This paper leverages previous work on the concept of smart object federations and proposes a new dynamic programming language for implementing and simulating smart objects and their interactions. Following their description in the proposed programming language, smart objects can be fully simulated and used for describing ambient intelligence scenarios. In this context, the contributions of the paper are two-fold: (a) the introduction of a new programming language whose runtime semantics allows for a simple and effective description of smart objects, and (b) the description of meaningful interaction strategies, that are implemented in the proposed language, through which executable smart object federations can be used for simulating and implementing ambient intelligence scenarios.
In this paper we describe a novel methodology for performing real-time analysis of localization data streams produced by sensors embedded in ambient intelligence (AmI) environments. The methodology aims to handle different types of real-time events, detect interesting behavior in sequences of such events, and calculate statistical information using a scalable stream-processing engine (SPE) that executes continuous queries expressed in a stream-oriented query language. Key contributions of our approach are the integration of the Borealis SPE into a large-scale interactive museum exhibit system that tracks visitor positions through a number of cameras; the extension and customization of Borealis to support the types of real-time analysis useful in the context of the museum exhibit as well as in other AmI applications; and the integration with a visualization component responsible for rendering events received by the SPE in a variety of human readable forms.
Ambient Intelligence is an emerging research field that aims to make many of the everyday activities of people easier and more efficient. This new paradigm gives rise to opportunities for novel, more efficient interactions with computing systems. At a technical level, the vision of Ambient Intelligence is realized by the seamless confluence of diverse computing platforms. In this context, a software framework (middleware) is essential to enable heterogeneous computing systems to interoperate. In this paper we first consider the basic requirements of a middleware that can effectively support the construction of Ambient Intelligence environments. Subsequently, we present a brief survey of existing, general-purpose middleware systems and evaluate them in terms of their suitability for serving as the low-level communication platform of an Ambient Intelligence middleware. Finally, we argue that an Object-Oriented middleware such as the Common Request Broker Architecture (CORBA) is most suited for basing a middleware for Ambient Intelligence environments.