Abstract
Abstract
The numerous applications of internet of things (IoT) and sensor networks combined with specialized devices used in each has led to a proliferation of domain specific middleware, which in turn creates interoperability issues between the corresponding architectures and the technologies used. But what if we wanted to use a machine learning algorithm to an IoT application so that it adapts intelligently to changes of the environment, or enable a software agent to enrich with artificial intelligence (AI) a smart home consisting of multiple and possibly incompatible technologies? In this work we answer these questions by studying a framework that explores how to simplify the incorporation of AI capabilities to existing sensor-actuator networks or IoT infrastructures making the services offered in such settings smarter. Towards this goal we present eVATAR+, a middleware that implements the interactions within the context of such integrations systematically and transparently from the developers’ perspective. It also provides a simple and easy to use interface for developers to use. eVATAR+ uses JAVA server technologies enhanced by mediator functionality providing interoperability, maintainability and heterogeneity support. We exemplify eVATAR+ with a concrete case study and we evaluate the relative merits of our approach by comparing our work with the current state of the art.
Publisher
Springer Science and Business Media LLC
Cited by
9 articles.
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