Article (Scientific journals)
Edge AI-IoT Pivot Irrigation, Plant Diseases and Pests Identification
Debauche, Olivier; Mahmoudi, Saïd; Elmoulat, Meryem et al.
2020In Procedia Computer Science, 177, p. 40-48
Peer reviewed
 

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Keywords :
center-pivot irrgation; connected irrigation; smart irrigation; water requirement; Intelligent Irrigation
Abstract :
[en] In a growing population context with less soil and water resources, the irrigated agriculture allows to increase the yield and the production of several crops in order to meet the increase of the food and fibers demands. To be efficient, an irrigation system must correctly evaluate amount of water and moments to which to apply the irrigation doses. Monitoring systems are crucial in areas of the planet where water is scarce and in environmental harsh conditions to ensure an efficient crop growth. Moreover, plant diseases and pests impact the yields of crops, an early detection allows to treat the disease or pest quickly and reduce the impact of these latter. In this paper, we propose an integrated approach which optimize the water use, the supply of fertilizers, the treatment of plant diseases and pests with a center-pivot equiped with camera by means of IoT and AI algorithms.
Disciplines :
Computer science
Author, co-author :
Debauche, Olivier  ;  Université de Liège - ULiège > Terra
Mahmoudi, Saïd
Elmoulat, Meryem
Mahmoudi, Sidi Ahmed
Manneback, Pierre
Lebeau, Frédéric  ;  Université de Liège - ULiège > Département GxABT > Biosystems Dynamics and Exchanges
Language :
English
Title :
Edge AI-IoT Pivot Irrigation, Plant Diseases and Pests Identification
Publication date :
11 November 2020
Journal title :
Procedia Computer Science
eISSN :
1877-0509
Publisher :
Elsevier, Amsterdam, Netherlands
Volume :
177
Pages :
40-48
Peer reviewed :
Peer reviewed
Available on ORBi :
since 11 August 2020

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