Authors:
Hubert Ngankam
1
;
Maxime Lussier
2
;
Aline Aboujaoudé
2
;
Cédric Demongivert
3
;
Hélène Pigot
1
;
Sébastien Gaboury
3
;
Kevin Bouchard
3
;
Mélanie Couture
4
;
Nathalie Bier
2
and
Sylvain Giroux
1
Affiliations:
1
Laboratoire DOMUS, Département d’Informatique, Université de Sherbrooke, Sherbrooke, Canada
;
2
Centre de Recherche de l’Institut Universitaire de Gériatrie de Montréal - CIUSSS-CSMTL, Université de Montréal, Montréal, Canada
;
3
LIARA Lab, Université du Québec aC̀hicoutimi, Chicoutimi, Canada
;
4
CREG ÉS, CIUSSS West-Central Montreal, Côte-Saint-Luc, Canada
Keyword(s):
Ambient Assisted Living, Event-driven Architecture, Event Streaming, Apache Kafka, Spark, IoT, ADL, Lambda Architecture.
Abstract:
Ambient Assisted Living (AAL) aims to allow frail older adults to stay safe at home, partly through remote monitoring which offers clinicians a means to prevent and manage risks. AAL needs an architecture to support the large set of data emanating from multiple sensors dispatched in several smart homes. These data must be processed in real-time to take the appropriate decisions in time. In this article, we propose an Event-Driven Architecture according to the publish-subscribe pattern. The proposed architecture is the core of our system, named SAPA Technology. It is composed of three layers: data gathering, data ingestion, and data processing. To ingest the data stream, we choose Apache Kafka, an open-source broker, and Apache Spark, a streaming system to process the ingested data. The SAPA Technology architecture respects scalability, homogeneity, and modularity. It supports at least thirty-eight smart homes.