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NEARS-Hub, a Lightweight Edge Computing for Real-Time Monitoring in Smart Environments

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Proceedings of the International Conference on Ubiquitous Computing & Ambient Intelligence (UCAmI 2022) (UCAmI 2022)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 594))

Abstract

iNnovative Easy Assistance System (NEARS) is a Canadian transdisciplinary research project that aims to create a platform and standards that will make the development of Ambient Assisted Living (AAL) solutions technically feasible and clinically viable. It built and operationalized a hardware and software infrastructure for smart environments called NEARS-Hub. The key function of the NEARS-Hub is to deliver data generated by The Internet of Things (IoT) devices near the edge. The processing of the collected data in homes and its storage in the event of break-in services are carried out locally at the level of the edge node. The goal is to provide high-quality services and a quick response time. Therefore, edge nodes must be capable of flexibility, interoperability, and scalability to adapt their services in case of unforeseen situations. A common modeling approach is to create services without separating responsibilities between system layers. However, very few solutions allow the administration of services and the provisioning of resources in a flexible way and as close as possible to the equipment, at the edge of the network, or, ultimately, at the places where the data has been generated. This article proposes NEARS-Hub, a lightweight edge computing platform for AAL solutions, which revolves around three main notions: interoperability, flexibility, and scalability. The design of the current version of the NEARS-Hub is based on knowledge from several home experiments. The proposed model is validated by comparing the performances of the NEARS-Hub with a version based on a classic AAL solution.

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Notes

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    https://www.academia.edu/download/51203248/199.pdf.

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    https://www.raspberrypi.com/products/raspberry-pi-4-model-b/.

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Acknowledgements

Special thanks to the DOMUS laboratory development team who spent several weeks developing and testing the NEARS-Hub, in particular, Mauricio Chiazzaro - Paul Guerlin - Yannick Drolet - Mathieu Gagnon. The research is funded by the AGE-WELL network and the Collaborative Health Research Projects of Canada. Nathalie Bier is supported by a salary award from the Fonds de la recherche du Québec - Santé.

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Authors and Affiliations

  1. Laboratoire DOMUS, Département d’informatique, Université de Sherbrooke, Sherbrooke, Canada

    Hubert Ngankam, Hélène Pigot & Sylvain Giroux

  2. Centre de recherche de l’Institut universitaire de gériatrie de Montréal - CIUSSS-CSMTL, Université de Montréal, Montréal, Canada

    Maxime Lussier, Aline Aboujaoudé & Nathalie Bier

  3. LIARA Lab, Université du Québec à Chicoutimi, Chicoutimi, Canada

    Sébastien Gaboury & Kevin Bouchard

  4. CREGÉS, CIUSSS West-Central Montreal, Côte-Saint-Luc, Canada

    Mélanie Couture

Authors
  1. Hubert Ngankam
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  2. Maxime Lussier
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  3. Aline Aboujaoudé
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  4. Hélène Pigot
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  5. Sébastien Gaboury
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  6. Kevin Bouchard
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  7. Mélanie Couture
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  8. Nathalie Bier
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  9. Sylvain Giroux
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Corresponding author

Correspondence to Hubert Ngankam .

Editor information

Editors and Affiliations

  1. Castilla-La Mancha University, Ciudad Real, Spain

    José Bravo

  2. Computer Science Department, University of Chile, Santiago, Chile

    Sergio Ochoa

  3. CICESE, Ensenada, Mexico

    Jesús Favela

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Ngankam, H. et al. (2023). NEARS-Hub, a Lightweight Edge Computing for Real-Time Monitoring in Smart Environments. In: Bravo, J., Ochoa, S., Favela, J. (eds) Proceedings of the International Conference on Ubiquitous Computing & Ambient Intelligence (UCAmI 2022). UCAmI 2022. Lecture Notes in Networks and Systems, vol 594. Springer, Cham. https://doi.org/10.1007/978-3-031-21333-5_13

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