Understanding As a New Paradigm in The Design of The Intelligent Systems in Automotive and Transportation Technology

2001 ◽  
Author(s):  
Zbigniew Les ◽  
Magdalena Les
Keyword(s):  
Intelligent Systems ◽  
New Paradigm ◽  
Automotive And Transportation

THE CONCEPT OF AUTONOMOUS SYSTEMS IN INDUSTRY 4.0

2019 ◽  
Vol 12 (1) ◽  
pp. 77-87
Author(s):  
György Kovács ◽  
Rabab Benotsmane ◽  
László Dudás
Keyword(s):  
Industry 4.0 ◽  
Intelligent Systems ◽  
Autonomous Systems ◽  
Essential Element ◽  
Industrial Sector ◽  
Life Cycles ◽  
Multi Agent Systems ◽  
New Paradigm ◽  
Intelligent Machines ◽  
Digital Network

Recent tendencies – such as the life-cycles of products are shorter while consumers require more complex and more unique final products – poses many challenges to the production. The industrial sector is going through a paradigm shift. The traditional centrally controlled production processes will be replaced by decentralized control, which is built on the self-regulating ability of intelligent machines, products and workpieces that communicate with each other continuously. This new paradigm known as Industry 4.0. This conception is the introduction of digital network-linked intelligent systems, in which machines and products will communicate to one another in order to establish smart factories in which self-regulating production will be established. In this article, at first the essence, main goals and basic elements of Industry 4.0 conception is described. After it the autonomous systems are introduced which are based on multi agent systems. These systems include the collaborating robots via artificial intelligence which is an essential element of Industry 4.0.

scholarly journals Социо-технические системы (СТС) как новая парадигма компьютеризации

2020 ◽  
pp. 353-357
Author(s):  
Anatolii Kosolapov
Keyword(s):  
Human Resource ◽  
Organizational Support ◽  
Intelligent Systems ◽  
Computer Systems ◽  
Technical System ◽  
New Paradigm ◽  
Global Society ◽  
Technical Systems ◽  
Definition Of ◽  
Resource Support

The paper considers the problems of the formation of modern global society and their impact on the development of computerization paradigms. At present, a new paradigm is emerging - socio-technical systems (STS) as the development of the paradigm of intelligent systems. The author has proposed a new definition of STS through the classical definition of the concept of the architecture of a socio-technical system, including an 8-link formula from all the main types of resource support for computer systems: a set of hardware (HRS), mathematical (MRS) and software (SRS) resource support, information (IRS) and linguistic (LRS), metrological (MetRS) and documentary (DRS) support and organizational support (ORS) or human resource of STS. In work the structure of resource support for computerization paradigms is given. The transition to STS is associated with the need to solve a number of pressing problems of society in the context of global informatization.

scholarly journals The social turn of artificial intelligence

AI & Society ◽  
2021 ◽  
Author(s):  
Nello Cristianini ◽  
Teresa Scantamburlo ◽  
James Ladyman
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Systems ◽  
Single System ◽  
New Paradigm ◽  
Digital Platforms ◽  
Online Platforms ◽  
Large Numbers ◽  
The Social ◽  
Social Machines ◽  
New Phase

AbstractSocial machines are systems formed by material and human elements interacting in a structured way. The use of digital platforms as mediators allows large numbers of humans to participate in such machines, which have interconnected AI and human components operating as a single system capable of highly sophisticated behaviour. Under certain conditions, such systems can be understood as autonomous goal-driven agents. Many popular online platforms can be regarded as instances of this class of agent. We argue that autonomous social machines provide a new paradigm for the design of intelligent systems, marking a new phase in AI. After describing the characteristics of goal-driven social machines, we discuss the consequences of their adoption, for the practice of artificial intelligence as well as for its regulation.

Ambient Intelligence

2010 ◽  
pp. 121-128 ◽  
Author(s):  
Fariba Sadri ◽  
Kostas Stathis
Keyword(s):  
Artificial Intelligence ◽  
Sensor Networks ◽  
Independent Living ◽  
Intelligent Systems ◽  
Ambient Intelligence ◽  
Language Translation ◽  
Portable Devices ◽  
New Paradigm ◽  
Advisory Groups ◽  
Contextual Reasoning

In recent years much research and development effort has been directed towards the broad field of ambient intelligence (AmI), and this trend is set to continue for the foreseeable future. AmI aims at seamlessly integrating services within smart infrastructures to be used at home, at work, in the car, on the move, and generally in most environments inhabited by people. It is a relatively new paradigm rooted in ubiquitous computing, which calls for the integration and convergence of multiple disciplines, such as sensor networks, portable devices, intelligent systems, humancomputer and social interactions, as well as many techniques within artificial intelligence, such as planning, contextual reasoning, speech recognition, language translation, learning, adaptability and temporal and hypothetical reasoning. The term AmI was coined by the European Commission, when in 2001 one of its Programme Advisory Groups launched the AmI challenge (Ducatel et al., 2001), later updated in 2003 (Ducatel et al., 2003). But although the term AmI originated from Europe, the goals of the work have been adopted worldwide, see for example (The Aware Home, 2007), (The Oxygen Project, 2007), and (The Sony Interaction Lab, 2007). The foundations of AmI infrastructures are based on the impressive progress we are witnessing in wireless technologies, sensor networks, display capabilities, processing speeds and mobile services. These developments help provide much useful (row) information for AmI applications. Further progress is needed in taking full advantage of such information in order to provide the degree of intelligence, flexibility and naturalness envisaged. This is where artificial intelligence and multi-agent techniques have important roles to play. In this paper we will review the progress that has been made in intelligent systems, discuss the role of artificial intelligence and agent technologies and focus on the application of AmI for independent living.

Ambient Intelligence

2011 ◽  
pp. 85-91 ◽  
Author(s):  
Fariba Sadri ◽  
Kostas Stathis
Keyword(s):  
Artificial Intelligence ◽  
Sensor Networks ◽  
Independent Living ◽  
Intelligent Systems ◽  
Ambient Intelligence ◽  
Language Translation ◽  
Portable Devices ◽  
New Paradigm ◽  
Advisory Groups ◽  
Contextual Reasoning

In recent years much research and development effort has been directed towards the broad field of ambient intelligence (AmI), and this trend is set to continue for the foreseeable future. AmI aims at seamlessly integrating services within smart infrastructures to be used at home, at work, in the car, on the move, and generally in most environments inhabited by people. It is a relatively new paradigm rooted in ubiquitous computing, which calls for the integration and convergence of multiple disciplines, such as sensor networks, portable devices, intelligent systems, human-computer and social interactions, as well as many techniques within artificial intelligence, such as planning, contextual reasoning, speech recognition, language translation, learning, adaptability, and temporal and hypothetical reasoning. The term AmI was coined by the European Commission, when in 2001 one of its Programme Advisory Groups launched the AmI challenge (Ducatel et al., 2001), later updated in 2003 (Ducatel et al., 2003). But although the term AmI originated from Europe, the goals of the work have been adopted worldwide, see for example (The Aware Home, 2007), (The Oxygen Project, 2007), and (The Sony Interaction Lab, 2007). The foundations of AmI infrastructures are based on the impressive progress we are witnessing in wireless technologies, sensor networks, display capabilities, processing speeds and mobile services. These developments help provide much useful (row) information for AmI applications. Further progress is needed in taking full advantage of such information in order to provide the degree of intelligence, flexibility and naturalness envisaged. This is where artificial intelligence and multi-agent techniques have important roles to play. In this paper we will review the progress that has been made in intelligent systems, discuss the role of artificial intelligence and agent technologies and focus on the application of AmI for independent living.

Intelligent Pervasive Middleware for Context-Aware Vehicle Services

2011 ◽  
Vol 2 (3) ◽  
pp. 7
Author(s):  
M. Madkour ◽  
A. Maach
Keyword(s):  
Intelligent Transportation Systems ◽  
Traffic Congestion ◽  
Intelligent Systems ◽  
Engine Performance ◽  
Transportation Systems ◽  
Vital Role ◽  
Context Aware ◽  
New Paradigm ◽  
Context Aware Service ◽  
Service Framework

Transportation of goods and people plays a vital role in the lives of everyone and in virtually all businesses on earth accordingly the demand on our overburdened transportation system is increasing every day . The traffic congestion multiplies the effects of individual variations in driving performance as determined by physical abilities, knowledge, experience and, indeed, personality. We lose control over our plans and schedules; we rush because we're late; we cause accidents through recklessness and bad temper...In other hand The Intelligent Car initiative is an attempt to move towards a new paradigm, one where cars dont crash anymore, and traffic congestion is drastically reduced, Intelligent systems can support drivers to avoid accidents, optimise engine performance, reduce travel times, enhance efficiency and confort, increase productivity, improve road safety, raise management perfomance ...For intelligent transportation systems to reach their true potential we need an environment in which innovative and flexible services can be developed and delivered cost- effectively, to drivers and vehicles.Today building context-aware services is a complex and time consuming task. We present a Vehicle Context-Aware Service Framework architecture for the building and rapid prototyping of context aware vehicle services.We propose a simple and dynamique data-model which supports context acquiring and processing, semantic representing, context reasoning and cooperating sensing( sharing knowledge, resolving sensors conflicts...).The Vehicle Context-Aware Service Framework objective is to support vehicles users with personalized services. Our framework offers mechanisms to deliver vehicle diagnostic and maintenance services, Location and time Based Services, and also it suggests other services based on context-aware information, It provides them in a personalized and an adaptive manner to the user.

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