1,094 research outputs found
A COGNITIVE ARCHITECTURE FOR AMBIENT INTELLIGENCE
LâAmbient Intelligence (AmI) è caratterizzata dallâuso di sistemi pervasivi per
monitorare lâambiente e modificarlo secondo le esigenze degli utenti e rispettando
vincoli definiti globalmente. Questi sistemi non possono prescindere da requisiti
come la scalabilitĂ e la trasparenza per lâutente. Una tecnologia che consente di
raggiungere questi obiettivi è rappresentata dalle reti di sensori wireless (WSN),
caratterizzate da bassi costi e bassa intrusivitĂ . Tuttavia, sebbene in grado di
effettuare elaborazioni a bordo dei singoli nodi, le WSN non hanno da sole le capacitĂ
di elaborazione necessarie a supportare un sistema intelligente; dâaltra parte
senza questa attività di pre-elaborazione la mole di dati sensoriali può facilmente
sopraffare un sistema centralizzato con unâeccessiva quantitĂ di dettagli superflui.
Questo lavoro presenta unâarchitettura cognitiva in grado di percepire e controllare
lâambiente di cui fa parte, basata su un nuovo approccio per lâestrazione
di conoscenza a partire dai dati grezzi, attraverso livelli crescenti di astrazione.
Le WSN sono utilizzate come strumento sensoriale pervasivo, le cui capacitĂ computazionali
vengono utilizzate per pre-elaborare i dati rilevati, in modo da consentire
ad un sistema centralizzato intelligente di effettuare ragionamenti di alto
livello.
Lâarchitettura 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, lâarchitettura
è stata arricchita con un protocollo di gestione distribuita della reputazione.
Ă stata inoltre sviluppata unâapplicazione di esempio che sfrutta le caratteristiche
del testbed, con lâobiettivo di controllare la temperatura in un ambiente
lavorativo. Questâapplicazione rileva la presenza dellâutente 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 dellâutente e del risparmio energetico.Ambient Intelligence (AmI) systems are characterized by the use of pervasive
equipments for monitoring and modifying the environment according to usersâ
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 usersâ 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 userâs
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 usersâ preference and energy consumption
constraints
Internet of things
Manual of Digital Earth / Editors: Huadong Guo, Michael F. Goodchild, Alessandro Annoni .- Springer, 2020 .- ISBN: 978-981-32-9915-3Digital Earth was born with the aim of replicating the real world within the digital world. Many efforts have been made to observe and sense the Earth, both from space (remote sensing) and by using in situ sensors. Focusing on the latter, advances in Digital Earth have established vital bridges to exploit these sensors and their networks by taking location as a key element. The current era of connectivity envisions that everything is connected to everything. The concept of the Internet of Things(IoT)emergedasaholisticproposaltoenableanecosystemofvaried,heterogeneous networked objects and devices to speak to and interact with each other. To make the IoT ecosystem a reality, it is necessary to understand the electronic components, communication protocols, real-time analysis techniques, and the location of the objects and devices. The IoT ecosystem and the Digital Earth (DE) jointly form interrelated infrastructures for addressing todayâs pressing issues and complex challenges. In this chapter, we explore the synergies and frictions in establishing an efďŹcient and permanent collaboration between the two infrastructures, in order to adequately address multidisciplinary and increasingly complex real-world problems. Although there are still some pending issues, the identiďŹed synergies generate optimism for a true collaboration between the Internet of Things and the Digital Earth
A Tree-based Hierarchy Data Storage Framework in a Pervasive Space
Context data is important information for catching the behaviors of applications in a pervasive space. To effectively store huge amount of data, tree-like layered storage architecture is proposed, where the leaf nodes collect data from sensing devices. In order to integrate data from mobile devices, the related leaf nodes that get data from the same device should upload and store the data to the host node. This paper presents a deep study of the data storage problem and proposes a global algorithm GHS and an online algorithm DHS to dynamically select the host node, which reduces the communication cost significantly. This paper also gives the theoretical and experimental analysis of these algorithms, which shows both GHS and DHS are correct and effective
Ubiquitous and context-aware computing modelling : study of devices integration in their environment
Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Information Systems and Technologies ManagementIn an almost imperceptible way, ubiquitous and context-aware computing make part
of our everyday lives, as the world has developed in an interconnected way between
humans and technological devices. This interconnectedness raises the need to
integrate humansâ interaction with the different devices they use in different social
contexts and environments. In the proposed research, it is suggested the
development of new scenario building based on a current ubiquitous computing
model dedicated to the environment context-awareness. We will also follow previous
research made on the formal structure computation model based on social paradigm
theory, dedicated to embed devices into different context environments with social
roles developed by Santos (2012/2015). Furthermore, several socially relevant context
scenarios are to be identified and studied. Once identified, we gather and document
the requirements that devices should have, according to the model, in order to
achieve a correct integration in their contextual environment
A DHT-Based Discovery Service for the Internet of Things
Current trends towards the Future Internet are envisaging the conception of novel services endowed with context-aware and autonomic capabilities to improve end users' quality of life. The Internet of Things paradigm is expected to contribute towards this ambitious vision by proposing models and mechanisms enabling the creation of networks of "smart things" on a large scale. It is widely recognized that efficient mechanisms for discovering available resources and capabilities are required to realize such vision. The contribution of this work consists in a novel discovery service for the Internet of Things. The proposed solution adopts a peer-to-peer approach for guaranteeing scalability, robustness, and easy maintenance of the overall system. While most existing peer-to-peer discovery services proposed for the IoT support solely exact match queries on a single attribute (i.e., the object identifier), our solution can handle multiattribute and range queries. We defined a layered approach by distinguishing three main aspects: multiattribute indexing, range query support, peer-to-peer routing. We chose to adopt an over-DHT indexing scheme to guarantee ease of design and implementation principles. We report on the implementation of a Proof of Concept in a dangerous goods monitoring scenario, and, finally, we discuss test results for structural properties and query performance evaluation
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