Arousal effects on Fitness-to-Drive assessment: algorithms and experiments

Several elements can affect the drivers' behaviour while they are performing driving activities. Ranging from visual to cognitive distractions, emotions and other drivers' conditions (that could emerge from biometric data, such as temperature, heartbeat, pressure, etc.) can play a significant role, performing as a factor that can increase drivers' response time. This could be crucial in avoiding dangerous situations and in deciding and performing actions that could influence the happening of car accidents. This paper introduces the concept of the "Fitness-to-Drive" index and aims to evaluate how the arousal effects can influence the drivers' status. The paper presents some experimental evaluations we have conducted on a driver simulator, discussing the obtained results

A Social Internet of Things Smart City Solution for Traffic and Pollution Monitoring in Cagliari

In the last years, the smart city paradigm has been deeply studied to support sustainable mobility and to improve human living conditions. In this context, a new smart city based on Social Internet of Things paradigm is presented in this article. Starting from the tracking of all vehicles (that is, private and public) and pedestrians, integrated with air quality measurements (that is, in real time by mobile and fixed sensors), the system aims to improve the viability of the city, both for pedestrian and vehicular users. A monitoring network based on sensors and devices hosted on board in local public transport allows real time monitoring of the most sensitive areas both from traffic congestion and from an environmental point of view. The proposed solution is equipped with an appropriate intelligence that takes into account instantaneous speed, type of traffic, and instantaneous pollution data, allowing to evaluate the congestion and pollution condition in a specific moment. Moreover, specific tools support the decisions of public administration facilitating the identification of the most appropriate actions for the implementation of effective policies relating to mobility. All collected data are elaborated in real time to improve traffic viability suggesting new directions and information to citizens to better organize how to live in the city

Virtual user in the IoT: definition, technologies and experiments

Virtualization technologies are characterizing major advancements in the Internet of Things (IoT) arena, as they allow for achieving a cyber-physical world where everything can be found, activated, probed, interconnected, and updated at both the virtual and the physical levels. We believe these technologies should apply to human users other than things, bringing us the concept of the Virtual User (VU). This should represent the virtual counterpart of the IoT users with the ultimate goal of: (i) avoiding the user from having the burden of following the tedious processes of setting, configuring and updating IoT services the user is involved in; (ii) acting on behalf of the user when basic operations are required; (iii) exploiting to the best of its ability the IoT potentialities, always taking always account the user profile and interests. Accordingly, the VU is a complex representation of the user and acts as a proxy in between the virtual objects and IoT services and application; to this, it includes the following major functionalities: user profiling, authorization management, quality of experience modeling and management, social networking and context management. In this respect, the major contributions of this paper are to: provide the definition of VU, present the major functionalities, discuss the legal issues related to its introduction, provide some implementation details, and analyze key performance aspects in terms of the capability of the VU to correctly identify the user profile and context

Alcohol-related behaviour in freshmen university students in Sardinia, Italy

This study aims to provide a picture of University of Cagliari students’ alcohol-related behaviour and to explore factors associated with it. Data were collected by administering a questionnaire to 992 freshmen university students from different programs consisting of twelve closed questions, including three questions from the Alcohol Use Disorders Identification Test for Consumption (AUDIT-C short form). Three subgroups of alcohol-related behaviour were distinguished (risky drinkers, social drinkers and abstainers). In order to explore factors associated with patterns of alcohol consumption, a multivariate logistic regression was performed. The prevalence of risky drinkers was 35%. A binge-drinking behaviour at least once in the last twelve months was declared by 65% (more widespread in men and in students living away from their parents). Risky consumption is significantly associated with age of onset of alcohol use, living away from parents’ home, drinking outside meals and attending health courses. Regarding the levels of daily alcohol consumption perceived as a health risk, 66% of men and 88% of women indicate values higher than those recommended. The results underline the need for tailored prevention measures. University could be a promising setting to implement actions according to a health promotion perspective, to empower students to control their alcohol consumption

Trustworthiness Management in the Social Internet of Things

The integration of social networking concepts into the Internet of things has led to the Social Internet of Things (SIoT) paradigm, according to which objects are capable of establishing social relationships in an autonomous way with respect to their owners with the benefits of improving the network scalability in information/service discovery. Within this scenario, we focus on the problem of understanding how the information provided by members of the social IoT has to be processed so as to build a reliable system on the basis of the behavior of the objects. We define two models for trustworthiness management starting from the solutions proposed for P2P and social networks. In the subjective model each node computes the trustworthiness of its friends on the basis of its own experience and on the opinion of the friends in common with the potential service providers. In the objective model, the information about each node is distributed and stored making use of a distributed hash table structure so that any node can make use of the same information. Simulations show how the proposed models can effectively isolate almost any malicious nodes in the network at the expenses of an increase in the network traffic for feedback exchange

Partial amplitude synchronization detection in brain signals using Bayesian Gaussian mixture models

The present work investigates instantaneous synchronization in multivariate signals. It introduces a new method to detect subsets of synchronized time series that do not consider any baseline information. The method is based on a Bayesian Gaussian mixture model applied at each location of a time–frequency map. The work assesses the relevance of detected subsets by a stability measure. The application to Local Field Potentials measured during a visuo-motor experiment in monkeys reveals a subset of synchronized time series measured in the visual cortex

On adding the social dimension to the Internet of Vehicles: Friendship and middleware

In this paper, we analyze the combination of Vehicular Ad-hoc NETworks (VANETs) with the Social Internet of Things (SIoT), i.e., the Social Internet of Vehicles (SIoV). In the SIoV every vehicle is capable of establishing social relationships with other vehicles in an autonomous way with the intent of creating an overlay social network that can be exploited for information search and dissemination in VANET applications. The contribution of this paper is two-fold: firstly, we define some relationships which can be established between the vehicles and between the vehicles and the road side units (RSUs); secondly, we propose a SIoV middleware which extends the functionalities of the Intelligent Transportation Systems Station Architecture (ITS SA), defined by ISO and ETSI standards, to take into account the elements needed to integrate VANETs in the SIoT. Additionally, we present results of software simulations analyzing realistic vehicular mobility trace in order to study the characteristics of the resulting social network structure

A Flexible FPGA/DSP Board for GNSS Receivers Design

With the recent launch of the first Galileo test satellite GIOVE-A, Europe made the first really important step towards the so-called Global Navigation Satellite System, which is already represented by the GPS and the GLONASS systems. In this context, the co-operation of these systems from the receiver point of view is going to ask the market for providing a user terminal able to deal with different signals. To achieve this target, a possible way forward goes through the study of dedicated signal processing algorithms based on Software Radio Defined principles. The paper will introduce the FPGA+DSP platform developed at the Politecnico di Torino, pointing out the advancements on the architecture design. Some results in terms of signal tracking performance will be also presented and discussed

Be Right Beach: A Social IoT System for Sustainable Tourism Based on Beach Overcrowding Avoidance

The coastal erosion is becoming of paramount importance for many countries. Many studies demonstrated that in some cases the beach overcrowding is the primary cause of coastal erosion. The goal of this work was to design, implement and test a system (BRB-Be Right Beach) that foster beach overcrowding avoidance and allows anyone to choose the right beach to go for having the best experience. The major requirement of our system was to have maximum accuracy (no errors, that is real-Time data only are used) in the information provided to the users. The system exploits the Social Internet of Things paradigm to implement a classifier trained by a community of smartphones brought by the owners to the beaches. The BRB sensor network consists of control units equipped with a UV sensor, a thermometer, a humidity sensor and a camera for crowdedness estimation. Data are collected by a cloud platform that provide any user with information about beaches and suggestions where to go, based on users preferences like weather, crowdedness, time of travel, and so on