The Use of Distributed Processing and Cloud Computing in Agricultural Decision-Making Support Systems

Abstract

One of the main challenges in agriculture is to sustainably meet the demand for food while preserving natural resources for future productions. Information Technology can assist producers to make better decisions by providing them with data and tools that enhance decision-making process, consequently allowing better management of the natural resources. Cloud-computing platforms and the extraction of data available on public weather related data sets allow the development of web applications that can assist producers with their investing and planning decisions. This paper describes the Big Weather solution, an agricultural decision-making support system that utilizes a cloud-computing platform, distributed processing technologies, and a big data framework. This paper also presents Big Weather architecture and an example of metric calculations (average temperature and humidity) and discusses the performance of the solution when tested in different virtual machine scenario configurations. The novelty is the transparency of the framework, which allows farmers to make better decisions based on data available on the cloud.