1,721,096 research outputs found
An Agent-based Framework for Indoor Navigation in Blended Shopping
No full textIn this paper we propose an advanced computational intelligence solution for an an Agent-based framework for implementing blended shopping scenarios. The proposed solution meets needs recently arose in Ubiquitous Computing and Pervasive Computing as well. The work focuses on the definition of an Indoor Navigation System that guides shoppers in a shopping mall, towards the shops providing the most suitable offerings for them, in a given time window. Such system is based on a distributed algorithm that runs on a network of intelligent cells sensing both shoppers and offerings by means of the sensor devices deployed in the mall
An ontology-driven context-aware recommender system for indoor shopping based on cellular automata
No full textSupporting Seamless Learning with Semantic Technologies and Situation Awareness
No full textThe goal of this work is to propose and motivate the usage of Linked Data (realized by means of the Semantic Web Stack) and Situation Awareness techniques in order to support Seamless Learning scenarios. In particular, Linked Data and Semantic Web technologies and methodologies are considered very useful to model and support the continuity of the seamless experience across heterogeneous (in quality, time and space) learning activities. Moreover, Situation Awareness and, in particular, Situation Recognition techniques can be exploited to sustain enhanced forms of ubiquitous access to learning resources and services which enable the improvement of the learning environment by using context-specific elements
A multi-agent fuzzy consensus model in a Situation Awareness framework
Full text linkIn order to define systems enabling the automatic identification of occurring situations, numerous approaches employing intelligent software agents to analyse data coming from deployed sensors have been proposed. Thus, it is possible that more agents are committed to monitor the same phenomenon in the same environment. Redundancy of sensors and agents is needed, for instance, in real world applications in order to mitigate the risk of faults and threats. One of the possible side effects produced by redundancy is that agents, observing the same phenomenon, could provide discordant opinions. Indeed, solid mechanisms for reaching an agreement among these agents and produce a shared consensus on the same observations are needed. This paper proposes an approach to integrate a fuzzy-based consensus model into a Situation Awareness framework. The main idea is to consider intelligent agents as experts claiming their opinions (preferences) on a phenomenon of interest
Corrigendum to “An approach based on semantic stream reasoning to support decision processes in smart cities” [Telemat. Informat. 35 (1) (2018) 68–81](S0736585317304768)(10.1016/j.tele.2017.09.019)
No full textThe authors regret that, in the work “An approach based on semantic stream reasoning to support decision processes in smart cities”, Telematics and Informatics (https://doi.org/10.1016/j.tele.2017.09.019), the name of the fourth author Antonio Simonetti has not been reported in the string of authors but erroneously only in acknowledgements. Thus, the correct string of authors and their affiliations are shown above. The authors would like to apologise for any inconvenience caused
An Adaptive System Based on Situation Awareness for Goal-Driven Management in Container Terminals
No full textLack of situation awareness when dealing with complex dynamic environments is recognized as one of the main causes of human errors that may lead to serious incidents, poor performance, etc. Thus, there
is a need to define systems able to support operators in focusing their attention on active goals and, when really needed, switching them on more suitable goals, in a sort of continuous adaptation. This paper proposes an adaptive goal selection approach capable of suggesting the goal on which human operators should focus their attention to maintain an adequate level of situation awareness. The approach has been implemented in a Decision Support System for the management of operations in a port container terminal. An evaluation of the system applied to the container terminal of Salerno (Italy) has been realized by using the Situation Awareness Global Assessment Technique (SAGAT), a well-known methodology for evaluating SA in operational contexts. An evaluation of the performance has been executed to demonstrate that the approach helps to improve the performance of the logistics operation
An AmI-based and privacy-preserving shopping mall model
No full textNowadays, large shopping malls provide tools to help and boost customers to buy products. Some of these tools melt down digital operations with physical ones executed by customers into blended commerce experiences. On the other hand, ambient intelligence (AmI) represents a paradigm focused on equipping physical environments to define ergonomic spaces for people interacting with computer-based localized services which are ubiquitously accessible. In this context, we propose a framework based on cellular automata (CA), a very well known formal computational model, suitable to abstract services deployed into an AmI-based environment preserving certain privacy levels of shoppersâ information. CA-based algorithms are advantageous because they are distributed, scalable, on-line and require low costs to be deployed. This work proposes a recent application of CA, namely Cellular ANTomata, to implement a service by which shoppers are guided to find the suitable offerings for items in their shopping lists. A further result provided by this paper is the instantiation of a protocol for privacy-preserving shopping experience in the shopping mall
A private Intelligent Shopping Mall
No full textIn this paper we extend a previous recent work on Ambient Intelligence, deployed into a scenario of Intelligence Shopping Malls, with a privacy layer. In fact nowadays, in the Ambient Intelligence context, privacy issues are more and more considered an urgent and main issue to take care of. The success of this permeated ubiquitous intelligence seems to be strongly correlated to how much the scenario is able to protect the privacy and the rights of the users. The Intelligence Shopping Mall is a physical environment for commerce equipped with sensors and actuators for supporting shoppers. These latters have a wish list of the items to buy. Once in the mall, the wish list should be disclosed to steer the shopper towards the right shop selling the wished item. Anyway, from shops' point of view, shopping lists contain valuable information about shoppers. Indeed, from shopping lists one could easily infer users' personal preferences or tendency (e.g., users' lifestyle) that could be used for marketing purpose. Hence, shopping lists could reveal shoppers' sensitive information. In this paper, to preserve the shoppers' privacy without limiting the possibility to guide users towards shops selling the sought products, we propose an efficient and efficacious privacy preserving protocol. Using such a protocol, shops can steer shoppers towards the shops selling the desired items without knowing the items in their shopping lists (excluding the items bought in the shop itself)
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