Scientific decision support system of marine environmental management in China’s Yellow Sea and Bohai Sea based on cloud computing mode

Xiurong, Huang; Xiao, Lei; Xiaodong, Tou

doi:10.3233/jifs-179169

Cited by 5 publications

(1 citation statement)

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“…This data can then be transmitted to a cloud-based platform for analysis and decision-making. Machine Learning (ML) [12] ML refers to a subset of artificial intelligence (AI) that uses algorithms to learn from data and make predictions or decisions. In crop management, ML can be used to analyze data from IoT sensors, as well as other sources such as weather forecasts, satellite imagery, and historical crop yields.…”

Section: Applications Of Cloud-based Dss For Crop Managementmentioning

confidence: 99%

A Cloud-based Decision Support System for Crop Management: Techniques and Applications

Sharma¹

2020

TURCOMAT

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The purpose of this study is to provide an introduction to cloud-based decision support systems for crop management. In recent years, cloud computing, the Internet of Things (IoT), and machine learning have seen significant advancements, which has contributed to the rise in popularity of these kinds of systems. These technologies make it possible for farmers to gather, process, and analyse data in real time, which provides them with invaluable insights about the growth, yield, and overall health of their crops. This, in turn, assists farmers in making decisions that are better informed on the timing of when to sow, irrigate, and fertilise their crops, as well as when to harvest their produce. In this work, we draw on current research conducted in both the academic and industrial spheres to describe the many methods and uses of cloud-based decision support systems for crop management. In conclusion, we will discuss the many advantages and disadvantages of these systems, as well as the possible directions that future study may go.

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Section: Applications Of Cloud-based Dss For Crop Managementmentioning

confidence: 99%