Logo des Repositoriums
 

Predictive task scheduler and ERP system for automated vegetable cultivation in an outdoor environment

Kurzanzeige
dc.contributor.authorMaike, Simon
dc.contributor.authorAbbas, Farooq
dc.contributor.authorLee, Ting Sheng
dc.contributor.authorKühnast, Marvin
dc.contributor.authorWeber, Bettina
dc.contributor.authorBecker, Rolf
dc.contributor.authorFranko, Josef
dc.date.accessioned2024-04-08T11:56:35Z
dc.date.available2024-04-08T11:56:35Z
dc.date.issued2024
dc.description.abstractAutomated spot farming is a promising approach to overcome the ecological and economical challenges in modern agriculture. This requires sophisticated robotic controls and data management. The AgriPV-Bot, as a full farming system for mixed vegetable farming, achieves this by extending a classical ERP (enterprise resource planning) system towards monitoring single plant cultivation. The task scheduler analyzes this data, determines the resulting horticultural process for each specific plant individually and monitors the process execution that is performed by robotics. This paper introduces the features of the ERP system as well as the strategy for the predictive task scheduler.en
dc.identifier.doi10.18420/giljt2024_03
dc.identifier.isbn978-3-88579-738-8
dc.identifier.issn2944-7682
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/43896
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartof44. GIL - Jahrestagung, Biodiversität fördern durch digitale Landwirtschaft
dc.relation.ispartofseriesLecture Notes in Informatics(LNI) - Proceedings, Volume P - 344
dc.subjecttask scheduling
dc.subjectERP system
dc.subjectOdoo
dc.subjectRobot Operating System (ROS)
dc.subjectspot farming
dc.titlePredictive task scheduler and ERP system for automated vegetable cultivation in an outdoor environmenten
dc.typeText/Conference Paper
gi.citation.endPage334
gi.citation.publisherPlaceBonn
gi.citation.startPage329
gi.conference.date27.-28. Februar 2024
gi.conference.locationStuttgart
gi.conference.reviewfull

Dateien

Originalbündel
1 - 1 von 1
Vorschaubild
Name:
GIL_2024_Maike_329-334.pdf
Größe:
350.27 KB
Format:
Adobe Portable Document Format
Herunterladen

Sammlungen

P344 - 44. GIL-Jahrestagung 2024 - Fokus: Biodiversität fördern durch digitale Landwirtschaft