ABSTRCT
Ambient Intelligence aims to enhance the way people interact with their environment to promote safety and to enrich their lives. A Smart Home is one such system but the idea extends to hospitals, public transport, factories and other environments. The achievement of Ambient Intelligence largely depends on the technology deployed (sensors and devices interconnected through networks) as well as on the intelligence of the software used for decision-making. The aims of this seminar are to describe the characteristics of systems with Ambient Intelligence, to provide examples of their applications and to highlight the challenges that lie ahead, especially for the Software Engineering and Knowledge Engineering communities. In particular we address system specification and verification for the former and knowledge acquisition from the vast amount of data collected for the latter.
INTRODUCTION
The steady progress in technology has not only produced a plethora of new devices and devolved computing power into many aspects of our daily lives; it is also driving a transformation on how society relates to Computer Science.
The miniaturization process in electronics has already made available a wide range of embedded computing devices which can now help us when we wash clothes and dishes, cook our meals, and drive our cars. Inspired by those successful applications technological developments, such Radio-Frequency Identification (RFID) technology, which can be used to identify, locate and track tagged items or people, in association with personal area networking protocols may be enablers to deliver ubiquitous computing to all aspects of our lives. These research developments are rapidly exploited by global enterprises, through the process of knowledge transfer, promoting ‘globalization’ of technology. (Want. 2004.)
This growth in technology and computing power has been continuously progressing since the very inception of Computer Science, and is exemplified by Moore’s Law (Augusto, 2006), which accurately predicted the doubling of the number of transistors on integrated circuits every 18 months. Consider the historical perspective. Initially a large mainframe machine was shared by many highly Juan Carlos Augusto and Paul McCullagh trained programmers located in a secure environment restricted to specialist researchers. The computer then became an essential tool for many nonscientific academic disciplines, exemplified by departmental mini computers.
As cost fell and power and storage increased, the computer was embraced by industry, hospitals, and governments. More recently office workers, not necessarily with a high level of training, gained access to a personal computer on the desktop. Nowadays in the developed world, most people have access to an array of mobile computing devices including laptop, mobile phone, personal data assistant (PDA) and interact with processing units embedded in electro-domestic appliances, such as DVD players, television set-top boxes, cookers and microwave ovens. Visionary opinion indicates that the trend for accelerating device sophistication, driven by intelligent sensors and smaller and more powerful processing elements will continue for the next 10-20 years (Harper, 2005.).
However it is possible to recognize a paradigm shift. Systems are being designed in such a way that people do not need to be a computer specialist to benefit from computing power, and indeed intuitive graphical interfaces have been augmented by voice interaction, and multi-modal interfaces where virtual objects (in a virtual world) can be moved by ‘hand’ using an enriched glove. Ambient intelligence has adapted to provide a wireless and more intuitive interface.
Protocols such as Bluetooth and Zigbee have removed the need for physical connection. This technical possibility is being explored in an area called Ambient Intelligence where the idea of making computing available to people in a non-intrusive way, minimizing explicit interaction is at the core of its values. The aim is to enrich specific places such room, building, car, street with computing facilities which can react to peoples’ needs and provide assistance.
People are now more willing to accept technologies participating and shaping their daily life. Today’s teenagers are part of the “Net” Generation, brought up within a world of computers, mobile phones and the Internet with little fear of technology and in fact embracing the latest electronic hi-tech advances. At the same time there are important socio-economic and political driving forces. An important example of this is the move towards decentralization of health care and development of health and social care assistive technologies for independent living. The electronic health (e-Health) paradigm (ay Kurzweil, 2001) moves the citizen away from the hospital-centric health care system, hastening this shift of care from the secondary and tertiary care environments to primary care. Subsequently, there is an effort to move away from the traditional concept of patients being admitted into hospitals (which are potentially dangerous places due to the potential for cross-infection) rather to enable a more flexible system whereby people are cared for closer to home, within their communities. Smart Homes are one such example of a technological development which facilitates this trend of bringing the health and social care system to the patient as opposed to bringing the patient into the health system.
Definition of Ambient Intelligence
Philips Research introduced Ambient Intelligence(AmI) in the year 1998. In 2001, AmI was taken up by The European Commission’s Information Society Technologies Advisory Group (ISTAG). In computing, AmI refers to electronic environments that are sensitive and responsive to the presence of people. Ambient intelligence is a vision on the future of consumer electronics, telecommunications and computing for the time frame 2010–2020.
The development of ambient intelligence applications that effectively adapt to the needs of the users and environments requires the presence of planning mechanisms for goal-oriented behavior. A planning system for AmI applications is based on the hierarchical task network (HTN) approach and is called distributed hierarchical task network (D-HTN). D-HTN is able to find courses of actions to address given goals. The application areas of AmI include health-related applications, public transportation sector, education services etc. This seminar aims to give an insight into ambient intelligence technology and a planner for AmI applications
Introduction of Ambient Intelligence
Ambient Intelligence (AmI) is a new paradigm in Information Technology that has potential for great impact in the future. The vision of AmI is that the people will be surrounded by intelligent objects that can sense the context and respond according to the desire of the people. AmI is a multidisciplinary topic, since it combines the features of many of the areas in Computer Science.
In the last five years, we have seen significant advances in three promising technology areas: virtual environments, in which 3D displays and interaction devices immerse the user in a synthesized world, mobile communication and sensors, in which increasingly small and inexpensive terminals and wireless networking llow users to roam the real world without being limited to stationary machines. The merging of these areas allows the emergence of a new vision: the Ambient Intelligence (AmI).
AmI refers to a digital environment that proactively, but sensibly, supports people in their everyday lives. It will make the feeling that the people live with technology. It is aligned with the concept of ‘disappearing computer’, since the AmI environment make the technology invisible. As the devices grow smaller, more connected and more integrated into our environment, the technology disappears into our surroundings.“The most profound technologies are those that disappear. They weave themselves into the fabric of everyday life until they are indistinguishable from it.” M. Weiser The basic idea behind AmI is that by enriching an environment with technology (mainly sensors and devices interconnected through a network), a system can be built to take decisions to benefit the users of that environment based on real-time information gathered and historical data accumulated.
An important aspect of AmI has to do with interaction. On one side there is a motivation to reduce the human-computer interaction as the system is supposed to use its intelligence to infer situations and user needs from the recorded activities, as if a passive human assistant was observing activities unfold with the expectation to help when (and only if) required. On the other side, a diversity of users may need or voluntarily seek direct interaction with the system to indicate preferences and needs. The entire environment around us, homes and offices, cars and cities, will collectively develop a pervasive network of intelligent devices that will cooperatively gather, process and transport information
Key Technologies:
The benefit of an AmI system is measured by how much can give to people while minimizing explicit interaction. The aim is to enrich specific places (a room, a building, a car, a street) with computing facilities which can react to people’s needs and provide assistance. In order for AmI to become a reality a number of key technologies are required:
· Unobtrusive hardware (Miniaturisation, Nanotechnology, smart devices, sensors etc.)
· Seamless mobile/fixed communication and computing infrastructure (interoperability, wired and wireless networks, service-oriented architecture, semantic web etc.)
· Dynamic and massively distributed device networks, which are easy to control and program (e.g. service discovery, auto-configuration, end-user programmable devices and systems etc.).
· Human-centric computer interfaces (intelligent agents, multimodal interaction, context awareness etc.)
· Dependable and secure systems and devices (self-testing and self repairing software, privacy ensuring technology etc.)
APPLICATIONS OF AMBIENT INTELLIGENCE
The range of possible applications for Ambient Intelligence and Smart Environments is vast and we can look at the future of the area with expectation and hope that it will bring to everyday life a range of available solutions. Here we list some emerging applications driven by the demand of users, companies and governmental organizations:
1 SUMMARY
Patience and sustained work will be needed to extend the technical frontiers of this area bit by bit. To what extent these technologies will be taken by society it is to be discovered, meanwhile the potential benefits are such that it is worth trying. Researchers and developers should remember at all times that users are at the center and that technology should be built for them.
The idea of a future home equipped with technical devices that reduce burdens and make life easier is an old one. What is new with ambient intelligence in this idea, is the added value of transparency and interactivity. As Aarts and Marzano (2003) put it, paradoxically the home of tomorrow will look more like the home of yesterday than the home of today. The bulky technological devices will fade into the background and be embedded into surfaces and ornaments.
4.2 CONCLUSION
There are great opportunities for ambient intelligence in housing: people spend a lot of time in their homes and both social and technological drivers are broadening the scope of activities to be undertaken at home. Solutions similar to the ones already developed for cars can be applied to housing. Consumer electronics, by having already gained a strong foothold in housing, can be at the forefront of ambient intelligence.
However, there are some critical aspects and serious challenges concerning the development of ambient intelligence in the field of housing. Home is a sanctuary, so technology and technological devices integrated to the house should not dominate the overall function of housing. The technology should enhance the quality if life of residents, not only by facilitating their daily activities, but also supporting their socialisation.
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