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Sensor web systems, cyber-physical systems, and the so-called Internet of Things are concepts that share a set of common characteristics. The nature of such systems is highly dynamic and very heterogeneous and issues such as interoperability, energy consumption, or resource management must be properly managed to ensure the operation of the applications within the required quality of service level. In this context, base technologies such as component based software engineering or Service Oriented Architecture can play a central role. Model driven development and middleware technologies also aid in the design, development, and operation of such systems. This paper presents a middleware solution that provides runtime support for the complete lifecycle management of a system consisting of several concurrent applications running over a set of distributed infrastructure nodes. The middleware builds up on top of a general purpose component model and is driven by a quality of service aware self-configuration algorithm that provides stateful reconfiguration capabilities in face of both internal (application triggered) and external (application unaware) reconfiguration events. The platform has been deployed over an automated warehouse supervision system that serves as a case study.

In this paper, we propose a motion-path based gesture recognition technique and show its application in a smart home environment. Users hand gestures are recognized by capturing the motion-path while they draw different symbols in the air. In order to capture the motion-path, we use infra-red camera's IR sensing capability. The IR camera tracks the infra-red emitter attached to the user's hand gloves and produces a sequence of motion-points, which are then analyzed syntactically to recognize the intended hand gesture. The recognized gesture is used to interact with the intelligent environment for accessing various services. Toggling a lamp switch, changing the light intensity, and playing/pausing a movie are few examples where we have integrated the gesturebased interaction. Our experiment shows that the proposed gesture recognition technique is robust and its use in the smart home environment is interesting and appealing to the people.

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