Ambient Intelligence in Perspective

2010 ◽  
pp. 129-136 ◽  
Author(s):  
Caroline Byrne ◽  
Michael O’Grady ◽  
Gregory O’Hare
Keyword(s):  
Artificial Intelligence ◽  
Mobile Computing ◽  
Ambient Intelligence ◽  
Design And Implementation ◽  
Computing Paradigm ◽  
Software Professionals ◽  
Essential Prerequisite ◽  
Embedded Intelligence

Ambient intelligence (AmI) is a relatively new and distinct interpretation of the mobile computing paradigm. However, its recognition that embedded intelligence, either in actuality or perception, is an essential prerequisite if mobile computing is to realize its potential distinguishes it from other mobile usage paradigms. Though stressing the need for intelligence, and implicitly the adoption of artificial intelligence (AI) techniques, AmI does not formally ratify any particular approach and is thus technique agnostic. In this article, we examine the constituent technologies of AmI and provide a brief overview of some exemplary AmI projects. In particular, the question of intelligence is considered and some strategies for incorporating intelligence into AmI applications and services are proposed. It is the authors hope that a mature understanding of the issues involved will aid software professionals in the design and implementation of AmI applications.

Ambient Intelligence in Perspective

2011 ◽  
pp. 136-140
Author(s):  
Caroline Byrne ◽  
Michael O’Grady ◽  
Gregory O’Hare
Keyword(s):  
Artificial Intelligence ◽  
Mobile Computing ◽  
Ambient Intelligence ◽  
Design And Implementation ◽  
Computing Paradigm ◽  
Software Professionals ◽  
Essential Prerequisite ◽  
Embedded Intelligence

Ambient intelligence (AmI) is a relatively new and distinct interpretation of the mobile computing paradigm. However, its recognition that embedded intelligence, either in actuality or perception, is an essential prerequisite if mobile computing is to realize its potential distinguishes it from other mobile usage paradigms. Though stressing the need for intelligence, and implicitly the adoption of artificial intelligence (AI) techniques, AmI does not formally ratify any particular approach and is thus technique agnostic. In this article, we examine the constituent technologies of AmI and provide a brief overview of some exemplary AmI projects. In particular, the question of intelligence is considered and some strategies for incorporating intelligence into AmI applications and services are proposed. It is the authors hope that a mature understanding of the issues involved will aid software professionals in the design and implementation of AmI applications.

scholarly journals Cyber-Physical Systems Improving Building Energy Management: Digital Twin and Artificial Intelligence

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2338
Author(s):  
Sofia Agostinelli ◽  
Fabrizio Cumo ◽  
Giambattista Guidi ◽  
Claudio Tomazzoli
Keyword(s):  
Artificial Intelligence ◽  
Renewable Energy ◽  
Energy Management ◽  
Three Dimensional ◽  
Cost Effective ◽  
Automation System ◽  
Climate Conditions ◽  
Digital Twin ◽  
Building Energy Management ◽  
Computing Paradigm

The research explores the potential of digital-twin-based methods and approaches aimed at achieving an intelligent optimization and automation system for energy management of a residential district through the use of three-dimensional data model integrated with Internet of Things, artificial intelligence and machine learning. The case study is focused on Rinascimento III in Rome, an area consisting of 16 eight-floor buildings with 216 apartment units powered by 70% of self-renewable energy. The combined use of integrated dynamic analysis algorithms has allowed the evaluation of different scenarios of energy efficiency intervention aimed at achieving a virtuous energy management of the complex, keeping the actual internal comfort and climate conditions. Meanwhile, the objective is also to plan and deploy a cost-effective IT (information technology) infrastructure able to provide reliable data using edge-computing paradigm. Therefore, the developed methodology led to the evaluation of the effectiveness and efficiency of integrative systems for renewable energy production from solar energy necessary to raise the threshold of self-produced energy, meeting the nZEB (near zero energy buildings) requirements.

On the Notion of Collective Intelligence

2010 ◽  
Vol 1 (1) ◽  
pp. 1-14 ◽  
Author(s):  
Epaminondas Kapetanios
Keyword(s):  
Collective Intelligence ◽  
Point Of View ◽  
Social Web ◽  
Synergistic Interactions ◽  
Design And Implementation ◽  
Computing Paradigm ◽  
The Social ◽  
Challenging Research ◽  
Research Questions ◽  
Set Up

In this article, the author explores the notion of Collective Intelligence (CI) as an emerging computing paradigm. The article is meant to provide a historical and contextual view of CI through the lenses of as many related disciplines as possible (biology, sociology, natural and environmental sciences, physics) in conjunction with the computer science point of view. During this explorative journey, the article also aims at pinpointing the current strengths and weaknesses of CI-related computational and system engineering design and implementation methodologies of CI-based systems. A non-exhaustive list of case studies set up the stage for CI applications as well as challenging research questions. These can be particularly directed towards the Social Web, as a very prominent example of synergistic interactions of a group of people with diverse cultural and professional backgrounds and its potential to become a platform for the emergence of truly CI-based systems.

Design and implementation of mobile trusted module for trusted mobile computing

2010 ◽  
Vol 56 (1) ◽  
pp. 134-140 ◽  
Author(s):  
Mooseop Kim ◽  
Hongil Ju ◽  
Youngsae Kim ◽  
Jiman Park ◽  
Youngsoo Park
Keyword(s):  
Mobile Computing ◽  
Design And Implementation

On the Notion of Collective Intelligence

2012 ◽  
pp. 1-14
Author(s):  
Epaminondas Kapetanios
Keyword(s):  
Collective Intelligence ◽  
Point Of View ◽  
Environmental Sciences ◽  
Synergistic Interactions ◽  
Design And Implementation ◽  
Computing Paradigm ◽  
The Social ◽  
Research Questions ◽  
Set Up ◽  
Exhaustive List

In this article, the author explores the notion of Collective Intelligence (CI) as an emerging computing paradigm. The article is meant to provide a historical and contextual view of CI through the lenses of as many related disciplines as possible (biology, sociology, natural and environmental sciences, physics) in conjunction with the computer science point of view. During this explorative journey, the article also aims at pinpointing the current strengths and weaknesses of CI-related computational and system engineering design and implementation methodologies of CI-based systems. A non-exhaustive list of case studies set up the stage for CI applications as well as challenging research questions. These can be particularly directed towards the Social Web, as a very prominent example of synergistic interactions of a group of people with diverse cultural and professional backgrounds and its potential to become a platform for the emergence of truly CI-based systems.

Security Engineering for Ambient Intelligence

2008 ◽  
pp. 3691-3712
Author(s):  
A. Mana ◽  
C. Rudolph ◽  
G. Spanoudakis ◽  
V. Lotz ◽  
F. Massacci ◽  
...  
Keyword(s):  
Ambient Intelligence ◽  
Comprehensive Approach ◽  
Integral Model ◽  
Security Engineering ◽  
Computing Paradigm ◽  
Integration Schemes ◽  
Computer Aided ◽  
New Challenges ◽  
Run Time

The scenarios of Ambient Intelligence introduce a new computing paradigm and set new challenges for the design and engineering of secure and dependable sys-tems. This chapter describes SERENITY, a comprehensive approach to overcome those problems. The key to success in this scenario is to capture security expertise in such a way that it can be supported by automated means. SERENITY’s integral model of S&D considers both static and dynamic aspects by relying in two main innovations: (1) the enhanced notion of S&D patterns and integration schemes; and (2) the computer aided run-time monitoring of the implemented security solutions.

Developing Trends in Power and Networking Technologies for Intelligent Cities

2021 ◽  
pp. 61-85
Author(s):  
Kadir Alpaslan Demir ◽  
Buğra Turan
Keyword(s):  
Artificial Intelligence ◽  
Internet Of Things ◽  
Industry 4.0 ◽  
Ambient Intelligence ◽  
The Internet ◽  
Key Technologies ◽  
Intelligent Cities ◽  
Networking Technologies ◽  
The Internet Of Things

The introduction of Industry 4.0 has increased the focus on a number of technologies. These technologies also help realize the vision for intelligent cities. Furthermore, there are already discussions of Industry 5.0. One emerging aspect of Industry 5.0 is human-robot co-working. With the help of artificial intelligence, the internet of things paradigm, Industry 4.0, and Industry 5.0 visions, there will be two predominant types of systems interfacing with people in intelligent cities. These are robotic and ambient intelligence systems. The increasing deployment of these will help make cities even smarter. However, we need to see advancements in a number of relevant key technologies, including power and networking technologies. In this chapter, first, the authors briefly discuss Industry 4.0, Industry 5.0, and intelligent cities paradigm, as well as robotic and ambient intelligence systems. Then, they focus on developing trends in power and networking technologies.

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.

Sign in / Sign up

Export Citation Format

Share Document