Editorial: Inaugural issue

Abstract

“Ambient Intelligence (AmI)” is a rapidly growing multi-disciplinary field allowing many areas of research to converge towards having a real beneficial influence in our society. The basic idea behind AmI is that by enriching an environment with technology (sensors, processors, actuators, information terminals, and other devices interconnected through a network), a system can be built such that based on the real-time information gathered and the historical data accumulated, decisions can be taken to benefit the users of that environment. AmI can be succinctly defined as “A digital environment that proactively, but sensibly, assists people in their daily lives” [2]. AmI is aligned with the concept of the disappearing computer: “The most profound technologies are those that disappear. They weave themselves into the fabric of everyday life until they are indistinguishable from it”, wrote Mark Weiser, one of the founders of the ubiquitous computing field [14,15]. Technology available today is rich. Several artifacts and items in a house can be enriched with sensors to gather information about their use and in some cases even to act independently without human intervention. Some examples of such devices are electro-domestic appliances (e.g., cooker and fridge), household items (e.g., taps, bed and sofa) and temperature handling devices (e.g., air conditioning and radiators). Expected benefits of this technology can be: (a) increasing safety (e.g., by monitoring lifestyle patterns or the latest activities and providing assistance when a possibly harmful situation is developing), (b) comfort (e.g., by adjusting temperature automatically), and (c) economy (e.g., controlling the use of lights). This abundance of technology has given place to the new notion of “Smart Environments (SmE)”, which refers to environments that sense, perceive, interpret, project, react to, and anticipate the events of interest and offer services to users accordingly. Areas of application extend from homes to offices, shopping malls, factories, roadways, and to novel applications in multimedia and gaming. Although Ambient Intelligence and Smart Environments are strongly related, we can distinguish them by going back to the old “mind/brain” metaphor used in Artificial Intelligence. While AmI is more concerned with the specific techniques to make an environment behave intelligently, SmE is more related to the intelligent interconnection of resources and their collective behavior. In other terms, while SmE aims to deal with the design of systems reactive and responsive to events, AmI also incorporates mechanisms for learning user preferences and behavior models over time. AmI and SmE share many common objectives and it is often difficult to separate them from each other. This is evident in the composition of topics in related conferences taking place around the world as these events attract interesting research in both areas. Such interconnection is reflected in the creation of JAISE, a journal addressing both areas. One of the most popular instantiations of these areas is the concept of smart homes. Recent applications include the use of smart homes to provide a safe environment where people with special needs can have a better quality of life. For example, in the case of people at early stages of senile dementia (the most frequent case among the elderly suffering from Alzheimer’s disease) the system can be tailored to minimize risks and ensure appropriate care at critical times by monitoring activities, diagnosing situations of interest and advising the carer. There are numerous ongoing academic research projects with well established smart homes research labs in this area, see for example Domus [13], MavHome [5], and Gator Tech Smart Home [8] in the US. The iDorm project [7] in the UK is another example, while many countries in the western half of Europe have smart home related programs (too many to list them all here). There are also many smart home Journal of Ambient Intelligence and Smart Environments 1 (2009) 1–4 DOI 10.3233/AIS-2009-0011 IOS Press