Big data is a collection of large volumes of data sets which are more complicated to analyze using standard data processing methods. It also emphasizes parameters like data variety and velocity data. Big data will play a most significant role in our daily life regarding applications like healthcare electronic commerce, agriculture, telecommunication, government, and financial trading. In the agriculture domain, big data is an optimal method to increase the productivity of farming by gathering and processing information like plant growth, farmland monitoring, greenhouse gases monitoring, climate change, soil monitoring and so forth. Virtualization is an emerging technique that can be combined with big data in agriculture. Virtualization has been used extensively in research for a long time, the term “virtual” entities affecting a real-life form. In agriculture, it has many more physical objects, sensors, and devices. This physical object is virtualized and has digital representation to store, communicate and process via the internet. The information from the virtual object has a large volume of data which helps meaningful data analysis or aspects to make application services like decision making, problem notification, and information handling. This paper provides a comprehensive review of big data virtualization in the agriculture domain. The virtualization methodology, and tools used by many researchers is surveyed.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.