5,150 research outputs found
Intelligent training in control centres based on an ambient intelligence paradigm
This article describes a new approach in the Intelligent Training of Operators in Power Systems Control Centres, considering the new reality of Renewable Sources, Distributed Generation, and Electricity Markets, under the emerging paradigms of Cyber-Physical Systems and Ambient Intelligence. We propose Intelligent Tutoring Systems as the approach to deal with the intelligent training of operators in these new circumstances
Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms
The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications
Attribute Identification and Predictive Customisation Using Fuzzy Clustering and Genetic Search for Industry 4.0 Environments
Today´s factory involves more services and customisation. A paradigm shift is towards “Industry 4.0” (i4) aiming at realising mass customisation at a mass production cost. However, there is a lack of tools for customer informatics. This paper addresses this issue and develops a predictive analytics framework integrating big data analysis and business informatics, using Computational Intelligence (CI). In particular, a fuzzy c-means is used for pattern recognition, as well as managing relevant big data for feeding potential customer needs and wants for improved productivity at the design stage for customised mass production. The selection of patterns from big data is performed using a genetic algorithm with fuzzy c-means, which helps with clustering and selection of optimal attributes. The case study shows that fuzzy c-means are able to assign new clusters with growing knowledge of customer needs and wants. The dataset has three types of entities: specification of various characteristics, assigned insurance risk rating, and normalised losses in use compared with other cars. The fuzzy c-means tool offers a number of features suitable for smart designs for an i4 environment
Pull control for Job Shop: Holonic Manufacturing System approach using multicriteria decision-making
International audienceFaced with international competition, industrial production increasingly requires implementation conditions which, in some cases, lead to seek new techniques for workshop control. This is the case when it is asked to establish Just in Time management in a Job Shop having the characteristics of working with small series. A new approach for the organization of the ‘control’ function in such a context is presented here. This approach relies on the use of the holonic paradigm on an isoarchic architecture and on a decision-making capacity based on a multicriteria analysis. The various concepts of this approach are addressed first. Then, the multicriteria decision mechanisms that are used are detailed, as well as the implementation and instrumentation phases. The first results that were obtained are presented
Case-based reasoning decision making in ambient assisted living
Series : Lecture Notes in Computer Science, vol. 5518Quality on the welfare services in caring, and the trend to minimize the economical
and social-political costs that come with such practice, due to the population aging, are
paramount nowadays, i.e., health care reform has become the leading policy issue in all
latitudes. Indeed, the major thrust of all this research is the perception that escalating costs
make the current structure and financing of health care unsustainable. The issue of
sustainability is, therefore, the main subject of this paper. As a result, and in order to
accomplish this goal, we decided to look to the problem from an user perspective, i.e., the
system not only will provide different services, but will be also able to trace the ones more
frequently used and to learn about the context in which they happen. As a result, we will have a
system that will act and learn according to the preferences and habits of its users, and,
simultaneously, will adapt to the environment with the objective of reducing the cost of its
practices
How 5G wireless (and concomitant technologies) will revolutionize healthcare?
The need to have equitable access to quality healthcare is enshrined in the United Nations (UN) Sustainable Development Goals (SDGs), which defines the developmental agenda of the UN for the next 15 years. In particular, the third SDG focuses on the need to “ensure healthy lives and promote well-being for all at all ages”. In this paper, we build the case that 5G wireless technology, along with concomitant emerging technologies (such as IoT, big data, artificial intelligence and machine learning), will transform global healthcare systems in the near future. Our optimism around 5G-enabled healthcare stems from a confluence of significant technical pushes that are already at play: apart from the availability of high-throughput low-latency wireless connectivity, other significant factors include the democratization of computing through cloud computing; the democratization of Artificial Intelligence (AI) and cognitive computing (e.g., IBM Watson); and the commoditization of data through crowdsourcing and digital exhaust. These technologies together can finally crack a dysfunctional healthcare system that has largely been impervious to technological innovations. We highlight the persistent deficiencies of the current healthcare system and then demonstrate how the 5G-enabled healthcare revolution can fix these deficiencies. We also highlight open technical research challenges, and potential pitfalls, that may hinder the development of such a 5G-enabled health revolution
Future bathroom: A study of user-centred design principles affecting usability, safety and satisfaction in bathrooms for people living with disabilities
Research and development work relating to assistive technology
2010-11 (Department of Health)
Presented to Parliament pursuant to Section 22 of the Chronically Sick and Disabled Persons Act 197
Sensor Networks in the Low Lands
This paper provides an overview of scientific and industrial developments of the last decade in the area of sensor networks in The Netherlands (Low Lands). The goal is to highlight areas in which the Netherlands has made most contributions and is currently a dominant player in the field of sensor networks. On the one hand, motivations, addressed topics, and initiatives taken in this period are presented, while on the other hand, special emphasis is given to identifying current and future trends and formulating a vision for the coming five to ten years. The presented overview and trend analysis clearly show that Dutch research and industrial efforts, in line with recent worldwide developments in the field of sensor technology, present a clear shift from sensor node platforms, operating systems, communication, networking, and data management aspects of the sensor networks to reasoning/cognition, control, and actuation
A COGNITIVE ARCHITECTURE FOR AMBIENT INTELLIGENCE
L’Ambient Intelligence (AmI) è caratterizzata dall’uso di sistemi pervasivi per
monitorare l’ambiente e modificarlo secondo le esigenze degli utenti e rispettando
vincoli definiti globalmente. Questi sistemi non possono prescindere da requisiti
come la scalabilità e la trasparenza per l’utente. Una tecnologia che consente di
raggiungere questi obiettivi è rappresentata dalle reti di sensori wireless (WSN),
caratterizzate da bassi costi e bassa intrusività. Tuttavia, sebbene in grado di
effettuare elaborazioni a bordo dei singoli nodi, le WSN non hanno da sole le capacità
di elaborazione necessarie a supportare un sistema intelligente; d’altra parte
senza questa attività di pre-elaborazione la mole di dati sensoriali può facilmente
sopraffare un sistema centralizzato con un’eccessiva quantità di dettagli superflui.
Questo lavoro presenta un’architettura cognitiva in grado di percepire e controllare
l’ambiente di cui fa parte, basata su un nuovo approccio per l’estrazione
di conoscenza a partire dai dati grezzi, attraverso livelli crescenti di astrazione.
Le WSN sono utilizzate come strumento sensoriale pervasivo, le cui capacità computazionali
vengono utilizzate per pre-elaborare i dati rilevati, in modo da consentire
ad un sistema centralizzato intelligente di effettuare ragionamenti di alto
livello.
L’architettura proposta è stata utilizzata per sviluppare un testbed dotato degli
strumenti hardware e software necessari allo sviluppo e alla gestione di applicazioni
di AmI basate su WSN, il cui obiettivo principale sia il risparmio energetico. Per
fare in modo che le applicazioni di AmI siano in grado di comunicare con il mondo
esterno in maniera affidabile, per richiedere servizi ad agenti esterni, l’architettura
è stata arricchita con un protocollo di gestione distribuita della reputazione.
È stata inoltre sviluppata un’applicazione di esempio che sfrutta le caratteristiche
del testbed, con l’obiettivo di controllare la temperatura in un ambiente
lavorativo. Quest’applicazione rileva la presenza dell’utente attraverso un modulo
per la fusione di dati multi-sensoriali basato su reti bayesiane, e sfrutta questa
informazione in un controllore fuzzy multi-obiettivo che controlla gli attuatori sulla
base delle preferenze dell’utente e del risparmio energetico.Ambient Intelligence (AmI) systems are characterized by the use of pervasive
equipments for monitoring and modifying the environment according to users’
needs, and to globally defined constraints. Furthermore, such systems cannot ignore
requirements about ubiquity, scalability, and transparency to the user. An
enabling technology capable of accomplishing these goals is represented by Wireless
Sensor Networks (WSNs), characterized by low-costs and unintrusiveness. However,
although provided of in-network processing capabilities, WSNs do not exhibit
processing features able to support comprehensive intelligent systems; on the other
hand, without this pre-processing activities the wealth of sensory data may easily
overwhelm a centralized AmI system, clogging it with superfluous details.
This work proposes a cognitive architecture able to perceive, decide upon, and
control the environment of which the system is part, based on a new approach to
knowledge extraction from raw data, that addresses this issue at different abstraction
levels. WSNs are used as the pervasive sensory tool, and their computational
capabilities are exploited to remotely perform preliminary data processing. A central
intelligent unit subsequently extracts higher-level concepts in order to carry on
symbolic reasoning. The aim of the reasoning is to plan a sequence of actions that
will lead the environment to a state as close as possible to the users’ desires, taking
into account both implicit and explicit feedbacks from the users, while considering
global system-driven goals, such as energy saving. The proposed conceptual architecture
was exploited to develop a testbed providing the hardware and software
tools for the development and management of AmI applications based on WSNs,
whose main goal is energy saving for global sustainability. In order to make the
AmI system able to communicate with the external world in a reliable way, when
some services are required to external agents, the architecture was enriched with
a distributed reputation management protocol.
A sample application exploiting the testbed features was implemented for addressing
temperature control in a work environment. Knowledge about the user’s
presence is obtained through a multi-sensor data fusion module based on Bayesian
networks, and this information is exploited by a multi-objective fuzzy controller
that operates on actuators taking into account users’ preference and energy consumption
constraints
A Big Bang–Big Crunch Type-2 Fuzzy Logic System for Machine-Vision-Based Event Detection and Summarization in Real-World Ambient-Assisted Living
The area of ambient-assisted living (AAL) focuses on developing new technologies, which can improve the quality of life and care provided to elderly and disabled people. In this paper, we propose a novel system based on 3-D RGB-D vision sensors and interval type-2 fuzzy-logic-based systems (IT2FLSs) employing the big bang-big crunch algorithm for the real-time automatic detection and summarization of important events and human behaviors from the large-scale data. We will present several real-world experiments, which were conducted for AAL-related behaviors with various users. It will be shown that the proposed BB-BC IT2FLSs outperform the type-1 fuzzy logic system counterparts as well as other conventional nonfuzzy methods, and the performance improves when the number of subjects increases
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