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

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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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Ngankam, H., Lussier, M., Aboujaoudé, A., Pigot, H., Gaboury, S., Bouchard, K., … Giroux, S. (2023). NEARS-Hub, a Lightweight Edge Computing for Real-Time Monitoring in Smart Environments. In Lecture Notes in Networks and Systems (Vol. 594 LNNS, pp. 125–138). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-21333-5_13

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