Search results for " Network"
showing 10 items of 6428 documents
A Knowledge Management System using Bayesian Network
2009
In today's world, decision support and knowledge management processes are strategic and interdependent activities in many organizations. The companies' interest on a correct knowledge management is grown, more than interest on the mere knowledge itself. This paper proposes a Knowledge Management System based on Bayesian networks. The system has been tested collecting and using data coming from projects and processes typical of ICT companies, and provides a Document Management System and a Decision Support system to share documents and to plan how to best use firms' knowledge.
Towards a deep-learning-based methodology for supporting satire detection
2021
This paper describes an approach for supporting automatic satire detection through effective deep learning (DL) architecture that has been shown to be useful for addressing sarcasm/irony detection problems. We both trained and tested the system exploiting articles derived from two important satiric blogs, Lercio and IlFattoQuotidiano, and significant Italian newspapers.
Path Modeling and Retrieval in Distributed Video Surveillance Databases
2012
We propose a framework for querying a distributed database of video surveillance data in order to retrieve a set of likely paths of a person moving in the area under surveillance. In our framework, each camera of the surveillance system locally pro- cesses the data and stores video sequences in a storage unit and the metadata for each detected person in the distributed database. A pedestrian’s path is formulated as a dynamic Bayesian network (DBN) to model the dependencies between subsequent observa- tions of the person as he makes his way through the camera net- work. We propose a tool by which the analyst can pose queries about where a certain person appeared while moving in the site duri…
DC4CD
2017
In this article, we present Distributed Computing for Constrained Devices (DC4CD), a novel software architecture that supports symbolic distributed computing on wireless sensor networks. DC4CD integrates the functionalities of a high-level symbolic interpreter, a compiler, and an operating system, and includes networking abstractions to exchange high-level symbolic code among peer devices. Contrarily to other architectures proposed in the literature, DC4CD allows for changes at runtime, even on deployed nodes of both application and system code. Experimental results show that DC4CD is more efficient in terms of memory usage than existing architectures, with which it also compares well in te…
Multisensor Data Fusion in Pervasive Artificial Intelligence Systems
Intelligent systems designed to manage smart environments exploit numerous sensing and actuating devices, pervasively deployed so as to remain invisible to users and subtly learn their preferences and satisfy their needs. Nowadays, such systems are constantly evolving and becoming ever more complex, so it is increasingly difficult to develop them successfully. A possible solution to this problem might lie in delegating certain decisions to the machines themselves, making them more autonomous and able to self-configure and self-manage. This work presents a multi-tier architecture for a complete pervasive system capable of understanding the state of the surrounding environment, as well as usi…
Robust Data Gathering for Wireless Sensor Networks
2006
2005 13th IEEE International Conference on Networks jointly held with the 2005 7th IEEE Malaysia International Conference on Communications, Proceedings Volume 1, 2005, Article number 1635527, Pages 469-474 2005 13th IEEE International Conference on Networks jointly held with the 2005 7th IEEE Malaysia International Conference on Communications; Kuala Lumpur; Malaysia; 16 November 2005 through 18 November 2005; Category number05EX1235; Code 69262 Robust data gathering for wireless sensor networks (Conference Paper) Ortolani, M. , Gatani, L. , Lo Re, G. Dipartimento di Ingegneria Informatica, Università degli Studi di Palermo, Viale delle Scienze Parco d'Orleans, 90128 Palermo, Italy View re…
DESIGN METHODOLOGIES TO ENABLE COLLECTIVE INTELLIGENCE IN PLATFORMS FOR HUMAN-HUMAN INTERACTION
2014
Context-awareness for multi-sensor data fusion in smart environments
2016
Multi-sensor data fusion is extensively used to merge data collected by heterogeneous sensors deployed in smart environments. However, data coming from sensors are often noisy and inaccurate, and thus probabilistic techniques, such as Dynamic Bayesian Networks, are often adopted to explicitly model the noise and uncertainty of data. This work proposes to improve the accuracy of probabilistic inference systems by including context information, and proves the suitability of such an approach in the application scenario of user activity recognition in a smart home environment. However, the selection of the most convenient set of context information to be considered is not a trivial task. To thi…
Programming distributed applications with symbolic reasoning on WSNs
2015
Programming Wireless Sensor Networks (WSNs) is a complex task for which existing approaches adopt rigid architectures that are only suitable for specific application fields. In previous papers we introduced a programming methodology and a lightweight middleware based on high-level programming and executable code exchange for distributed processing on WSNs. In this paper, we show how high-level programming can be effectively used on WSNs to implement symbolic reasoning. In order to prove the feasibility of our approach, we present a Fuzzy Logic system where the value updates and the rule evaluations are performed in a distributed way. Through the proposed methodology, we discuss the developm…
A Fog-Based Application for Human Activity Recognition Using Personal Smart Devices
2019
The diffusion of heterogeneous smart devices capable of capturing and analysing data about users, and/or the environment, has encouraged the growth of novel sensing methodologies. One of the most attractive scenarios in which such devices, such as smartphones, tablet computers, or activity trackers, can be exploited to infer relevant information is human activity recognition (HAR). Even though some simple HAR techniques can be directly implemented on mobile devices, in some cases, such as when complex activities need to be analysed timely, users’ smart devices can operate as part of a more complex architecture. In this article, we propose a multi-device HAR framework that exploits the fog c…