Database Reference
In-Depth Information
Addressing Information Processing Needs of
Digital Agriculture with OpenIoT Platform
B
Prem Prakash Jayaraman
1(
)
, Doug Palmer
1
, Arkady Zaslavsky
1
, Ali Salehi
1
,
and Dimitrios Georgakopoulos
2
1
CSIRO Digital Productivity, Canberra 2601, Australia
{
prem.jayaraman,doug.palmer,arkady.zaslavsky
}
@csiro.au
2
School of Computer Science and Information Technology, RMIT University,
GPO Box 2476, Melbourne 3001, Australia
dimitrios.georgakopoulos@rmit.edu.au
Abstract.
Food security is a global challenge and agriculture can add-
ress this challenge through radical improvements in productivity, e-
ciency and effectiveness. Internet of Things (IoT) is a major enabler
of such improvements. This paper discusses challenges that agricultural
industry is facing and proposes a solution based on IoT technology and a
specific platform called OpenIoT developed jointly by the EU FP7 Ope-
nIoT consortium. Phenonet is an OpenIoT use case developed by CSIRO,
Australia and demonstrates how digital agriculture benefits from deploy-
ing the IoT. Experience and lessons from using OpenIoT middleware for
Phenonet development are also presented and analysed.
1
Introduction
Agricultural industry faces many challenges, such as climate change, water short-
ages, labour shortages due to an ageing urbanized population, and increased
societal concern about issues such as animal welfare, food safety, and environ-
mental impact [
11
]. Quoting from a recent article by IBM [
5
]. “Agriculture is
ultimately driven by the mathematics of science; balancing the pH levels of soil,
the rate of Nitrogen depletion and many other factors for optimum growth of
grains and produce”. The goal is to use information technology to harness the
vast amount of data available from the field, equipment sensors and other third-
party sources, to provide fact- and math-based decision support to augment
farmers experience.
Pervasive and ubiquitous computing have addressed agriculture in different
precision agriculture projects. One such example is the use of sensor networks for
viticulture [
4
]. Modern agriculture is a knowledge-intensive industry that thrives
on multiple facets of information such as climate, farm/field management, sup-
ply chain, consumer demand, environmental impact, livestock management and
health etc. According to the United Nations Food and Agriculture Organization
Prof. Zaslavsky is a visiting Professor at St. Petersburg National Research University
of IT, Mechanics and Optics, Russia.
c
Springer International Publishing Switzerland 2015
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