What are Ambient Intelligent Systems?
How integrated services can deliver a more inclusive society
Society is undergoing a fundamental transition, from the present industrial society towards an information society. Among the possible embodiments of the emerging information society, an interesting and widely discussed potential instantiation is the Ambient Intelligence (AmI) paradigm. The information society is not seen as being characterised by an increased diffusion and use of present-day computers and telecommunication terminals, but as the emergence of an environment in which people are surrounded by fixed and mobile intelligent objects, interconnected through fixed and mobile networks, and an environment capable of recognising and responding to the presence of different individuals. The interaction with the objects and with the intelligence in the environment will allow access to information, interpersonal communication and environmental control.
The AmI environment will be populated by a multitude of hand-held and wearable ‘micro-devices’ and computational power and interaction peripherals (eg embedded screens and speakers, ambient displays) will be distributed in the environment. Devices will range from ‘personal’ (eg wrist-watches, bracelets, personal mobile displays and notification systems, health monitors embedded in clothing), carrying individual and possibly private information, to ‘public’ in the surrounding environment (eg wall-mounted displays). As technology ‘disappears’ to humans both physically and mentally, devices will be no longer perceived as computers, but rather as augmented elements of the physical environment. Personal devices will be equipped with facilities for multimodal interaction and alternative input/output (eg voice recognition and synthesis, pen-based pointing devices, vibration alerting, touch screens, input prediction), or with accessories that facilitate alternative ways of use (eg hands-free kits), thus addressing a wider range of user and context requirements than the traditional desktop computer.
A variety of new products and services will be made possible by the emerging technological environment, including home networking and automation, mobile health management, interpersonal communication, and personalised information services. These applications will be characterised by increasing ubiquity, nomadism and personalisation, and are likely to pervade all daily human activities. They will have the potential to enhance security in the physical environment, save human time, augment human memory and support people in daily routines and simple activities, as well as in complex tasks.
This development is potentially very promising for users. According to European development scenarios, from a socio-economic perspective ambient intelligence is supposed:
- to facilitate human contacts;
- to be oriented towards community and cultural enhancement;
- to help to build knowledge and skills for work, better quality of work, citizenship and consumer choice;
- to inspire trust and confidence;
- to be consistent with long-term sustainability - personal, societal and environmental - and with life-long learning;
- to be controllable by ordinary people. Moreover, from a human-computer interaction
perspective, interaction with the intelligent environment will have to be redefined.
Namely, the ambient intelligence environment must be unobtrusive (ie many distributed devices are embedded in the environment, and do not intrude into our consciousness unless we need them), personalized (ie it can recognize the user, and its behaviour can be tailored to the user’s needs), adaptive (ie its behaviour can change in response to a person’s actions and environment), and anticipatory (ie it anticipates a person’s desires and environment as much as possible without the need for mediation). Therefore, the emphasis is put on greater user-friendliness, more efficient support of services, user-empowerment, and support for human interaction. Interaction is intended as taking place through ‘natural’ interfaces.
However, integration within the AmI environment is complex, due to the interplay of its different levels, eg the physical level with a multiplicity and heterogeneity of intelligent objects and their need for a continuous and high-speed connection, the level of identification and consideration of the variety of contexts of use, and the level of elicitation of the diversity of user goals and help in their fulfilment. The system must be able to seamlessly integrate the three levels considered above. At the lower level, all intelligent objects in the environment must be interconnected and able to cooperate in order to support the goals of the user. Moreover, the environment must be reconfigurable in real time, to cater for the introduction or removal of components (for example, objects that users entering the environment may have with them). At a higher level, the AmI environment must take care of the contexts of use considered as processes, which are defined by specific sets of situations, roles, relations, and entities.
In the foreseen ubiquitous interaction with information and telecommunication systems the context of use may change continuously or abruptly and the same systems or services may need to behave differently in different contexts. Finally, it must be considered that most of the interaction with currently available systems is based on the performance of tasks determined by the application used. In the intelligent environment, the goals of the user are the starting point. They must be inferred by the system and decomposed into tasks that are adapted to the preferences of the individual. Therefore, the environment must not only be filled with intelligent objects (that is, computer-based systems), but must also be able to reason with regard to the goals of the users.
Therefore the acceptability and uptake of the new paradigm will be dependent on a design that facilitates the system in inferring the goals of the users in the continuously varying contexts of use and in organising the available resources in order to help users to fulfil them in a psychologically acceptable way. From this perspective, for example, the system must be able to deal with the task of inferring the goals of the users without giving them the impression that they are under control (big brother), and must be able to support the users without giving them the impression that they are forcing them. It must ‘offer’ possible solutions, not ‘impose’ them. This requires a lot of ingenuity also on the part of human beings, and appears particularly difficult for a machine.
| 0.4% | Wheelchair users | 1.0% | Dyslexic | |
| 5.0% | Cannot walk without an aid | 3.0% | Intellectually impaired | |
| 2.8% | Reduced strangth | 0.1% | Deaf | |
| 1.4% | Reduced co-ordination | 6.0% | Hard of hearing | |
| 0.3% | Speech impaired | 0.4% | Blind | |
| 0.6% | Language impaired | 1.5% | Low vision |
Approximate proportion of the population who have disabilities which are likely to affect their use of ambient intelligent systems (NB Do not aggregate the figures since multiple impairments are common).
Last updated: 20.11.2009 © Copyright reserved Website design: Digital Accessibility Team