Towards Sustainable Computing through Ambient Intelligence J.UCS Special Issue

Ambient Intelligence (AmI) represents a new generation of user-centred computing environments aiming to find new ways to obtain a better integration of information technology in everyday life devices and activities. On the other hand, Ambient Assisted Living (AAL), is an important application domain of AmI that aims to contribute with ICT research applied to enabling assistive living environments. AmI environments are integrated by several autonomous computational devices of modern life ranging from consumer electronics to mobile phones. Ideally, people in an AmI and AAL environments will not notice these devices, but they will benefit from the services they provide them. Such devices are aware of the people present in those environments by reacting to their gestures, actions and context. Recently the interest in Ambient Intelligence Environments has grown considerably due to new challenges posed by society, giving place to new interesting associated research disciplines such as Intelligent Transport, Ambient Assisted Living (AAL), e-Health, Internet of Things, Sustainable Computing and Smart Cities among others. The main focus of this special issue is to explore how Ambient Intelligence can contribute towards Smarter but still more Sustainable Environments (e.g. Smart Cities, Smart Cars, Eco-aware devices and so on). Consequently, a selection of papers addressing key aspects about Sustainability, particularly, but several other key areas and domains within AmI such Smart Environment Configuration, Activity Recognition within Ambient Assisted Living and Ambient Assisted Learning are included. These papers were subjected to additional rounds of anonymous reviews. The revised versions of the selected papers are included in this special issue, covering topics such as the need for minimal use of computation, storage and energy in the Internet of Things powered environments, how mobile devices and public displays may aid in the coordination and orchestration of surrounding smart objects, how ontologies can be used to help further automatizing Smart Environments and to enhance composite activity recognition or how learning can also be enhanced by smarter objects and environments.