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A comprehensive and scalable middleware for Ambient Assisted Living based on cloud computing and Internet of Things
Author(s) -
Gomes Berto de Tácio Pereira,
Muniz Luiz Carlos Melo,
Silva e Silva Francisco José,
Ríos Luis Eduardo Talavera,
Endler Markus
Publication year - 2016
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.4043
Subject(s) - cloud computing , computer science , scalability , middleware (distributed applications) , orchestration , the internet , distributed computing , computer security , world wide web , database , operating system , art , musical , visual arts
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.