Mobile Personalised Support in Industrial Environments: Coupling Learning with Context - Aware Features - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Communication Dans Un Congrès Année : 2014

Mobile Personalised Support in Industrial Environments: Coupling Learning with Context - Aware Features

Résumé

The human response time to events in a manufacturing environment depends both on the available skills and competencies of technical staff but also on the extent to which actionable and task-relevant content is readily available when and where is needed. Relevance itself is determined by the task situation context, which in turn is influenced by many factors. This paper presents the development of a context-aware mobile support system for personalised assistance in industrial environments. Combining the individual strengths of learning and content management systems with the ubiquity of delivering relevant content to users carrying NFC (Near Field Communication) enabled mobile devices, the system aims at both enhancing personnel competences as well as their work efficiency. The developed solution is customised to serve an industrial maintenance-support application scenario, wherein the relevant context is determined through location and asset identification, as well as through task and user profiling, offering practical on the spot mobile support.
Fichier principal
Vignette du fichier
978-3-662-44739-0_37_Chapter.pdf (522.3 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01388265 , version 1 (26-10-2016)

Licence

Paternité

Identifiants

Citer

Nikos Papathanasiou, Dimitris Karampatzakis, Dimitris Koulouriotis, Christos Emmanouilidis. Mobile Personalised Support in Industrial Environments: Coupling Learning with Context - Aware Features. IFIP International Conference on Advances in Production Management Systems (APMS), Sep 2014, Ajaccio, France. pp.298-306, ⟨10.1007/978-3-662-44739-0_37⟩. ⟨hal-01388265⟩
221 Consultations
68 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More