A Survey of Ambient Intelligence

A considerable increase in road traffic has provoked a total change in the operating paradigms of vehicles, shifting vehicle handling from “just steering” towards a complex adaptation task. With the emergence of wireless communication technology, vehicle operation can now incorporate for the first time ever beside the local driver-vehicle interaction also more significant information obtained from cars in the surrounding. With this foundation it would be possible to build collectively operating driver assistance systems, negotiating the interests of all road participants in a certain area with the final goal to improve global parameters such as road throughput or traffic fluidity, also having an effect on the individual car (driver), e. g. increased travel speed, less congestions, or a reduced level of cognitive load. The question addressed with this paper is whether or not the vehicle speed can be sustained while merging onto a motorway, leading to a more harmonious integration of the merging cars into the flowing traffic on the main road. To achieve this we propose the application of ambient intelligence (AmI) technology operating on the collective behavior of all cars in the periphery of the entrance ramp. To prove our hypothesis we applied the AmI technology to a data driven, true to scale simulation model of the Madrid motorway M30, one of the most busiest roads in Spain. The comparison of simulation runs with high volume of traffic showed that technology assistance could help to increase road throughput and minimize the variance of traffic flow, but on the other side demands solutions for one of the bigger problems of data driven simulation – missing or noisy data compromising simulation results.

This chapter begins with a grounding in the principles underlying the Ambient Intelligence (AmI) paradigms providing healthcare services to older residents who are living in their homes or in supported housing. This study will explore the complexity of diagnosis and prognosis in healthcare where multiple vital sign parameters are obtained from the patients using smart sensors and Internet of Things (IoT) technologies. Moreover, Ubiquitous/Pervasive computing, wearable technologies, context-awareness and Artificial Intelligence (AI) are investigated to highlight the importance and contribution of these paradigms and disciplines to the intelligence, ubiquitous and adaptivity of the Ambient Assisted Living (AAL) environment. Later in this chapter, the current application of AAL health monitoring will be discussed followed by a discussion on research gaps.

Ambient Intelligence (AmI) constitutes an evolution of Information and Communication Technologies which responds to the current increasing demand for anytime anywhere availability of information and electronic services. AmI technologies integrate sensing capabilities, processing power, reasoning mechanisms, networking facilities, applications and services, digital content, and actuating capabilities distributed the environment. While a wide variety of different technologies is involved, the goal of AmI is to either entirely hide their presence from users or to smoothly integrate them within the surrounding context as enhanced environment artifacts, rather than as technological gadgets. The pervasiveness of interaction AmI environments requires the elaboration of new interaction concepts that extend beyond the current user interface concepts like the desktop metaphor and menu driven interfaces. AmI will therefore bring about new interaction techniques, as well as novel uses and multimodal combinations of existing advanced techniques, such as, for example, gestures and localisation. Additionally, interaction is embedded everyday objects and smart artifacts. This concept refers to interfaces that use physical artifacts as objects for representation and interaction, seamlessly integrating the physical and digital worlds. Interaction AmI environments inherently relies on multimodal input, implying that it combines various user input modes, such as speech, pen, touch, manual gestures, gaze and head and body movements, as well as more than one output modes, primarily the form of visual and auditory feedback. In this context, adaptive multimodality is prominent to support natural input a dynamically changing context-of-use, adaptively offering to users the most appropriate and effective input forms at the current interaction context.The ICS-FORTH Ambient Intelligence Programme is an on-going horizontal interdisciplinary RTD Programme aiming to develop and apply pioneering human-centric AmI technologies and Smart Environments, capable of understanding and fulfilling individual human needs. This Programme constitutes a systematic effort towards addressing the challenges which arise the context of AmI, by providing natural forms of interaction and access to information and communication. In this context, a wide variety of AmI applications and services have been developed for various environments and domains, including home and everyday living, office work, culture and museums, exhibitions and public spaces, education, and health. These developments constitute showcases for demonstrating practice AmI technologies and their potential and benefits different aspects of everyday life and activities. Some of them have been deployed in vivo and are available and used real environments, such as, for example, the exhibition of AmI artifacts Macedonia from fragments to pixels deployed at the Archaeological Museum of Thessaloniki. The new ICSFORTH AmI Research Facility, due to be completed by the end of 2011, will comprise simulated AmI-augmented environments and their support spaces, laboratory spaces for developing and testing related technologies, and will provide an appropriate environment for the pilot deployment and user-based evaluation of the developed AmI technologies under conditions very similar to real life.

The potentially attractive exploitation of Ambient Intelligence (AmI) seeks improving performance and quality of life of people inside workplaces (e.g., offices, manufacturing work centers, homes). To succeed at making the implementation of AmI fruit

Ambient Intelligence (AmI) is an information technology approach that is interactive, sensitive and responsive to a user's environment. Emerging AmI technologies are intended to be intelligent and intuitive to a user's needs and therefore embedded into a user's everyday life without so much as being obtrusive. However, with any emergent technology such as AmI, ethical concerns arise. It would be desirable to have a better understanding of future technological developments, and in this case, AmI technological developments in order to allow ethical considerations to influence design and implementations of the technologies. However, the unavoidable contingency of future developments provides a fundamental limit to what we can know about the future. With this, this paper attempts to explore how this problem can be addressed by providing a framework of technical developments which include AmI technology developments that one can reasonably expect to materialise in the medium term future of 10 to 15 years and ethical issues that are currently expected to arise within the European Union (EU). This is done by analysing current European research funding documents with a view to exploring the trends, purposes, applications, artefacts, ethical issues, and governance structures that the European Commission foresees. The overall aim of the paper is to provide the conceptual basis of this framework.

As digital technologies become increasingly pervasive, we might find ourselves living with almost invisible, intelligent interactive systems - an 'ambient intelligence' - that forms a part of our everyday existence and ecology. The implications of this development are far reaching for individuals, businesses and communities. Ambient intelligence could lead to great opportunities. But as with all new technologies, we know that the technology itself is neither good nor bad. It is how we might use it that makes the difference. The main challenge at this moment is to guarantee that the new ambient intelligence technologies are appropriate, sustainable and meet people's individual and social needs. The AMEC project explores how an ambient ecology of products, services and content that is adaptive and intuitive to use can support domestic life in the connected home of the future

The utilization of large language model-based artificial intelligence (AI) in the field of neurology has gained attention as a viable tool to enhance and assist providers with processes ranging from scheduling patients to providing preliminary interpretations of testing results, pending orders, and documenting encounters. Epileptologists could benefit from these technologies by utilizing ambient AI models, recent applications of which offer promising solutions for automating clinical documentation. While the potential benefits of using these tools are significant and include reduced physician burnout and improved patient experience, the deployment of these technologies also raises critical concerns, such as potential biases in model training and the risk of errors being inserted into the electronic health record (EHR), among other yet to be realized unintended consequences. The accuracy of clinical documentation is essential in epilepsy care, where detailed seizure histories and accurate medication records are critical to patient safety. Another concern may be paradoxically increased physician burnout as increased expectations of providers are created. This article examines the challenges, risks, and practical considerations in applying documentation tools that utilize ambient intelligence (AmI) for outpatient epilepsy clinic encounters, highlighting key examples from clinical practice and underscoring the importance of human oversight. Although AmI models may enhance clinical documentation efficiency as measured by time to close a note and reduced rates of burnout in providers, their role in clinical environments must be carefully regulated, with further studies needed to validate this claim, provide ongoing monitoring of performance, and establish safeguards for patient safety. Collaborative efforts among clinicians, clinical informatics professionals, AI developers, and regulatory bodies are pressingly needed to ensure the safe deployment of AmI into clinical care settings. PLAIN LANGUAGE SUMMARY: Ambient artificial intelligence technology takes advantage of sensors embedded in the environment to automate tasks without the need for human input. It has the potential to streamline numerous tasks within outpatient epilepsy clinics and reduce the workload of providers as well as improve patient care. This technology has already been brought to the market as a tool for clinical documentation. The current challenges and limitations associated with its implementation require careful human oversight, which we show with examples. Further research, regulations, and ongoing monitoring are necessary to ensure ambient artificial intelligence benefits both patients and healthcare providers while minimizing risks.

Ambient intelligence refers to the combination of pervasive ubiquitous computing, big data and artificial frameworks, IoT, sensor networks, and human-computer interaction (HCI) technologies. This technology paves the way for a futuristic world in which sensors incorporated into everyday devices create a smart environment that is seamlessly adapted to customer requirements and wishes. With patient health status records and patient electronic medical record (EMR), updates can help to provide a better and more straightforward narrative for the healthcare sector. It can assist healthcare workers, such as physicians and nurses, in providing quality care by analyzing patient data, such as prior treatments, allergic reactions, and more. Ambient intelligence helps the elderly in countries with a higher population of senior citizens by remotely monitoring their health and enabling them to live independently through ambient assisted living (AAL) technology. In this chapter, a case study related to the COVID disaster will be discussed with the help of ambient intelligence and new technologies.

The ubiquitous computing (UC) idea envisioned by Weiser in 1991 has recently evolved to a more general paradigm known as Ambient Intelligence (AmI). This vision represents a new generation of user-centred computing environments aiming to find new ways to obtain a better integration of the information technology in everyday life devices and activities. AmI environments are integrated by several autonomous computational devices of modern life ranging from consumer electronics to mobile phones. Ideally, people in an AmI environment 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 vehicular ad hoc networks (VANET), Ambient Assisted Living (AAL), e-Health, Internet of Things and Home Automation among others. This theme issue focuses on gathering research results coming from Ambient Intelligence and probably its most promising, socially and commercially speaking, application domain, namely Ambient Assisted Living (AAL). The papers in this issue have been selected from two international conferences held in Valencia in September 2010, namely UCAmI and IWAAL, respectively. The Symposium of Ubiquitous Computing and Ambient Intelligence (UCAmI) has consolidated, in its four editions, as a reference event in Europe and South America, and it is one of the two oldest Ambient Intelligence-specific events. On the other hand, the International Workshop of Ambient Assisted Living (IWAAL) is one of the few specific conferences on the topic of Ambient Assisted Living (AAL). AAL is, without doubt, one of the most clear targets of Ubiquitous Computing/Ambient Intelligence since it attempts to solve a real problem, i.e. how the seamless integration of infocommunication technologies within homes and residences can enhance elderly people’s quality of life and autonomy, thus reducing their need for being institutionalized or aiding them when it happens. In what follows, a short overview of the papers included classified by their specific topic within AmI is given. Notice that contributions from researchers from Belgium, France, Mexico, Chile and Spain have been compiled in this issue. Firstly, several works have centred on the application of novel software engineering techniques and middleware to make reality the Ubiquitous Computing vision:

T Subjects such as knowledge engineering, pervasive computing, unified communication, ubiquitous sensing and actuation and situation awareness are gaining the most critical and crucial attention from information technology (IT) professionals and pundits across the globe these days in order to accomplish the vision of ambient intelligence (AmI). It is all about effective and round-the-clock gleaning of data and information from different and distributed sources. Secondly whatever is gathered, transmitted, and stocked are being subjected to a cornucopia of tasks such as processing, mining, clustering, classification, and analysis for the real-time and elegant extraction of hidden actionable insights. Based on the knowledge extracted and the needs identified, the final tasks is decide and initiate the next course of actions in time. Not only information, interaction and transaction, but also physical services can be conceived, constructed and supplied to human users with the stability and maturity AmI technologies and instrumented, interconnected, and intelligent devices. This paper gives the detailed description of an AmI application which can provide impenetrable and unbreakable security, convenience, care and comfort for the needy. Our focus here is to develop a secure and safety-critical Ambient Assisted Living (AAL) environment which can monitor the patient's situation and give timely updates. In order to fulfill all these needs, a smart environment has been created to effectively and insightfully control patients' needs. The middleware standard preferred for the development and deployment a bevy of ambient and articulate services is Open Service Gateway Initiative (OSGi).

The population of elderly people keeps increasing rapidly, which becomes a predominant aspect of our societies. As such, solutions both efficacious and cost-effective need to be sought. Ambient assisted living (AAL) is a new approach which promises to address the needs from elderly people. Ambient intelligence technologies are widely developed in this domain aiming to construct safe environments around assisted peoples and help them maintain independent living. However, there are still many fundamental issues in AAL that remain open. Most of the current efforts still do not fully express the power of human being, and the importance of social connections and social activities is less noticed. Our conjecture is that such features are fundamental prerequisites towards truly effective AAL services. This paper reviews the current status of researches on AAL, discusses the promises and possible advantages of AAL, and also indicates the challenges we must meet in order to develop practical and efficient AAL systems for elderly people. In this paper, we also propose an approach to construct effective home-care system for the elderly people.

Pervasive healthcare systems are designed to support elderly and care-dependent people to live an independent life. Recent developments are driven by technological advances of wireless sensor networks and mobile devices, which ease their application in the health- and homecare domain. The integration into pervasive healthcare systems helps to improve the impact and the efficiency of eldercare, while keeping financial efforts at a moderate level. The importance of these issues leads to the development of systems covering situation-aware, ambient assisted living and health data exchange between care institutions and ambient assistant solutions. Various projects within the Ambient Assisted Living (AAL) domain have proven that remarkable results can be achieved by using wireless sensor technology and mobile devices for data collection, but there are still several problems concerning the exchange and integration of healthcare data. This chapter gives an overview about AAL, healthcare related standards, and state of the art approaches for data integration. In addition, best practice projects, which deal with patient-oriented care information, ambient assisted living, as well as ambient intelligence, are covered.

Ambient intelligence (AmI) is perceived as a tool that can provide innovative and cost-effective ways to support everyday living of elderly individuals by monitoring them in their homes, in healthcare centers and in their out-of-home activities. In contrast to previous surveys of AmI and its applications for various segments in society, this review, which is not intended to be exhaustive, focuses primarily on the possible uses of AmI for the elderly. This review defines the term of AmI and exemplifies some current applications of AmI in our lives, points out the reasons for developing AmI applications specifically for the elderly and offers insights to various research projects that aim to use AmI for the benefit of the elderly. Since user acceptance of AmI systems presents challenges in the process of developing and applying AmI technologies, this review also sheds light on the views of elderly individuals regarding the use of these technologies. Finally, following a section briefly reviewing the ethical issues related to AmI technologies as it pertains to the elderly, this review offers some recommendations for the further development and use of AmI in this population.

“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

Advances in Ambient Intelligence (AmI) technologies have significant implications for individuals, society and warfare. This paper examines ethical challenges associated with the development of the emerging discipline of Ambient Intelligence technologies. It is argued that Ambient Intelligence technologies, while providing support for many aspects of everyday life and well-being, may also present increased privacy risks and potential risks to national security.