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An Ontology-Based Ambient Intelligence Framework for Ageing Workforce

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Intelligent Systems and Applications (IntelliSys 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 543))

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Abstract

As workers are expected to stay longer in the labor force, the active workforce is ageing more and more every day. Ageing workforce is characterized by the necessity of specific solutions for elderly employees in the workspaces, minding their specific health conditions with a continuous attention, while regarding for other people sharing the same environment. The recent developments in Ambient Intelligence (AmI) field seem a promising solution for the necessities of an ageing workforce. In this work, an ontology-based AmI framework is proposed to enhance the comfort metrics in workplaces, considering the specific physical needs of each worker and collective well-being of all workers at the same time. The framework aims at being the less invasive possible, avoiding direct monitoring of the workers and their activities, relying instead on knowledge related to their status. This paper introduces the framework, its architecture and the underlying ontology. Two scenarios specify the adaptation provided by the framework, while a preliminary validation is presented.

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Authors and Affiliations

  1. Institute of Intelligent Industrial Technologies and Systems for Advanced Manufacturing (STIIMA), National Research Council of Italy (CNR), Via G. Previati 1/E, 23900, Lecco, Italy

    Daniele Spoladore, Turgut Cilsal & Marco Sacco

  2. Department of Pure and Applied Sciences, Insubria University, Via Ottorino Rossi 9, 21100, Varese, Italy

    Daniele Spoladore

Authors
  1. Daniele Spoladore
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  2. Turgut Cilsal
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  3. Marco Sacco
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Correspondence to Daniele Spoladore .

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Editors and Affiliations

  1. Faculty of Science and Engineering, Saga University, Saga, Japan

    Kohei Arai

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Spoladore, D., Cilsal, T., Sacco, M. (2023). An Ontology-Based Ambient Intelligence Framework for Ageing Workforce. In: Arai, K. (eds) Intelligent Systems and Applications. IntelliSys 2022. Lecture Notes in Networks and Systems, vol 543. Springer, Cham. https://doi.org/10.1007/978-3-031-16078-3_22

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