Book of Extended summaries ISDA

International Conference on Reimagining Rainfed Agro-ecosystems: Challenges &
Opportunities during 22-24, December 2022 at ICAR-CRIDA, Hyderabad
T5-38P-1589
Cloud Computing, Data science for Big Data Management in Agriculture
R. Lakshmi Sreya
Maturi Venkata Subba Rao (MVSR) Engineering College, Hyderabad, India
Farm productivity and farmer income in India is plagued with several challenges – marginal
land holdings of farmers making mechanization difficult and implementation of technology
difficult or unviable, timely access to genuine and high-quality inputs and farming advice,
heavily intermediated supply chains, dependence on monsoon rains, and inadequate storage
facilities. Cloud computing technology in agricultural area has greater scope in the overall
development of India. This paper reviews the potential uses of cloud computing in agriculture.
Methodology
This paper is based on literature review of application of data science tools in making
agriculture more competitive and efficient.
Results
Data science is the method of gleaning insights from data. It enables the use of real-time data
and past data to form meaningful insights on buyer behavior, customer credit behavior, product
testing, cropping patterns, and others. Data science already plays a significant role in banking
and healthcare, both in India and globally. The principles of data science could also be applied
to the Indian agriculture industry across the value chain from the farm through retail.
Agriculture and cloud computing cloud services:
a) Infrastructure as a Service (IaaS):
Infrastructure as a Service abbreviated as IaaS, contains the basic building blocks for cloud IT
and typically provide access to networking features, computers (virtual or on dedicated
hardware), and data storage space. Infrastructure as a Service provides you with the highest
level of flexibility and management control over your IT resources and is most similar to
existing IT resources that many IT departments and developers are familiar with today.
b) Platform as a Service (PaaS):
Platforms as a service remove the need for organizations to manage the underlying
infrastructure (usually hardware and operating systems) and allow you to focus on the
deployment and management of your applications. This helps you to be more efficient as you
don’t need to worry about resource procurement, capacity planning, software maintenance,
patching, or any of the other undifferentiated heavy lifting involved in running your
application.
783 | Page Emerging approaches (RS, AI, ML, Drones etc) for crop management &assessment