On Dependability Issues in Ambient Intelligence Systems

2011 ◽  
Vol 3 (3) ◽  
pp. 18-27
Author(s):  
Marcello Cinque ◽  
Antonio Coronato ◽  
Alessandro Testa
Keyword(s):  
Assisted Living ◽  
Intelligent Systems ◽  
Ambient Intelligence ◽  
Ambient Assisted Living ◽  
Smart Environments ◽  
Practical Application ◽  
Smart Systems ◽  
Computing Paradigm ◽  
Ambient Intelligent ◽  
Verification Techniques

Ambient Intelligence (AmI) is the emerging computing paradigm used to build next-generation smart environments. It provides services in a flexible, transparent, and anticipative manner, requiring minimal skills for human-computer interaction. Recently, AmI is being adapted to build smart systems to guide human activities in critical domains, such as, healthcare, ambient assisted living, and disaster recovery. However, the practical application to such domains generally calls for stringent dependability requirements, since the failure of even a single component may cause dangerous loss or hazard to people and machineries. Despite these concerns, there is still little understanding on dependability issues in Ambient Intelligent systems and on possible solutions. This paper provides an analysis of the AmI literature dealing with dependability issues and to propose an innovative architectural solution to such issues, based on the use of runtime verification techniques.

On Dependability Issues in Ambient Intelligence Systems

2014 ◽  
pp. 146-155
Author(s):  
Marcello Cinque ◽  
Antonio Coronato ◽  
Alessandro Testa
Keyword(s):  
Assisted Living ◽  
Intelligent Systems ◽  
Ambient Intelligence ◽  
Ambient Assisted Living ◽  
Runtime Verification ◽  
Smart Environments ◽  
Smart Systems ◽  
Computing Paradigm ◽  
Ambient Intelligent ◽  
Verification Techniques

Ambient Intelligence (AmI) is the emerging computing paradigm used to build next-generation smart environments. It provides services in a flexible, transparent, and anticipative manner, requiring minimal skills for human-computer interaction. Recently, AmI is being adapted to build smart systems to guide human activities in critical domains, such as, healthcare, ambient assisted living, and disaster recovery. However, the practical application to such domains generally calls for stringent dependability requirements, since the failure of even a single component may cause dangerous loss or hazard to people and machineries. Despite these concerns, there is still little understanding on dependability issues in Ambient Intelligent systems and on possible solutions. This paper provides an analysis of the AmI literature dealing with dependability issues and to propose an innovative architectural solution to such issues, based on the use of runtime verification techniques.

Ambient Assisted Living Systems: The Scope of Research and Development

2017 ◽  
Vol 3 (2) ◽  
pp. 21
Author(s):  
Ashish D Patel ◽  
Jigarkumar H. Shah
Keyword(s):  
Assisted Living ◽  
Independent Living ◽  
Intelligent Systems ◽  
New Technologies ◽  
Ambient Assisted Living ◽  
Smart Devices ◽  
Economic Changes ◽  
Aged Population ◽  
The People ◽  
Living Person

The aged population of the world is increasing by a large factor due to the availability of medical and other facilities. As the number grows rapidly, requirements of this segment of age (65+) are increasing rapidly as well as the percentage of aged persons living alone is also increasing with the same rate due to the inevitable socio-economic changes. This situation demands the solution of many problems like loneliness, chronic conditions, social interaction, transportation, day-to-day life and many more for independent living person. A large part of aged population may not be able to interact directly with new technologies. This sought some serious development towards the use of intelligent systems i.e. smart devices which helps the people with their inability to use the available as well future solutions. Ambient Assisted Living (AAL) is the answer to these problems. In this paper, issues related to AAL systems are studied. Study of challenges and limitations of this comparatively new field will help the designers to remove the barriers of AAL systems.

Cognitive Internet of Everything (CIoE)

2020 ◽  
pp. 1212-1238
Author(s):  
Gopal Singh Jamnal ◽  
Xiaodong Liu ◽  
Lu Fan ◽  
Muthu Ramachandran
Keyword(s):  
Assisted Living ◽  
Smart Home ◽  
Ambient Intelligence ◽  
Clustering Algorithms ◽  
Critical Evaluation ◽  
Internet Of Everything ◽  
Metropolitan Cities ◽  
New Information ◽  
Ambient Intelligent ◽  
Input Dataset

In today's world, we are living in busy metropolitan cities and want our homes to be ambient intelligent enough towards our cognitive requirements for assisted living in smart space environment and an excellent smart home control system should not rely on the users' instructions (Wanglei, 2015). The ambient intelligence is a sensational new information technology paradigm in which people are empowered for assisted living through multiple IoTs sensors environment that are aware of inhabitant presence and context and highly sensitive, adaptive and responsive to their needs. A noble ambient intelligent environment are characterized by their ubiquity, transparency and intelligence which seamlessly integrated into the background and invisible to surrounded users/inhabitant. Cognitive IoE (Internet of Everything) is a new type of pervasive computing. As the ambient smart home is into research only from a couple of years, many research outcomes are lacking potentials in ambient intelligence and need to be more dug around for better outcomes. As a result, an effective architecture of CIoE for ambient intelligent space is missing in other researcher's work. An unsupervised and supervised methods of machine learning can be applied in order to classify the varied and complex user activities. In the first step, by using fuzzy set theory, the input dataset value can be fuzzified to obtain degree of membership for context from the physical layer. In the second step, using K-pattern clustering algorithms to discover pattern clusters and make dynamic rules based on identified patterns. This chapter provides an overview, critical evaluation of approaches and research directions to CIoE.

Cognitive Internet of Everything (CIoE)

2017 ◽  
pp. 277-309 ◽  
Author(s):  
Gopal Singh Jamnal ◽  
Xiaodong Liu ◽  
Lu Fan ◽  
Muthu Ramachandran
Keyword(s):  
Assisted Living ◽  
Smart Home ◽  
Ambient Intelligence ◽  
Clustering Algorithms ◽  
Critical Evaluation ◽  
Internet Of Everything ◽  
Metropolitan Cities ◽  
New Information ◽  
Ambient Intelligent ◽  
Input Dataset

In today's world, we are living in busy metropolitan cities and want our homes to be ambient intelligent enough towards our cognitive requirements for assisted living in smart space environment and an excellent smart home control system should not rely on the users' instructions (Wanglei, 2015). The ambient intelligence is a sensational new information technology paradigm in which people are empowered for assisted living through multiple IoTs sensors environment that are aware of inhabitant presence and context and highly sensitive, adaptive and responsive to their needs. A noble ambient intelligent environment are characterized by their ubiquity, transparency and intelligence which seamlessly integrated into the background and invisible to surrounded users/inhabitant. Cognitive IoE (Internet of Everything) is a new type of pervasive computing. As the ambient smart home is into research only from a couple of years, many research outcomes are lacking potentials in ambient intelligence and need to be more dug around for better outcomes. As a result, an effective architecture of CIoE for ambient intelligent space is missing in other researcher's work. An unsupervised and supervised methods of machine learning can be applied in order to classify the varied and complex user activities. In the first step, by using fuzzy set theory, the input dataset value can be fuzzified to obtain degree of membership for context from the physical layer. In the second step, using K-pattern clustering algorithms to discover pattern clusters and make dynamic rules based on identified patterns. This chapter provides an overview, critical evaluation of approaches and research directions to CIoE.

The Role of Augmented Reality within Ambient Intelligence

2014 ◽  
pp. 73-88
Author(s):  
Kevin Curran ◽  
Denis McFadden ◽  
Ryan Devlin
Keyword(s):  
Augmented Reality ◽  
Real Time ◽  
Physical Environment ◽  
Intelligent Systems ◽  
Ambient Intelligence ◽  
Contextual Information ◽  
Ambient Intelligent

An Augmented Reality (AR) is a technology which provides the user with a real time 3D enhanced perception of a physical environment with addition virtual elements—either virtual scenery, information regarding surroundings, other contextual information—and is also capable of hiding or replacing real structures. With Augmented Reality applications becoming more advanced, the ways the technology can be viably used is increasing. Augmented Reality has been used for gaming several times with varying results. AR systems are seen by some as an important part of the ambient intelligence landscape. Therefore, the authors present several types of augmentation applications of AR in the domestic, industrial, scientific, medicinal, and military sectors which may benefit future ambient intelligent systems.

scholarly journals ATTICUS: Ambient-Intelligent Tele-monitoring and Telemetry for Incepting and Catering Over hUman Sustainability

2021 ◽  
Vol 3 ◽  
Author(s):  
Gennaro Laudato ◽  
Simone Scalabrino ◽  
Angela Rita Colavita ◽  
Quintiliano Chiacchiari ◽  
Romolo D'Orazio ◽  
...  
Keyword(s):  
Assisted Living ◽  
Ambient Assisted Living ◽  
Home Monitoring ◽  
Distributed Software ◽  
Remote Monitoring System ◽  
Essential Components ◽  
Ambient Intelligent ◽  
Behavioral Parameters ◽  
Electrocardiogram Ecg ◽  
Tele Monitoring

Wearable devices as medical technologies are becoming an integral part of our lives. Many research studies are dedicated to these devices and are mainly focused on providing personal analytics, measuring physical status, and acquiring physiological signals and parameters. These continuously evolving technologies play an important role in telemedicine. Telemedicine can be broadly defined as the use of advanced telecommunications technologies to support many medical activities, such as the diagnosis, the analysis of patient data, the improvement of disease management and the treatment in remote areas. In this article, we present ATTICUS (Ambient-intelligent Tele-monitoring and Telemetry for Incepting and Catering over hUman Sustainability), an innovative remote monitoring system for ambient-assisted living based on the analysis of vital and behavioral parameters. The ATTICUS system consists of two essential components: a smart wearable—in the form of a short singlet—made of innovative textile which allows the acquisition of real-time body signals, e.g., electrocardiogram (ECG), breathing wave, temperature, and a multi-level Decision Support System (DSS), a distributed software which integrates advanced machine learning methods to automatically detect anomalies. ATTICUS is capable of operating in different application scenarios. Especially, the system will support in-home and out-home monitoring, personal check-ups, and specialized check-ups. Thus, the system will positively impact the canonical medical practices allowing simultaneous and continuous monitoring of a large number of people.

Situation-Aware Ambient Assisted Living and Ambient Intelligence Data Integration for Efficient Eldercare

2013 ◽  
pp. 315-348
Author(s):  
Werner Kurschl ◽  
Mario Buchmayr ◽  
Barbara Franz ◽  
Margit Mayr
Keyword(s):  
Data Integration ◽  
Mobile Devices ◽  
Assisted Living ◽  
Data Exchange ◽  
Ambient Intelligence ◽  
Ambient Assisted Living ◽  
Healthcare Systems ◽  
Wireless Sensor ◽  
Pervasive Healthcare ◽  
Recent Developments

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 Assisted Living Research in the CareLab

GeroPsych ◽  
2010 ◽  
Vol 23 (2) ◽  
pp. 115-119 ◽  
Author(s):  
Boris de Ruyter ◽  
Elly Zwartkruis-Pelgrim ◽  
Emile Aarts
Keyword(s):  
Assisted Living ◽  
Ambient Intelligence ◽  
Social Connectedness ◽  
Technology Development ◽  
Ambient Assisted Living ◽  
The Elderly ◽  
Cognitive Stimulation ◽  
Technology Applications ◽  
Aging Societies

As technology development progresses, the vision of ambient intelligence has provided a human-centric approach to applications of technology. In the context of aging societies, ambient intelligence has focused on providing assistive solutions for elders at risk of losing their independence. In this article we report on a research environment called CareLab and describe three projects that have studied the role of technology in the monitoring and coaching of older adults. By focusing on the need for a feeling of safety, cognitive stimulation, and social connectedness, these projects have investigated the role of technology applications for supporting the elderly in maintaining an independent lifestyle. Finally, we discuss some challenges crucial for the success of ambient assisted-living research.

scholarly journals A Computational Approach to Improve the Gathering of Ambient Assisted Living Requirements

Proceedings ◽  
2018 ◽  
Vol 2 (19) ◽  
pp. 1246
Author(s):  
Noelia Castillo ◽  
Juan Pérez ◽  
Jorge Gómez-Sanz
Keyword(s):  
Social Sciences ◽  
Assisted Living ◽  
Simulation Modeling ◽  
Ambient Intelligence ◽  
Ambient Assisted Living ◽  
End Users ◽  
Computational Approach ◽  
Human Values ◽  
Societal Impact ◽  
Depth Interviews

Recent publications focus on the importance of designing an Ambient Intelligence that can be sensitive to human values and responsible for its societal impact. Obtaining and properly modeling these requirements can be a challenging task. Co-creation and social sciences methods are frequently applied in order to discover what end-users need using methods such as field/case studies where interviews or focus group sessions are conducted. However, those methods can be limited. This paper introduces two complementary approaches, one using traditional semi-structured and in-depth interviews, and another one based on 3D simulation modeling. The context is a research project where interviews were conducted to caregivers of people with Alzheimer disease. When designing the solution, it is important to account what kind of technology the end-users are expecting and what scenarios need to be accounted. So, the paper first summarizes what technology this collective is seeking or willing to accept. Then it proceeds with a brief summary of one of the interviews. Following, it shows the process of transferring this information to actual 3D simulations and discusses the benefits of doing so in the context of Ambient Assisted Living.

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