Edge AI-IoT Pivot Irrigation, Plant Diseases and Pests Identification

[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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171 (11 by ULiège)

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829 (5 by ULiège)

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Bibliography

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