Dynamic spatial task generation for collaborative location-based collecting systems coverage objectives

Autores
Dalponte Ayastuy, María Nieves; Torres, Diego; Lattanzio, Bruno J.
Año de publicación
2022
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Collaborative location-based collecting systems (CLCS) are a particular case of collaborative systems where a community of users collaboratively collect geo-referenced data. Each CLCS sets its territory coverage objectives, commonly defined as to guarantee that all the affected territory is surveyed with a particular coverage criterium. This paper presents a three-step pipeline to recommend the subareas that require observations dynamically. The first step generates a disjoint and adjacent set of areas -a mesh- covering the sampling territory. The second step sets a priority and coverage objective for each area. Finally, the third step considers the project’s objectives and the area coverage situation to recommend the areas that need surveys. The output of this last step is an input for a user-task distribution process where the user’s profile is taken into account. Moreover, an example of meshing strategy and task generation is proposed.
This paper is partially supported by funding provided by the STIC AmSud program, Project 22STIC-01.
Facultad de Informática
Materia
Ciencias Informáticas
Collaborative Location-based Collecting Systems
Meshing, Decision-making
Spatial Crowdsourcing
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/158787
Acceder
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network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Dynamic spatial task generation for collaborative location-based collecting systems coverage objectivesDalponte Ayastuy, María NievesTorres, DiegoLattanzio, Bruno J.Ciencias InformáticasCollaborative Location-based Collecting SystemsMeshing, Decision-makingSpatial CrowdsourcingCollaborative location-based collecting systems (CLCS) are a particular case of collaborative systems where a community of users collaboratively collect geo-referenced data. Each CLCS sets its territory coverage objectives, commonly defined as to guarantee that all the affected territory is surveyed with a particular coverage criterium. This paper presents a three-step pipeline to recommend the subareas that require observations dynamically. The first step generates a disjoint and adjacent set of areas -a mesh- covering the sampling territory. The second step sets a priority and coverage objective for each area. Finally, the third step considers the project’s objectives and the area coverage situation to recommend the areas that need surveys. The output of this last step is an input for a user-task distribution process where the user’s profile is taken into account. Moreover, an example of meshing strategy and task generation is proposed.This paper is partially supported by funding provided by the STIC AmSud program, Project 22STIC-01.Facultad de Informática2022info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf76-87http://sedici.unlp.edu.ar/handle/10915/158787enginfo:eu-repo/semantics/altIdentifier/isbn/978-950-34-2303-5info:eu-repo/semantics/reference/hdl/10915/158339info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-11-26T10:19:25Zoai:sedici.unlp.edu.ar:10915/158787Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-11-26 10:19:25.558SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Dynamic spatial task generation for collaborative location-based collecting systems coverage objectives
title Dynamic spatial task generation for collaborative location-based collecting systems coverage objectives
spellingShingle Dynamic spatial task generation for collaborative location-based collecting systems coverage objectives
Dalponte Ayastuy, María Nieves
Ciencias Informáticas
Collaborative Location-based Collecting Systems
Meshing, Decision-making
Spatial Crowdsourcing
title_short Dynamic spatial task generation for collaborative location-based collecting systems coverage objectives
title_full Dynamic spatial task generation for collaborative location-based collecting systems coverage objectives
title_fullStr Dynamic spatial task generation for collaborative location-based collecting systems coverage objectives
title_full_unstemmed Dynamic spatial task generation for collaborative location-based collecting systems coverage objectives
title_sort Dynamic spatial task generation for collaborative location-based collecting systems coverage objectives
dc.creator.none.fl_str_mv Dalponte Ayastuy, María Nieves
Torres, Diego
Lattanzio, Bruno J.
author Dalponte Ayastuy, María Nieves
author_facet Dalponte Ayastuy, María Nieves
Torres, Diego
Lattanzio, Bruno J.
author_role author
author2 Torres, Diego
Lattanzio, Bruno J.
author2_role author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Collaborative Location-based Collecting Systems
Meshing, Decision-making
Spatial Crowdsourcing
topic Ciencias Informáticas
Collaborative Location-based Collecting Systems
Meshing, Decision-making
Spatial Crowdsourcing
dc.description.none.fl_txt_mv Collaborative location-based collecting systems (CLCS) are a particular case of collaborative systems where a community of users collaboratively collect geo-referenced data. Each CLCS sets its territory coverage objectives, commonly defined as to guarantee that all the affected territory is surveyed with a particular coverage criterium. This paper presents a three-step pipeline to recommend the subareas that require observations dynamically. The first step generates a disjoint and adjacent set of areas -a mesh- covering the sampling territory. The second step sets a priority and coverage objective for each area. Finally, the third step considers the project’s objectives and the area coverage situation to recommend the areas that need surveys. The output of this last step is an input for a user-task distribution process where the user’s profile is taken into account. Moreover, an example of meshing strategy and task generation is proposed.
This paper is partially supported by funding provided by the STIC AmSud program, Project 22STIC-01.
Facultad de Informática
description Collaborative location-based collecting systems (CLCS) are a particular case of collaborative systems where a community of users collaboratively collect geo-referenced data. Each CLCS sets its territory coverage objectives, commonly defined as to guarantee that all the affected territory is surveyed with a particular coverage criterium. This paper presents a three-step pipeline to recommend the subareas that require observations dynamically. The first step generates a disjoint and adjacent set of areas -a mesh- covering the sampling territory. The second step sets a priority and coverage objective for each area. Finally, the third step considers the project’s objectives and the area coverage situation to recommend the areas that need surveys. The output of this last step is an input for a user-task distribution process where the user’s profile is taken into account. Moreover, an example of meshing strategy and task generation is proposed.
publishDate 2022
dc.date.none.fl_str_mv 2022
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Objeto de conferencia
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/158787
url http://sedici.unlp.edu.ar/handle/10915/158787
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/isbn/978-950-34-2303-5
info:eu-repo/semantics/reference/hdl/10915/158339
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
76-87
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
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reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
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repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
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