A comprehensive and scalable middleware for Ambient Assisted Living based on cloud computing and Internet of Things. (8th December 2016)

• Record Type: Journal Article
• Authors: Gomes, Berto de Tácio Pereira; Muniz, Luiz Carlos Melo; da Silva e Silva, Francisco José; Ríos, Luis Eduardo Talavera; Endler, Markus
• Other Names: Zbakh Mostapha guestEditor.; Bakhouya Mohamed guestEditor.; Essaaidi Mohamed guestEditor.; Piccialli Francesco guestEditor.; Chianese Angelo guestEditor.; Jung Jason J. guestEditor.
• Is Part Of: Concurrency and computation. Volume 29:Number 11(2017)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2016-12-08
• Subjects: ambient assisted living -- cloud computing -- health monitoring systems -- internet of things (IoT); Parallel processing (Electronic computers) -- Periodicals; Parallel computers -- Periodicals; 004.35
• DOI: 10.1002/cpe.4043
• Languages: English
• ISSNs: 1532-0626

Abstract

Summary: Ambient Assisted Living (AAL) main goal is the development of health monitoring systems for patients with chronic diseases and elderly people through the use of body, home, and environmental sensors that increase their degree of independence and mobility. A comprehensive software infrastructure for AAL systems should be able to cover scenarios involving several patient mobility levels, locations, and physical and cognitive abilities. Cloud computing can provide to AAL systems the ability to extend the limited processing power of mobile devices, but its main role is to integrate all stakeholders through the storage and processing of health data and the orchestration of healthcare business logic. On the other hand, the Internet of Things (IoT) provides the ability to connect sensors and actuators, integrating and making them available through the Internet. This paper presents the Mobile‐Hub/Scalable Data Distribution Layer, a middleware for AAL based on cloud computing and IoT. We discuss how this middleware can handle the requirements of the main health monitoring scenarios and present results that demonstrate the ability to opportunistically discover and connect with sensors in a timely manner and the scalability necessary for handling the connection and data processing of many connected patients.