Search results for "Wireless Sensor Network"
showing 10 items of 363 documents
An Ambient Intelligence Architecture for Extracting Knowledge from Distributed Sensors
2009
Precisely monitoring the environmental conditions is an essential requirement for AmI projects, but the wealth of data generated by the sensing equipment may easily overwhelm the modules devoted to higher-level reasoning, clogging them with irrelevant details. The present work proposes a new approach to knowledge extraction from raw data that addresses this issue at different levels of abstraction. Wireless sensor networks 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 represented in a geometrical space and carries on symbolic re…
Exploiting the Human Factor in a WSN-Based System for Ambient Intelligence
2009
Practical applications of ambient intelligence cannot leave aside requirements about ubiquity, scalability, and transparency to the user. An enabling technology to comply with this goal is represented by wireless sensor networks (WSNs); however, although capable of limited in-network processing, they lack the computational power to act as a comprehensive intelligent system. By taking inspiration from the sensory processing model of complex biological organisms, we propose here a cognitive architecture able to perceive, decide upon, and control the environment of which the system is part. WSNs act as a transparent interface that allows the system to understand human requirements through impl…
Design of an Adaptive Bayesian System for Sensor Data Fusion
2014
Many artificial intelligent systems exploit a wide set of sensor devices to monitor the environment. When the sensors employed are low-cost, off-the-shelf devices, such as Wireless Sensor Networks (WSN), the data gathered through the sensory infrastructure may be affected by noise, and thus only partially correlated to the phenomenon of interest. One way of overcoming these limitations might be to adopt a high-level method to perform multi-sensor data fusion. Bayesian Networks (BNs) represent a suitable tool for performing refined artificial reasoning on heterogeneous sensory data, and for dealing with the intrinsic uncertainty of such data. However, the configuration of the sensory infrast…
Short-Term Sensory Data Prediction in Ambient Intelligence Scenarios
2014
Predicting data is a crucial ability for resource-constrained devices like the nodes of a Wireless Sensor Network. In the context of Ambient Intelligence scenarios, in particular, short-term sensory data prediction becomes a key enabler for more difficult tasks such as prolonging network lifetime, reducing the amount of communication required and improving user-environment interaction. In this chapter we propose a software module designed for clustered wireless sensor networks, able to predict various environmental quantities, namely temperature, humidity and light. The software module is supported by an ontology that describes the topology of the AmI scenario and the effects of the actuato…
An Adaptive Bayesian System for Context-Aware Data Fusion in Smart Environments
2017
The adoption of multi-sensor data fusion techniques is essential to effectively merge and analyze heterogeneous data collected by multiple sensors, pervasively deployed in a smart environment. Existing literature leverages contextual information in the fusion process, to increase the accuracy of inference and hence decision making in a dynamically changing environment. In this paper, we propose a context-aware, self-optimizing, adaptive system for sensor data fusion, based on a three-tier architecture. Heterogeneous data collected by sensors at the lowest tier are combined by a dynamic Bayesian network at the intermediate tier, which also integrates contextual information to refine the infe…
Detection of User Activities in Intelligent Environments
2014
Research on Ambient Intelligence (AmI) focuses on the development of smart environments adaptable to the needs and preferences of their inhabitants. For this reason it is important to understand and model user preferences. In this chapter we describe a system to detect user behavior patterns in an intelligent workplace. The system is designed for a workplace equipped in the context of Sensor9k, a project carried out at the Department of Computer Science at the University of Palermo (Italy). © Springer International Publishing Switzerland 2014.
Extracting Structured Knowledge From Sensor Data for Hybrid Simulation
2014
Obtaining continuous and detailed monitoring of indoor environments has today become viable, also thanks to the widespread availability of effective and flexible sensing technology; this paves the way for the design of practical Ambient Intelligence systems, and for their actual deployment in real-life contexts, which require advanced functionalities, such as for instance the automatic discovery of the activities carried on by users. Novel issues arise in this context; on one hand, it is important to reliably model the phenomena under observation even though, to this end, it is often necessary to craft a carefully designed prototype in order to test and fine-tune the theoretical models.
SmartBuildings: An AmI system for energy efficiency
2015
Nowadays, the increasing global awareness of the importance of energy saving in everyday life acts as a stimulus to provide innovative ICT solutions for sustainability. In this scenario, the growing interest in smart homes has been driven both by socioeconomic and technological expectations. One of the key aspects of being smart is the efficiency of the urban apparatus, which includes, among others, energy, transportation and buildings. The present work describes SmartBuildings, a novel Ambient Intelligence system, which aims at reducing the energy consumption of "legacy" buildings by means of artificial intelligence techniques applied on heterogeneous sensor networks. A prototype has been …
Human-ambient interaction through Wireless Sensor Networks
2009
Recent developments in technology have permitted the creation of cheap, and unintrusive devices that may be effectively employed for instrumenting an intelligent environment. The present work describes a modular framework that makes use of a class of those devices, namely wireless sensors, in order to monitor relevant physical quantities and to collect users' requirements through implicit feedback. A central intelligent unit extracts higher-level concepts from raw sensory inputs, and carries on symbolic reasoning based on them. 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 b…
A Hybrid Framework for Soft Real-Time WSN Simulation
2009
The design of a wireless sensor network is a chal- lenging task due to its intrinsically application-specific nature. Although a typical choice for testing such kind of networks requires devising ad-hoc testbeds, this is often impractical as it depends on expensive, and hard to maintain deployment of nodes. On the other hand, simulation is a valuable option, as long as the actual functioning conditions are reliably modeled, and carefully replicated. The present work describes a framework for supporting the user in early design and testing of a wireless sensor network with an augmented version of TOSSIM, the de-facto standard for simulators, that allows merging actual and virtual nodes seaml…