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Cloud architecture for digital phenotyping and automation
Debauche, Olivier; Mahmoudi, Saïd; Manneback, Pierre et al.
2018In IEEE Cloud Computing
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Keywords :
cloud; lambda architecture; digital phenotyping; 3D plant model; phytotron; application platform; Internet of things
Abstract :
[en] Digital phenotyping presents a very important tool for scientists to measure with high accuracy the effects of external phenomena on plant development. Plant phenotyping is mainly based on imaging techniques. However, the number of images and parameters used to store and treat these parameters are continuously growing. Consequently, the high-throughput of data and the need of specific treatment in real or near real-time requires a large quantity of resources. Moreover, the increasing amount of particular phenotyping case studies needs the development of specific application. Cloud architectures offers means to store a wide range of numerous data and host a large quantity of specific software to process these data. In this paper, we propose to match digital phenotyping need and cloud possibilities in a lambda cloud architecture in order to store and treat this important amount of data. We also propose a data platform allowing to host applications and access to the stored data within the lambda architecture. The present application platform allows to use several frameworks with a fine-grained resource use of the cluster. We develop then a case study in a controlled environment system (growth chamber) where we grow basil plants.
Disciplines :
Computer science
Author, co-author :
Debauche, Olivier  ;  Université de Liège - ULiège > Doct. sc. agro. & ingé. biol. (Paysage)
Mahmoudi, Saïd
Manneback, Pierre
Massinon, Mathieu ;  Université de Liège - ULiège > Agronomie, Bio-ingénierie et Chimie (AgroBioChem) > Gestion durable des bio-agresseurs
Tadrist, Nassima ;  Université de Liège - ULiège > Gembloux Agro-Bio Tech
Lebeau, Frédéric  ;  Université de Liège - ULiège > Ingénierie des biosystèmes (Biose) > Biosystems Dynamics and Exchanges
Mahmoudi, Sidi
Language :
English
Title :
Cloud architecture for digital phenotyping and automation
Publication date :
08 February 2018
Event name :
Cloud Tech 2017
Event organizer :
ENSIAS
Event place :
Rabat, Morocco
Event date :
du 24 octobre 2017 au 26 octobre 2017
Audience :
International
Journal title :
IEEE Cloud Computing
eISSN :
2325-6095
Publisher :
Institute of Electrical and Electronics Engineers (IEEE), Piscataway, United States - New York
Peer reviewed :
Peer Reviewed verified by ORBi
Available on ORBi :
since 16 September 2017

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