Active In-Database Processing to Support Ambient Assisted Living Systems
2014 (English)In: Sensors, ISSN 1424-8220, Vol. 14, no 8, 14765-14785 p.Article in journal (Refereed) Published
As an alternative to the existing software architectures that underpin the development of smart homes and ambient assisted living (AAL) systems, this work presents a database-centric architecture that takes advantage of active databases and in-database processing. Current platforms supporting AAL systems use database management systems (DBMSs) exclusively for data storage. Active databases employ database triggers to detect and react to events taking place inside or outside of the database. DBMSs can be extended with stored procedures and functions that enable in-database processing. This means that the data processing is integrated and performed within the DBMS. The feasibility and flexibility of the proposed approach were demonstrated with the implementation of three distinct AAL services. The active database was used to detect bed-exits and to discover common room transitions and deviations during the night. In-database machine learning methods were used to model early night behaviors. Consequently, active in-database processing avoids transferring sensitive data outside the database, and this improves performance, security and privacy. Furthermore, centralizing the computation into the DBMS facilitates code reuse, adaptation and maintenance. These are important system properties that take into account the evolving heterogeneity of users, their needs and the devices that are characteristic of smart homes and AAL systems. Therefore, DBMSs can provide capabilities to address requirements for scalability, security, privacy, dependability and personalization in applications of smart environments in healthcare.
Place, publisher, year, edition, pages
Basel: Multidisciplinary Digital Publishing Institute AG , 2014. Vol. 14, no 8, 14765-14785 p.
healthcare technology, smart homes, ambient assisted living, database management systems, active databases, in-database processing, data mining
Electrical Engineering, Electronic Engineering, Information Engineering
IdentifiersURN: urn:nbn:se:hh:diva-26238DOI: 10.3390/s140814765ISI: 000341499900073OAI: oai:DiVA.org:hh-26238DiVA: diva2:737561
This article belongs to the Special Issue Select Papers from UCAmI & IWAAL 2013 - the 7th International Conference on Ubiquitous Computing and Ambient Intelligence & the 5th International Workshop on Ambient Assisted Living (UCAmI & IWAAL 2013: Pervasive Sensing Solutions2014-08-132014-08-132016-03-09Bibliographically approved