Authors:
J. Hadabas
1
;
M. Hovari
2
;
I. Vass
2
and
A. Kertesz
1
Affiliations:
1
Software Engineering Department, University of Szeged and Hungary
;
2
Institute of Plant Biology, Biological Research Centre and Hungary
Keyword(s):
Internet of Things, Cloud Computing, Plant Phenotyping, Gateway.
Related
Ontology
Subjects/Areas/Topics:
Cloud Computing
;
Collaboration and e-Services
;
Data Engineering
;
e-Business
;
Enterprise Information Systems
;
Mobile Software and Services
;
Ontologies and the Semantic Web
;
Services Science
;
Software Agents and Internet Computing
;
Software Engineering
;
Software Engineering Methods and Techniques
;
Telecommunications
;
Web Services
;
Wireless Information Networks and Systems
Abstract:
According to a recent Beecham Research report, food production have to be increased by 70 percent till 2050 to feed 9.6 billion global population predicted by the United Nations Food and Agriculture Organisation. Since Cloud Computing and the Internet of Things (IoT) have already opened new ways for revolutionizing industrial processes, these technologies could be important for the farming industry. Smart farming has the potential to improve productivity and reduce waste to transform agriculture. Plant phenotyping is an important research field that gained a high attention recently due to the need for complex monitoring of development and stress responses of plants. However, the current phenotyping platforms are very expensive, and used in large central infrastructures, which limit their widepread use. The newly emerging ICT technologies together with the availability of low cost sensors and computing solutions paved the way towards the development of affordable phenotyping solutions
, which can be applied under standard greenhouse conditions. The Internet of Living Things (IoLT) project has been launched to integrate IoT technological research with applied research on specific, biological applications. In this paper we introduce our research results for developing a low cost plant phenotyping platform for small sized plants, which is one of our goals in this project. The proposed IoLT Smart Pot is capable of monitoring environmental parameters by sensors placed above the plant and into the pot, managed by a Raspberry Pi board placed under the pot. We have also developed a private IoT-Cloud gateway for receiving, storing, visualizing and downloading the monitored parameters sent by the pot devices. We have performed the evaluation of our proposed platform both with simulated and real smart pots.
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