Multi-Objective Scheduling for Agricultural Interventions

Research output: Chapter in Book/Report/Conference proceedingConference paper

62 Downloads (Pure)

Abstract

Monitoring crops and fields is an important aspect in the agricultural sector to prevent droughts, floods or the spreading of insects and diseases. We introduce an intelligent solution to monitor agricultural environments. The system learns a model of the underlying field which it then uses to plan an optimal monitoring schedule. By interactively querying the preferences of the decision maker, we define a weighting to optimise over multiple objectives in the schedule, such as visiting frequency, intervention frequency and distance. We implement this as an interactive demo, called CropBot, using LEGO Mindstorms.
Original languageEnglish
Title of host publicationBNAIC/BeNeLearn 2022
Publication statusPublished - 9 Nov 2022
EventBNAIC/BeNeLearn 2022: Joint International Scientific Conferences on AI and Machine Learning - Lamot Mechelen, Belgium
Duration: 7 Nov 20229 Nov 2022
https://bnaic2022.uantwerpen.be/

Publication series

NameBNAIC Proceedings
ISSN (Print)1568-7805

Conference

ConferenceBNAIC/BeNeLearn 2022
Abbreviated titleBNAIC/BeNeLearn 2022
Country/TerritoryBelgium
CityLamot Mechelen
Period7/11/229/11/22
Internet address

Fingerprint

Dive into the research topics of 'Multi-Objective Scheduling for Agricultural Interventions'. Together they form a unique fingerprint.

Cite this