolds various benefits such as increased production, real time data and production insights and remote monitoring. The rising advancements in Information and Communication Technologies (ICT) have paved the way for researchers to use these technologies in managing agricultural practices, leading to greater benefits for farmers and society. These innovations are the key to establishing agriculture as a research discipline. The purpose of this article is to conduct a scientometric analysis to study the structure and evolution of research activities in the field of smart agriculture. The scientometric analysis aims to empirically map the scientific knowledge and identify any possible challenges in the field. This study performs elementary analysis to study publication growth over the years, impact analysis to assess the leading journals, authors, and countries, and articles analysis for findings patterns among the citations over the years and among the keyword‐based clusters. There has been a considerable increase of more than 200% in the number of publications from 2011 to 2022. However, around 60% of authors have contributed with a single publication. The findings of the study reveal the research trends and hot topics for future research fronts. Deep learning, digital agriculture, object detection, blockchain, and semantic segmentation have been identified as trending topics in smart agriculture. Comprehensively, an intellectual view of the agriculture domain is presented as a scientific field in this article.

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Section: Key Insights Of Impact Analysismentioning

confidence: 99%

Section: Impact Analysismentioning

confidence: 99%