Towards a Model to Address the Interplay Between IoT Applications and Users in Complex Heterogeneous Contexts

  • Carmelo ArditoEmail author
  • Danilo Caivano
  • Lucio Colizzi
  • Loredana Verardi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11262)


Internet of Things (IoT) is now pervasive in most business and Public Administration processes. Along with the dizzying development of technological solutions, in recent years new methodological approaches are emerging with the objective of abstracting IoT functionalities, in order to manage them as resources in project management methodologies. A critical aspect is the representation of the knowledge grasped from the data acquired by IoT devices, since different types of users interact with such data with different goals. In order to transform them in knowledge, data have to be organized in a proper way and meaningfully provided in an IoT application specific for that type of user. In this paper, we propose the Knowledge Stratification Model that technical experts can take into account when developing an IoT application. The model, which organizes the knowledge elements in three layers, aims to identify the data produced by IoT devices and integrate them into business processes, thus making them meaningful for the user. A semantic approach, based on three subsets of ontologies specific for each model layer, is proposed to represent domain knowledge and to solve the technological and user interaction semantic issues characterizing complex and heterogeneous contexts as Smart City.


Business processes Knowledge model Ontology 



This work is funded by Italian Ministry of Education, University and Research (MIUR) through PON Ricerca e Innovazione 2014-2020 - Asse I “Investimenti in capitale umano” - Azione I.1 “Dottorati Innovativi con caratterizzazione industriale” (CUP H92H18000210006 and H92H18000200006 approved with D.R.n.991 on 29/03/2018 of University of Bari Aldo Moro).


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Copyright information

© IFIP International Federation for Information Processing 2019

Authors and Affiliations

  1. 1.Dipartimento di InformaticaUniversità degli Studi di Bari Aldo MoroBariItaly

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