1,720,971 research outputs found
A low cost smart glove for visually impaired people mobility
No full textDegradation of the visual system reduces the mobility of a person that relies only on his sense of touch and hearing. This paper presents the prototype of a low cost smart glove to improve the mobility of the visually impaired people. The glove is equipped with rangefinders to explore the surroundings: it provides a vibro-tactile feedback on the position of the closest obstacles in range by means of vibration motors. The system is designed to operate with the white cane, enhancing the reliability of this traditional tool
Augmenting white cane reliability using smart glove for visually impaired people
No full textThe independent mobility problem of visually impaired people has been an active research topic in biomedical engineering: although many smart tools have been proposed, traditional tools (e.g., the white cane) continue to play a prominent role. In this paper a low cost smart glove is presented: the key idea is to minimize the impact in using it by combining the traditional tools with a technological device able to improve the movement performance of the visually impaired people
Hybrid map building for personal indoor navigation systems
No full textTracking the positions of people in large indoor spaces is important, since it enables a range of applications related to security, indoor navigation and guidance. This paper proposes a personal indoor navigation system based on hybrid map, containing geometric as well as symbolic information. In this way the same map can be exploited to guide and localise the user efficiently during navigation. The hybrid map is built using floor plans of the environment. It is a topological graph capturing the connectivity of complex indoor environment and it is retrieved by applying image-processing techniques. Some additional metric information are added to make the map suitable for quantitative localisation. Semantic features are considered to improve user readability
Hybrid Indoor Positioning System for First Responders
Full text linkIn the last decade, many efforts have been devoted to indoor localization and positioning. In this paper, a hybrid indoor localization system has been developed within the European project REFIRE for emergency situations. The REFIRE solution estimates the user's pose according to a prediction-correction scheme. The user is equipped with a waist-mounted inertial measurement unit and a radio frequency identification (RFID) reader. In the correction phase, the estimation is updated by means of geo-referenced information fetched from passive RFID tags predeployed into the environment. Accurate position correction is obtained through a deep analysis of the RFID system radiation patterns. To this end, extensive experimental trials have been performed to assess the RFID system performance, both in static and dynamic operating conditions. Experimental validation in realistic environments shows the effectiveness of the proposed indoor localization system, even during long-last missions and/or using a limited number of tags
Finding critical nodes in infrastructure networks
No full textIt is well known that profiling attacker behavior is an effective way to obtain insights into network attacks and to identify the systems and components that must be protected. This paper presents a novel integer linear programming formulation that models the strategy of an attacker who targets a set of nodes with the goal of compromising or destroying them. The attacker model considers the infliction of the greatest possible damage with minimal attacker effort. Specifically, it is assumed that the attacker is guided by three conflicting objectives: (i) maximization of the number of disconnected components; (ii) minimization of the size of the largest connected component; and (iii) minimization of the attack cost. Compared with other research in the area, the proposed formulation is much more descriptive but has less complexity; thus, it is very useful for predicting attacks and identifying the entities that must be protected. Since exact solutions of the formulation are computationally expensive for large problems, a heuristic algorithm is presented to obtain approximate solutions. Simulation results using a U.S. airport network dataset demonstrate the effectiveness and utility of the proposed approach
Performance Analysis of Single and Multi-objective Approaches for the Critical Node Detection Problem
No full textCritical infrastructures are network-based systems which are prone to various types of threats (e.g., terroristic or cyber-attacks). Therefore, it is paramount to devise modelling frameworks to assess their ability to withstand external disruptions and to develop protection strategies aimed at improving their robustness and security. In this paper, we compare six modelling approaches for identifying the most critical nodes in infrastructure networks. Three are well-established approaches in the literature, while three are recently proposed frameworks. All the approaches take the perspective of an attacker whose ultimate goal is to inflict maximum damage to a network with minimal effort. Specifically, they assume that a saboteur must decide which nodes to disable so as to disrupt network connectivity as much as possible. The formulations differ in terms of the attacker objectives and connectivity metrics (e.g., trade-off between inflicted damage and attack cost, pair-wise connectivity, size and number of disconnected partitions). We apply the six formulations to the IEEE24 and IEEE118 Power Systems and conduct a comparative analysis of the solutions obtained with different parameters settings. Finally, we use frequency analysis to determine the most critical nodes with respect to different attack strategies
Critical node detection based on attacker preferences
No full textThe identification of Critical Nodes in technological, biological and social networks is a fundamental task in order to comprehend the behavior of such networks and to implement protection or intervention strategies aimed at reducing the network vulnerability. In this paper we focus on the perspective of an attacker that aims at disconnecting the network in several connected components, and we provide a formulation of the attacker behavior in terms of an optimization problem with two concurrent objectives: maximizing the damage dealt while minimizing the cost or effort of the attack. Such objectives are mediated according to the subjective preferences of the attacker. Specifically, the attacker identifies a set of nodes to be removed in order to disconnect the network in at least m connected components; the final objective is from one side to minimize the number of attacked nodes, and from another side to minimize the size of the largest connected component. We complement the paper by providing an heuristic approach to calculate an admissible solution to the problem at hand, based on the line graph of the original network topology and on the spectral clustering methodology
ZADIG: A novel Extended Detection and Response System
No full textThis paper introduces ZADIG XDR, an innovative Extended Detection and Response system designed to enhance real-time anomaly detection, response, and prevention. Using advanced artificial intelligence and machine learning techniques, the system is able to evaluate anomalous events and predict their recurrence. ZADIG XDR's modular architecture allows for extensive customization, supporting targeted and effective protection. The system's efficient proprietary data ingestion pipeline, based on multiple tools such as Zeek, Kafka, Logstash, ElasticSearch, and a fork of LoudML: ZADIG AI, maintained by bitCorp, automates data collection, processing, and storage, ensuring seamless integration of multiple sources for in-depth security analysis. ZADIG XDR's robustness and flexibility in detecting anomalies and mitigating advanced cyber threats are then demonstrated through a simulation of multiple attack scenarios: Man-in-the-Middle, Denial of Service, and Scanning attacks
Indoor positioning system using walking pattern classification
No full textIn the age of automation the ability to navigate persons and devices in indoor environments has become increasingly important for a rising number of applications. While Global Positioning System can be considered a mature technology for outdoor localization, there is no off-the-shelf solution for indoor tracking. In this contribution, an infrastructure-less Indoor Positioning System based on walking feature detection is presented. The proposed system relies on the differences characterizing different human actions (e.g., walking, ascending or descending stairs, taking the elevator). The motion features are extracted in time domain by exploiting data provided by a 9DoF Inertial Measurement Unit. The positioning algorithm is based on walking distance and heading estimation. Step count and step length are used to determine the walking distance, while the heading is computed by quaternions. An experimental setup has been developed. The collected results show that system guarantee room level accuracy during long trials
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