A delicate balance of the combination of those principles listed above is fundamental for this technology to thrive and to gain widespread acceptance. If a system overwhelms the user offering help, or delivers the wrong assistance or at a time or mode the user does not want it then users will soon get tired and switch the system off.
Human assistants are capable to balance all these aspects, some more successfully than others and on that basis they are appreciated or not. Artificial systems should aim to master the subtle skills that distinguish successful human assistants and make them acceptable companions [ 11 ]. We explain below how these areas contribute to the realization of Intelligent Environments.
There is a wide range of sensors with varying capabilities, allowing the measurement of [ 12 , 13 ], for example:. There is no single formula to combine sensors in an environment for a specific problem and current developments arrange them in an ad hoc manner to suit a specific application. Networks and Middleware: each intelligent environment has usually a variety of distributed sensors which helps to understand the current status of the environment.
This flow of data is channelled to the main system through a wired or wireless network. This process presents the first set of major challenges to the system designers: how to merge in real-time all the influx of information, how to cope with incomplete or corrupt information coming from malfunctioning sensors, how to present the information in a way that can be useful to other higher decision-making modules of the system, and how to manage a huge number of devices and sensors?
One important task typically assigned to the middleware layer of a system is to facilitate interoperability, that is, help parts of the system devices, network, etc. There is still much work to do in this area as there is no standard middleware, i. This paradigm explores the development of systems which departs from the desktop PC centred paradigm and supports a shift towards a model that follows the user where it goes, transparently across different physical locations. This paradigm is related to user-centred computing and highlights the value of concepts like Context-awareness [ 15 ], the capability of a system to understand the current situation in the environment, to keep tracks of its evolution and to relate this knowledge to modules within the system that produces proactive reactions.
Artificial Intelligence: Autonomous decision-making is one of the implicit expectations about any intelligent environment, they are precisely deployed to provide services in a similar way other humans will decide to provide in the same circumstances. To achieve this autonomous decision-making capability, systems will usually apply AI techniques which allow them to perform:.
A variety of methods exist here, ranging from systems which are more rule-based to those based in biologically inspired models [ 17 ]. This independence is needed at all levels, from assisting the users, to energy preservation and other internal decision which are more related to ensuring delivery of service, for example, self-reconfiguration and self-healing [ 18 , 19 ]. Relevant to these intelligent systems is the use of a Multiagent systems provides a flexible paradigm to model the different levels of autonomy and dependency that each component can have in a Smart Environment [ 21 — 23 ], and b Robots: providing a valuable tool both as an interface and as an actuator within a smart environment.
Robots can provide an element of socialization [ 24 ]. They can also be disguised in the way of a tool that users can benefit from like an intelligent wheelchair which can help navigate a house to users with mobility challenges [ 25 ]. Humans should be able to use devices in a way that does not demand vast amounts of training and specialization, needless to say, most of what it is on offer today in the areas of AmI and SmE fall short of this expectation.
It is also fair to say that there is a significant part of the community which is doing interesting progress and is working extremely hard to overcome limitations in this area. Gesture recognition [ 26 ], gaze tracking [ 27 ], facial expression recognition [ 28 ], emotion recognition [ 29 ], and spoken dialogue [ 30 ], either isolated or combined to form multi-modal interfaces [ 31 ], are some of a range of options becoming available to facilitate communication between humans and the system in a natural way.
There is a variety of problems that makes Intelligent Environments interesting and at the same time difficult to implement. We try to explain some of them in this section. Users are at the center of Intelligent Environments, in that respect this area overlap with the efforts of the scientific community focused on Person-Centric Computing [ 32 , 33 ]. The system should be able to help people of all ages and educational backgrounds, crucially those who do not have IT knowledge.
This represent the opposite of the predominant philosophy in our area, a mere accumulation of technology will overwhelm users. The introduction of technology has to be sensitive to the user and abide to the principle that the human is the master and the computer the slave and not the other way round [ 34 ]. This principles have been emphasized from the very beginning [ 2 ] highlighting the importance that unobtrusiveness and transparency of these services have for its success.
Intelligent Environments should also be aware of and be sensitive to multiple users in the same environment. These multiple users may coexist, may be interacting, may be cooperating, or may even be conflicting interests. Systems also have to be resilient enough to cope with users which will try to use the system in unexpected ways and with the richness and variability of human's behaviour on a daily basis. The spaces where these systems can be deployed are very diverse. There are closed spaces with relatively well defined boundaries and others which do not have well defined boundaries which we can call open spaces.
All of them can be roughly defined by the area physical space that the sensors can sense. Examples of closed spaces are: houses, offices, hospitals, classrooms, and cars. Examples of open spaces are: streets, bridges and car parks for example for surveillance , fields for agriculture , air for airplanes and sea for underwater pollution measurement and tsunami early warning system.
These environments are usually rich, complex, unpredictable, possibly generating substantial 'noisy' data, unstructured and sometimes highly dynamic i. All intelligent environments are embedded in a world they have to act upon. The understanding the system has of the environment where is operating is directly proportional to the quantity and quality of its perceptive capability. In current systems that amounts to the sensing network that is connected to.
This sensing network informs but at the same time oversimplifies reality. The impact of the sensing network in an intelligent environment is huge. The intelligent system at the core of an Intelligent Environment base most of its decision-making on the perceived current situation which is composed out of the information perceived in real-time through the sensors.
Sensors allow the system to perceive what happens in a place without a human being necessarily being there.
But how accurate and useful this perception is? We are able to see part of the landscape around us, but we do not see all objects, we see some objects partially occluded and we see others in their entirety but fuzzy. To illustrate the practical implications of this impoverished depiction of reality that sensors bring to the system let us compare them with the richest sensing machine we know: humans. A pressure sensor can sense whether there is certain weight over it, so we can put it on a chair or a sofa and use it to sense whether someone is sitting but that information alone will not tell us univocally whether there is a person or a dog on the sofa and if we know a person is there we do not know whether the person is awake or has fainted.
So often several sensors have to be combined in order to support the accurate understanding of a simple aspect of reality. This however will still have a cost and require such computational skills to process the rich input which very few can afford and which, despite constant progress in the area, is far from being accessible to the masses. At the same time, the richer the more information a device can extract per time unit, the more invasive and resisted on privacy grounds. Opposing forces, each one pulling in a different direction, the resulting system is a compromise of these.
The next section explains how people working in this area applies all the knowledge gained through decades of advances in different fields of Computer Science to allow a system to understand as best as possible an environment and provide valuable decision-making to benefit people that interacts with that environment. 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:. They can also increase safety by, for example, only allowing authorized personnel and patients to have access to specific areas and devices. Health can be decentralized and made accessible at home through telecare and telehealth services in what it is commonly termed Ambient Assisted Living [ 36 — 38 ].
Transport is already benefiting from technology including satellite services, GPS-based spatial location, vehicle identification, image processing and other technologies to make transport more fluent and hence more efficient and safe. This progress is starting to emerge in the form of Smart Cars and Smart Road Network infrastructure [ 39 , 40 ].
Education-related institutions may use technology to create smart classrooms where the modes of learning are enhanced by technology that support students and lecturers inside and outside the classroom [ 41 ]. Companies can use RFID sensors to tag different products and track them along the production and commercialization processes.
IEEE EUC 2018 – 16th International Conference on Embedded and Ubiquitous Computing
This allows identifying the product path from production to consumer and helps improving the process by providing valuable information for the company on how to react to favourable demand and unusual events like products that become unsuitable for sale [ 42 ]. They have been also the centre of attention and some interesting proposals aim at equipping offices with ways to assist their employees to perform their tasks more efficiently [ 43 , 44 ]. Part of the marketing implied they will provide a more efficient managing of those resources.
People worldwide is taking those issues much more seriously today and Intelligent Environments can be one important instrument to achieve those goals [ 46 ]. Many houses contain now a wide range of devices to provide entertainment and fun for a diversity of ages. The sophistication of these games can be highly enhanced by technology which provides more immersive experiences, an important feature in modern gaming [ 47 ].
During the last decade or so, this area has increasingly attracted interest, effort and resources. Still the complexities associated with the limitations of the technological infrastructure and its relation to the variety of humans they are supposed to serve is considerable. Below we try to explain the dimension of this gap through some features which can make a substantial difference on technology adoption. An intelligent environment needs to made decisions that benefit the environment inhabitants. Naturally, the decision needs to take into account the context of the current situation.
Computationally, context may refer to network connectivity, communication costs, and resource availability. The environment context may capture internal features such as lighting and temperature levels as well as the current state outside the environment. Also important, time context includes the hour of the day, day of the week, season, and year [ 48 ]. By combining heterogeneous sources of information including the user location, automatically-recognized activity, and online information e.
While context-awareness is crucial for intelligent environments to provide effective decisions and actions, a danger is focusing on a too narrow understanding of the context recognition problem. Sensor data fusion techniques can combine disparate sources of information into a concise, usable contextual description [ 49 ]. An intelligent environment should seamlessly adapt to changing context or behaviors at an individual, social group, or community level. Intelligent environments deal with massive amounts of data and highly complex situations.
As a result, they also need to make decisions based on insufficient, incomplete and noisy data samples. Preferences e. On one side it will be unpractical to design each system from scratch in an ad hoc manner for each person, on the other hand, a "one size fits all" approach to Intelligent Environment development will clearly not address all specific preferences and needs of each user.
One option ahead is to create a generic system and then to personalize it, ideally the system should have a learning system which can learn how to serve the user better. However, the capability of the system to recognize, learn and update preferences and needs dynamically is a crucial problem still to be tackled.
Related to the problem described above is the problem of how the system can obtain an updated understanding of the preferences and needs of a user at any given moment. Some users may not be willing to speak to the system or to use any keyboard or device to explicitly indicate that the current situation e. Is there any way a system can understand whether the user is in more of a receptive or introverted mood?
Can for example, the activities performed in the last hour and the way they were performed e. So far all these research is reporting some moderated success on achieving specific technical goals [ 50 — 53 ] but they have not yet been used in a holistic and comprehensive manner that is meaningful to the field and to a real practical e. Working with one user has proved difficult enough to produce reliable affordable systems capable to serve a person.
Some advances have been made and some prototypes have been deployed and are currently being tested but it is clear there is still a long way to go. Things get more difficult when the system is supposed to deliver differentiated services to more than one user in the same environment. The first problem is identifying each one of the users at all times.
Current technology is such that univocally identifying a person is proportional to the cost and complexity of the identification mechanisms. Let us assume the user wears an ID tag which can be read by a device approaching meaningful points like doors or objects of daily use. This imply the replication of reading devices all along the house to know where the user is and to deliver meaningful services according to the context e.
This still leave us with the problem that each user may confuse the tags and the system will deliver services to the wrong person. Other technologies can be used, e. An intelligent environment can rely on these biometric approaches to identifying individuals in a space. An alternative approach is to draw from behaviometrics. In this case the environment performs identification by recognizing the movement or behavioral patterns that are typically associated with a specific individual.
Using behavior to classify individuals into groups e. Designing intelligent environments to make the same kind of prediction is a natural extension of sensor-based systems [ 54 ]. Another typical problem arising when more than one user co-exist in an environment is described in the next section. Humans have lot in common but it is very difficult to find two human beings with exactly the same preferences and needs.
Whether it is on T. How the system should react to those situations? What happens when all alternatives to reach an agreement fail, will the system give priority to one human, based, for example, on a social hierarchy? Intelligent Environments are designed to assist and support people, in some cases are intended to take care of people in vulnerable situations, the potential for disaster when a system fails is high. Assuming systems should be developed to perfection is naive, companies are decided to exploit this market and the best we can do is to create and make available methodologies and tools that can be easily incorporated to the development process facilitating adoption by industry.
There are reports which eloquently explain how the complexity of the software needed to govern these systems can easily develop hidden complex interactions which create instability within the behaviour of the system [ 56 ]. Doing nothing and passing the responsibility to the user which usually is not technically prepared to thoroughly assess what is being installed in an environment is unethical. This is an aspect our community should take very seriously given the potential to harm other humans.
Software Engineering has been working on these areas for long but the systems we consider here have a mix of sensors, networks, intelligent software, human-computer interfaces and users which makes thorough testing and verification to exceed the complexity traditional techniques and tools can cope with. It is difficult to test context-aware software in comparison with other software, because the former needs to be tested in its target contexts to develop reliable systems.
A solution is to run such software with contexts e. Also, we often need formal methodologies to simulate or verify intelligent environments to confirm whether they can satisfy the specifications. Systems which are designed to serve humans have to do so in a sensitive way. This area which aspires to be so intimately connected with our daily lives has to take this dimension very seriously. The more a system knows about us the more is able to serve us as we would like. The system may know we like chocolate ice cream because we have told the system explicitly or because we allowed the system to infer that from the last two months purchases from the supermarket.
If we have not told the system we hate pistachio flavoured ice cream then the system may one day incur in what we consider a wrong decision. We have discussed above the limitations of simple sensors and how they feed the decision-making modules with a simplified perception of reality. From all the data gathering devices we have available, video cameras are the most successful ones in the sense they provide us with fuller and crisper information about the fragment of the environment they are observing.
Cameras provide more information that is useful but also have the potential to absorve information the user may not like to be captured by a camera. To illustrate the point think about extreme situations like having a camera in your own bathroom or bedroom at home. Sure there are many other situations where cameras can be used and indeed are being used. What is acceptable or not acceptable to share changes enormously with cultural values and the situation being observed.
Some users are happy to give up some degree of privacy in return for increased safety; some humans will never accept a camera recording their daily life activities. Researchers and developers have to work out systems which adapt to the different degrees of sensitivity users may have when blending technology with daily life affairs.
Sensors available in an intelligent environment may be owned and managed by different organizations or people. When such sensors in a space acquire information on targets, e. That is, intelligent environment s tend to have multiple stakeholders. Before using information from intelligent environment s, we must adjust interests among all potential stakeholders. This problem becomes serious when IEs are supported in public spaces, e. Furthermore, we need to limit free riders in intelligent environment s, where a free rider is someone who consumes a resource without paying for it, or pays less than the full cost.
This is an economic problem in the sense that it leads to the excessive use of a common property resource. However, if too many people do this, users cannot be provided with services from intelligent environments. Intelligent environments need mechanisms to limit free riders. On the other hand, when an emergent situation, e. Since intelligent environments become social infrastructures in future, researchers and developers have to solve multiple stakeholder problems, including free rider problems.
Sensors record information about our daily activities and there is technology that can mine the recorded data to extract patterns of behaviour. The idea being that negative behaviours can be indentified and discouraged and positive ones encouraged and reinforced. But what happens if all that private information fall in the wrong hands? There have been many incidents where sensitive digital information from governments and military forces around the world has been forgotten in a pen drive, CD or laptop at an airport or a train.
We can get many unwanted calls per week because a company e. It is not unlikely then that the same can happen to sensitive private data and our habits and illnesses can be accessible to groups of people who are eager to take profit of that knowledge. Both economic and personal safety can be compromised as a result of personal data falling in the wrong hands. As a result, users will become more and more aware of this and extra measures have to be provided to bring peace of mind to the early adopters of this technology. If the market is labeled as unsafe by the users then all those involved will lose a fantastic opportunity to benefit society.
Given the inherent intrinsic complexity of systems of this anture and given the extrinsic complexity of humans expectations from technology, these systems will unavoidably fail from time to time in some way or another. Four first steps are proposed: a A more formal software engineering approach to systems design, b enhanced understanding of human—computer interaction, c a partnership between the technical level and human, d a higher ethical dimension. It is also recognized they are not a solution but only a first step in the right direction.
We have provided an account of a new emerging area, one that can have an important role in a transition towards computing devices supporting our daily life to an extent not experimented before. There are still considerable challenges, which we highlighted above. There are technological limitations both in hardware, which is currently based on limited and unreliable sensors and networks, as well as in software, forced to make good decisions out of a limited perception of reality, and to deal with a number of users with different needs and preferences.
Privacy and safety concerns also have to be carefully considered for these systems to be adopted. At the core of these systems there is a paradox where for us to be served best, the system needs to know more about our daily life, which in turn makes us more vulnerable to system failure. On the other hand there are important benefits for humanity if this technological enterprise succeeds. Also, a scientific point of view it is an interesting catalyst for blending efforts from different areas of Computer Science which have achieved relative success and maturity AI, HCI, communications, etc.
An intelligent environment necessarily needs a multi-disciplinary approach, this includes as well the professional expertise incumbent to the application area, hence a Smart Home to support independent living may require the involvement of social workers, nurses and architects. This is a very interesting source of applications that has an impact on society yet has well defined physical boundaries e. The area is well suited for incremental development, i. Whilst previous AI research was predominantly inspired by challenges that benefited either a few in very specific places e.
Still these applications present reasonable challenges solutions are feasible for the state of the art in a relatively short term and are a new inspiration for CS professionals to produce something tangible for society which still demands ingenuity and responsible development. This is hopefully the era when computing is finally blended in our lives not to benefit the few but the masses, not in rare occasions but continuously.
New York: Prentice Hall; Weiser M: The computer for the 21st century. Early scenario's in Ambient Intelligence envisioned a world in which Ambient intelligence and smart environments: A state of the art free download Advances in the miniaturization of electronics is allowing computing devices with various capabilities and interfaces to become part of our daily life.
Sensors, actuators, and processing units can now be purchased at very affordable prices. This technology can be Combining ongoing Ambient Intelligence AmI technological developments eg pervasive computing, wearable devices, sensor networks etc. Learning the preferences and habits of users then becomes an important step in allowing a system to provide such personalized services. A flexible architecture for ambient intelligence systems supporting adaptive multimodal interaction with users free download Abstract.
Ambient Intelligence AmI systems aim at augmenting real environments to create Smart Spaces where users are provided with pervasive virtual services. In order to allow users to seamlessly complete their tasks across a multitude of smart devices, and across Ambient intelligence for decision making in fire service organizations free download This paper describes the results of the European Project AMIRA Advanced Multimodal Intelligence for Remote Assistance which deals with the support of emergency services in particular fire services by Ambient Intelligence.
We address the problem of mobile decision Using FML and fuzzy technology in adaptive ambient intelligence environments free download Abstract: Ambient Intelligence AmI, shortly gathers best results from three key technologies, Ubiquitous Computing, Ubiquitous Communication, and Intelligent User Friendly Interfaces. The functional and spatial distribution of tasks is a natural thrust to employ multi-agent Presence The emergence of ambient intelligence free download Abstract. 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 This paper presents the results of a study on how elderly people perceive an intelligent system, embedded in their home, which should enable them to live independently longer.
Users of a motion sensor system were interviewed about their experiences.
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A sensor system Towards a reference middleware architecture for ambient intelligence systems free download ABSTRACT Ambient-intelligence AmI systems raise a series of new challenges in software and system development: Mobility, adaptability and heterogeneity are new concerns that have to be addressed. Many of these concerns are common and therefore should be Ambient intelligence for people with disabilities and elderly people free download ABSTRACT Recent advancements experienced by diverse network technologies, such as wireless personal and local area networks and wired networks, interacting with location systems, make possible the development of intelligent environments .
Elderly and Science and technology roadmapping: Ambient intelligence in everyday life AmI Life free download New paradigms in telemedicine: ambient intelligence, wearable, pervasive and personalized free download Abstract.
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After decades of development of information systems dedicated to health professionals, there is an increasing demand for personalized and non-hospital based care. An especially critical domain is cardiology: almost two third of cardiac deaths occur out of On human aspects in ambient intelligence free download This paper briefly outlines the scientific area that addresses Ambient Intelligence applications in which not only sensor data, but also knowledge from the human-directed sciences such as biomedical science, neuroscience, and psychological and social sciences The future of ambient intelligence in Europe: the need for more everyday life free download Abstract: Ambient Intelligence AmI refers to a vision of the future information society where intelligent interfaces enable people and devices to interact with each other and with the environment.
Today, most of the technologies needed for the realisation of this vision are Interacting with the ambience: Multimodal interaction and ambient intelligence free download Abstract. Multimodality allows adaption of human-computer interaction on two different levels: on the one hand different users with different abilities can interact with information technology through a customized configuration of interaction devices supporting their Ambient Intelligence: Beyond the Inspiring Vision.
This vision represents a new generation of user-centred computing environments aiming to find new ways to obtain a In the second half of the 19th century Jules Gabriel Verne, one of the science fiction's founding fathers, wrote his famous novels playing in a world full of technology most of which was unknown yet at that time, but to become reality some years later. Still considered to AmE framework: a model for emotion-aware ambient intelligence free download Abstract. The objective of this paper is to explore human emotional intelligence and to advance research on emotion-aware technology by merging fundamental emotion theories, emotion-aware human-computer interaction, and ambient intelligence.
The final goal is to As sensors and antennas are embeddable in things around us, a new era of physical Internet begins. The revolution is brought by economies of scale and millions of consumers. Today, a music birthday card may have more computing power than a mainframe computer Dynamic service composition in ambient intelligence environments: a multi-agent approach free download Abstract. Ambient Intelligence pushes forward a vision where technology is integrated into everyday objects with the intent of turning the users' surrounding environment into a global and simple interface with information systems.
This vision poses major challenges in Multimodal dialogue for ambient intelligence and smart environments free download Ambient Intelligence AmI and Smart Environments SmE are based on three foundations: ubiquitous computing, ubiquitous communication and intelligent adaptive interfaces . This type of systems consists of a series of interconnected computing and sensing devices Towards ambient intelligence: Multimodal computers that understand our intentions free download Abstract: This paper discusses the state-of-the-art and future developments of conversational multimodal interaction with computers, one of the corner stones of all future eCommerce and eWork applications.
On the basis of past and present experience it is Distributed AI for ambient intelligence: issues and approaches free download Research in many fields of AI, such as distributed planning and reasoning, agent teamwork and coalition formation, cooperative problem solving and action theory has advanced significantly over the last years, both from a theoretical and a practical perspective. In the Ambient intelligence AmI is a novel concept for embedded computing that builds on the large-scale integration of electronic devices into peoples' surroundings and the ubiquitous availability of digital information to the users of such environments.
The concept however is Ambient Assisted Living AAL is currently one of the important research and development areas, where software engineering aspects play a significant role. The goal of AAL solutions is to apply ambient intelligence technologies to enable people with specific needs to Ambient Intelligence for Scientific Discovery free download For half a century, computer scientists have been working on systems for discovering lawful patterns in letters, numbers, words and images.
The research has expanded into the computational study of the process of scientific discovery, producing such well-known AI The Ambient Intelligence paradigm offers an excellent way to define Ambient Assisted Living systems for all kind of users. In addition, people with physical, sensory or cognitive restrictions are expected to particularly benefit from the support of intelligent environments. Occupant behaviour prediction in ambient intelligence computing environment free download Abstract In this paper, the application of ambient intelligence computing techniques in the prediction of occupant behaviours is addressed.
It is aimed to deliver a wellbeing monitoring and assistive environment to support elderly lives independently, in control of their day to Ubiquitous computing and ambient intelligence: New challenges for computing j. It refers to an exciting new paradigm of information technology, in which people are empowered through a digital environment that is aware of their A survey of service composition in ambient intelligence environments free download Abstract This article presents a comparative review of systems performing service composition in Ambient Intelligence Environments.
Such environments should comply to ubiquitous or pervasive computing guidelines by sensing the user needs or wishes and The battle of concepts: Ubiquitous Computing, pervasive computing and ambient intelligence in Mass Media free download ABSTRACT For the past two decades the concepts of ubiquitous computing, pervasive computing and ambient intelligence have been used to describe the Internet of Things. It looks at the challenges and bottlenecks facing the realisation of the Intelligent agile agents: Active enablers for ambient intelligence free download This paper advocates the use of mobile intentional agents as a key enabler in the delivery of ambient intelligence.
Ambient computing as an ideal demands levels of functional attainment that have hithertofar not been realised. Ambient applications demand that the Ubiquitous sensor networks in IMS: an ambient intelligence Telco platform free download Ubiquitous Sensor Network USN concept describes the integration of heterogeneous and geographically dispersed Wireless Sensor and Actuator Networks WSAN into rich information infrastructures for accurate representation and access to different dynamic user's On the role of graspable objects in the ambient intelligence paradigm free download Abstract Ambient Intelligence refers to a vision of the future, in which people are empowered by an electronic environment that is aware of their presence, and is sensitive and responsive to their needs.
It aims at improving the quality of life by creating the desired atmosphere and Agent-based Architecture in An Ambient Intelligence Context. It is based on previous Middleware for ambient intelligence environments: Reviewing requirements and communication technologies free download Ambient Intelligence is an emerging research field that aims to make many of the everyday activities of people easier and more efficient.
This new paradigm gives rise to opportunities for novel, more efficient interactions with computing systems.
At a technical level, the vision Middleware for in-door ambient intelligence: the polyomaton system free download Abstract Ubiquitous computing environments are highly distributed, heterogeneous, complex and context-aware. Therefore, they require emerging middleware components and paradigms, which significantly extend the capabilities of conventional middleware systems. This paper starts out by introducing the Landscapes category at the Joint International Conference on Ambient Intelligence AmI and provides an overview over the two sessions.
The main part of the paper presents a framework for the role of Ambient Identity, profiling algorithms and a world of ambient intelligence free download Abstract The tendency towards an increasing integration of the informational web into our daily physical world in particular in so-called Ambient Intelligent technologies which combine ideas derived from the field of Ubiquitous Computing, Intelligent User Interfaces Ambient intelligence and simulation in health care virtual scenarios free download The success of change depends greatly on the ability to respond to human needs and to bridge the gap between humans and machines, and understanding the environment.
With such experience, in addition to extensive practice in managing change, knowledge sharing 14 The role of Ambient Intelligence in the Social Integration of the Elderly free download Abstract. Society is facing the challenge of demographic changes resulting in a larger proportion of older people. ICTs, may potentially mitigate some of the difficulties created by an ageing society.
New technologies, like Wi-Fi networks and 3rd generation mobile phones, are offering the infrastructure to conceive Ambient Intelligence in the classroom: an augmented school desk free download ABSTRACT This paper discusses the opportunities and challenges of Ambient Intelligence AmI technologies in the context of classroom education, and presents the methodology and preliminary results of the development of an augmented school desk which integrates Development of Ambient Intelligence Applications using Components and Aspects.
One of the main challenges in the development of these systems is to improve their modularization in order to achieve a high degree of reusability, adaptability and Towards secure agent computing for ubiquitous computing and ambient intelligence free download After a first phase of great activity in the field of multi-agent systems, researchers seemed to lose interest in the paradigm, mainly due to the lack of scenarios where the highly distributed nature of these systems could be appropriate.
Ambient intelligence AmI is a growing interdisciplinary area where the focus is shifted towards users instead of merely emphasizing the technological opportunities of AmI. Different methods are employed to understand the adoption of AmI appliances by users. Reasoning about Context in Ambient Intelligence Environments free download So far, most ambient computing frameworks have followed fully centralized approaches, while others have used blackboard and shared memory paradigms. Collecting the reasoning tasks in a central entity certainly has advantages in terms of control and Abstract Systems for Ambient Intelligence environments involve at some stage a service composition task, as a mean of adaptability to the context changes.
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