References of "Engel, Thomas 50001752"
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See detailCharacterizing Driving Environments Through Bluetooth Discovery
Bronzi, Walter UL; Faye, Sébastien UL; Frank, Raphaël UL et al

Scientific Conference (2017, December)

Within the world of wireless technologies, Bluetooth has recently been at the forefront of innovation. It is becoming increasingly relevant for vehicles to become aware of their surroundings. Therefore ... [more ▼]

Within the world of wireless technologies, Bluetooth has recently been at the forefront of innovation. It is becoming increasingly relevant for vehicles to become aware of their surroundings. Therefore, having knowledge of nearby Bluetooth devices, both inside and outside other vehicles, can provide the listening vehicles with enough data to learn about their environment. In this paper, we collect and analyze a dataset of Bluetooth Classic (BC) and Low Energy (BLE) discoveries. We evaluate their respective characteristics and ability to provide context-aware information from a vehicular perspective. By taking a look at data about the encountered devices, such as GPS location, quantity, quality of signal and device class information, we infer distinctive behaviors between BC and BLE relative to context and application. For this purpose, we propose a set a features to train a classifier for the recognition of different driving environments (i.e. road classes) from Bluetooth discovery data alone. Comparing the performance of our classifier with different sampling parameters, the presented results indicate that, with our feature selection, we are able to predict with reasonable confidence up to three classes (Highway, City, Extra-Urban) by using only discovery data and no geographical information. This outcome gives promising results targeted at low energy and privacy-friendly applications and can open up a wide range of research directions. [less ▲]

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See detailEstimating Urban Road Traffic States Using Mobile Network Signaling Data
Derrmann, Thierry UL; Frank, Raphaël UL; Viti, Francesco UL et al

in Derrmann, Thierry; Frank, Raphaël; Viti, Francesco (Eds.) et al Estimating Urban Road Traffic States Using Mobile Network Signaling Data (2017, October)

It is intuitive that there is a causal relationship between human mobility and signaling events in mobile phone networks. Among these events, not only the initiation of calls and data sessions can be used ... [more ▼]

It is intuitive that there is a causal relationship between human mobility and signaling events in mobile phone networks. Among these events, not only the initiation of calls and data sessions can be used in analyses, but also handovers between different locations that reflect mobility. In this work, we investigate if handovers can be used as a proxy metric for flows in the underlying road network, especially in urban environments. More precisely, we show that characteristic profiles of handovers within and between clusters of mobile network cells exist. We base these profiles on models from road traffic flow theory, and show that they can be used for traffic state estimation using floating-car data as ground truth. The presented model can be beneficial in areas with good mobile network coverage but low road traffic counting infrastructure, e.g. in developing countries, but also serve as an additional predictor for existing traffic state monitoring systems. [less ▲]

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See detailHow Mobile Phone Handovers reflect Urban Mobility: A Simulation Study
Derrmann, Thierry UL; Frank, Raphaël UL; Engel, Thomas UL et al

in Derrmann, Thierry; Frank, Raphaël; Engel, Thomas (Eds.) et al How Mobile Phone Handovers reflect Urban Mobility: A Simulation Study (2017, June 26)

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See detailCharacterizing User Mobility Using Mobile Sensing Systems
Faye, Sébastien UL; Bronzi, Walter UL; Tahirou, Ibrahim UL et al

in International Journal of Distributed Sensor Networks (2017), 13(8),

Recent technological advances and the ever-greater developments in sensing and computing continue to provide new ways of understanding our daily mobility. Smart devices such as smartphones or smartwatches ... [more ▼]

Recent technological advances and the ever-greater developments in sensing and computing continue to provide new ways of understanding our daily mobility. Smart devices such as smartphones or smartwatches can, for instance, provide an enhanced user experience based on different sets of built-in sensors that follow every user action and identify its environment. Monitoring solutions such as these, which are becoming more and more common, allows us to assess human behavior and movement at different levels. In this article, extended from previous work, we focus on the concept of human mobility and explore how we can exploit a dataset collected opportunistically from multiple participants. In particular, we study how the different sensor groups present in most commercial smart devices can be used to deliver mobility information and patterns. In addition to traditional motion sensors that are obviously important in this field, we are also exploring data from physiological and environmental sensors, including new ways of displaying, understanding, and analyzing data. Furthermore, we detail the need to use methods that respect the privacy of users and investigate the possibilities offered by network traces, including Wi-Fi and Bluetooth communication technologies. We finally offer a mobility assistant that can represent different user characteristics anonymously, based on a combination of Wi-Fi, activity data, and graph theory. [less ▲]

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See detailSmartphone-based Adaptive Driving Maneuver Detection: A large-scale Evaluation Study
Castignani, German UL; Derrmann, Thierry UL; Frank, Raphaël UL et al

in IEEE Transactions on Intelligent Transportation Systems (2017)

The proliferation of connected mobile devices together with advances in their sensing capacity has enabled a new distributed telematics platform. In particular, smartphones can be used as driving sensors ... [more ▼]

The proliferation of connected mobile devices together with advances in their sensing capacity has enabled a new distributed telematics platform. In particular, smartphones can be used as driving sensors to identify individual driver behavior and risky maneuvers. However, in order to estimate driver behavior with smartphones, the system must deal with different vehicle characteristics. This is the main limitation of existing sensing platforms, which are principally based on fixed thresholds for different sensing parameters. In this paper, we propose an adaptive driving maneuver detection mechanism that iteratively builds a statistical model of the driver, vehicle, and smartphone combination using a multivariate normal model. By means of experimentation over a test track and public roads, we first explore the capacity of different sensor input combinations to detect risky driving maneuvers, and we propose a training mechanism that adapts the profiling model to the vehicle, driver, and road topology. A large-scale evaluation study is conducted, showing that the model for maneuver detection and scoring is able to adapt to different drivers, vehicles, and road conditions. [less ▲]

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See detailPoster: LuST-LTE: A Simulation Package for Pervasive Vehicular Connectivity
Derrmann, Thierry UL; Faye, Sébastien UL; Frank, Raphaël UL et al

Poster (2016, December 08)

Recent technological advances in communication technology have provided new ways to understand human mobility. Connected vehicles with their rising market penetration are particularly representative of ... [more ▼]

Recent technological advances in communication technology have provided new ways to understand human mobility. Connected vehicles with their rising market penetration are particularly representative of this trend. They become increasingly interesting, not only as sensors, but also as participants in Intelligent Transportation System (ITS) applications. More specifically, their pervasive connectivity to cellular networks enables them as passive and active sensing units. In this paper, we introduce LuST-LTE, a package of open-source simulation tools that allows the simulation of vehicular traffic along with pervasive LTE connectivity. [less ▲]

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See detailEnabling SDN in VANETs: What is the Impact on Security?
Di Maio, Antonio UL; Palattella, Maria Rita UL; Soua, Ridha et al

in Sensors (2016), 16(12), 2077

The demand for safe and secure journeys over roads and highways has been growing at a tremendous pace over recent decades. At the same time, the smart city paradigm has emerged to improve citizens’ ... [more ▼]

The demand for safe and secure journeys over roads and highways has been growing at a tremendous pace over recent decades. At the same time, the smart city paradigm has emerged to improve citizens’ quality of life by developing the smart mobility concept. Vehicular Ad hoc NETworks (VANETs) are widely recognized to be instrumental in realizing such concept, by enabling appealing safety and infotainment services. Such networks come with their own set of challenges, which range from managing high node mobility to securing data and user privacy. The Software Defined Networking (SDN) paradigm has been identified as a suitable solution for dealing with the dynamic network environment, the increased number of connected devices, and the heterogeneity of applications. While some preliminary investigations have been already conducted to check the applicability of the SDN paradigm to VANETs, and its presumed benefits for managing resources and mobility, it is still unclear what impact SDN will have on security and privacy. Security is a relevant issue in VANETs, because of the impact that threats can have on drivers’ behavior and quality of life. This paper opens a discussion on the security threats that future SDN-enabled VANETs will have to face, and investigates how SDN could be beneficial in building new countermeasures. The analysis is conducted in real use cases (smart parking, smart grid of electric vehicles, platooning, and emergency services), which are expected to be among the vehicular applications that will most benefit from introducing an SDN architecture. [less ▲]

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See detailTowards Characterizing Bluetooth Discovery in a Vehicular Context
Bronzi, Walter UL; Derrmann, Thierry UL; Castignani, German UL et al

in Vehicular Networking Conference (VNC), 2016 IEEE (2016, December)

Bluetooth has, in recent years, gained more and more momentum. New commodity objects and wearables im- plementing Bluetooth Smart technology (Low Energy) are re- leased everyday. In particular, the ever ... [more ▼]

Bluetooth has, in recent years, gained more and more momentum. New commodity objects and wearables im- plementing Bluetooth Smart technology (Low Energy) are re- leased everyday. In particular, the ever increasing number of discoverable devices both inside and outside a populated area gives us an encouraging insight on future research directions for this technology. In this paper, based on a sensing system developed as an Android application, we evaluate Bluetooth Classic and Low Energy discovery characteristics from a vehic- ular perspective. By recording information about devices nearby (e.g. the number of discovered devices, their signal strength, manufacturer information) and the GPS location we can derive interesting information about a driver’s situation, as well as his/her environment. Presented results indicate that the amount of discovered devices and signal strengths are dependent on velocity and road category. Finally, future work and discussions address potential use-case applications based only on Bluetooth discovery, such as low energy and privacy friendly road and traffic context awareness. The sensing system used in this article is free online under the MIT License. [less ▲]

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See detailDemo Abstract: Human Mobility Profiling Using Privacy-Friendly Wi-Fi and Activity Traces
Faye, Sébastien UL; Tahirou, Ibrahim UL; Engel, Thomas UL

in Proceedings of the 14th ACM Conference on Embedded Networked Sensor Systems (SenSys 2016) (2016, November 14)

Human mobility is one of the key topics to be considered in the networks of the future, both by industrial and research communities that are already focused on multidisciplinary applications and user ... [more ▼]

Human mobility is one of the key topics to be considered in the networks of the future, both by industrial and research communities that are already focused on multidisciplinary applications and user-centric systems. If the rapid proliferation of networks and high-tech miniature sensors makes this reality possible, the ever-growing complexity of the metrics and parameters governing such systems raises serious issues in terms of privacy, security and computing capability. In this demonstration, we show a new system, able to estimate a user's mobility profile based on anonymized and lightweight smartphone data. In particular, this system is composed of (1) a web analytics platform, able to analyze multimodal sensing traces and improve our understanding of complex mobility patterns, and (2) a smartphone application, able to show a user's profile generated locally in the form of a spider graph. In particular, this application uses anonymized and privacy-friendly data and methods, obtained thanks to the combination of Wi-Fi traces, activity detection and graph theory, made available independent of any personal information. [less ▲]

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See detailUnderstanding User Daily Mobility Using Mobile and Wearable Sensing Systems
Faye, Sébastien UL; Engel, Thomas UL

in Proceedings of the 2016 International Conference on Information and Communications Technology Convergence - ICTC 2016 (2016, October)

Recent technological advances and the ever-greater developments in sensing and computing continue to provide new ways of understanding our daily mobility. Smart devices such as smartphones or smartwatches ... [more ▼]

Recent technological advances and the ever-greater developments in sensing and computing continue to provide new ways of understanding our daily mobility. Smart devices such as smartphones or smartwatches can, for instance, provide an enhanced user experience based on different sets of built-in sensors that follow every user action and identify its environment. Monitoring solutions such as these, which are becoming more and more common, allow us to assess human behavior and movement at different levels. In this article, we focus on the concept of human mobility. With the participation of 13 individuals, we carried out an experiment to discover how groups of sensors currently available in smartphones and smartwatches can help to distinguish different profiles and patterns of human mobility. We show that it is possible to use not only motion sensors but also physiological sensors and environmental data provided, for instance, by Wi-Fi. Finally, detailed study of these categories enables us to offer a way of representing the mobility of individual users, based on anonymized traces and graph theory. [less ▲]

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See detailPOSTER: Fingerprinting Tor Hidden Services
Mitseva, Asya UL; Panchenko, Andriy UL; Lanze, Fabian et al

Poster (2016, October)

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See detailSDN coordination for CCN and FC content dissemination in VANETs
Soua, Ridha; Kalogeiton, Eirini; Manzo, Gaetano et al

in Proceedings of the 8th International Conference on Ad Hoc Networks (ADHOCNETS), Ottawa, ON, Canada (2016, September 26)

Content dissemination in Vehicular Ad-hoc Networks has a myriad of applications, ranging from advertising and parking notifications, to traffic and emergency warnings. This heterogeneity requires ... [more ▼]

Content dissemination in Vehicular Ad-hoc Networks has a myriad of applications, ranging from advertising and parking notifications, to traffic and emergency warnings. This heterogeneity requires optimizing content storing, retrieval and forwarding among vehicles to deliver data with short latency and without jeopardizing network resources. In this paper, for a few reference scenarios, we illustrate how approaches that combine Content Centric Networking (CCN) and Floating Content (FC) enable new and efficient solutions to this issue. Moreover, we describe how a network architecture based on Software Defined Networking (SDN) can support both CCN and FC by coordinating distributed caching strategies, by optimizing the packet forwarding process and the availability of floating data items. For each scenario analyzed, we highlight the main research challenges open, and we describe a few possible solutions. [less ▲]

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See detailA Two-Level Approach to Characterizing Human Activities from Wearable Sensor Data
Faye, Sébastien UL; Louveton, Nicolas UL; Gheorghe, Gabriela UL et al

in Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications (2016), 7(3),

The rapid emergence of new technologies in recent decades has opened up a world of opportunities for a better understanding of human mobility and behavior. It is now possible to recognize human movements ... [more ▼]

The rapid emergence of new technologies in recent decades has opened up a world of opportunities for a better understanding of human mobility and behavior. It is now possible to recognize human movements, physical activity and the environments in which they take place. And this can be done with high precision, thanks to miniature sensors integrated into our everyday devices. In this paper, we explore different methodologies for recognizing and characterizing physical activities performed by people wearing new smart devices. Whether it’s smartglasses, smartwatches or smartphones, we show that each of these specialized wearables has a role to play in interpreting and monitoring moments in a user's life. In particular, we propose an approach that splits the concept of physical activity into two sub-categories that we call micro- and macro-activities. Micro- and macro-activities are supposed to have functional relationship with each other and should therefore help to better understand activities on a larger scale. Then, for each of these levels, we show different methods of collecting, interpreting and evaluating data from different sensor sources. Based on a sensing system we have developed using smart devices, we build two data sets before analyzing how to recognize such activities. Finally, we show different interactions and combinations between these scales and demonstrate that they have the potential to lead to new classes of applications, involving authentication or user profiling. [less ▲]

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See detailTowards Privacy-Neutral Travel Time Estimation from Mobile Phone Signalling Data
Derrmann, Thierry UL; Frank, Raphaël UL; Faye, Sébastien UL et al

in Proceedings of the 2016 IEEE International Smart Cities Conference (ISC2) (2016, September)

Today’s mobile penetration rates enable cellular signaling data to be useful in diverse fields such as transportation planning, the social sciences and epidemiology. Of particular interest for these ... [more ▼]

Today’s mobile penetration rates enable cellular signaling data to be useful in diverse fields such as transportation planning, the social sciences and epidemiology. Of particular interest for these applications are mobile subscriber dwell times. They express how long users stay in the service range of a base station. In this paper, we want to evaluate whether dwell time distributions can serve as predictors for road travel times. To this end, we transform floating car data into synthetic dwell times that we use as weights in a graph-based model. The model predictions are evaluated using the floating car ground truth data. Additionally, we show a potential link between handover density and travel times. We conclude that dwell times are a promising predictor for travel times, and can serve as a valuable input for intelligent transportation systems. [less ▲]

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See detailHeat is in the Eye of the Beholder: Towards Better Authenticating on Smartglasses
Gheorghe, Gabriela UL; Louveton, Nicolas UL; Martin, Benoît et al

in Proceedings of the 9th International Conference on Human System Interaction (HSI'16) (2016, July)

Smart and wearable devices are trendy electronic objects that have become increasingly popular in recent years. Those devices are, by definition, tightly connected with the user's personal activities ... [more ▼]

Smart and wearable devices are trendy electronic objects that have become increasingly popular in recent years. Those devices are, by definition, tightly connected with the user's personal activities. Authentication is therefore a critical feature for both identifying users and personalizing the services on the device. In particular, the emergence of smartglasses changed the way we thought a wearable could assist users in their daily activities. As designed by commercial providers, smartglasses are sold with a very specific set of interactions capabilities. These capabilities have a strong impact on how comfortably or safely users may authenticate to their smartglasses. For this reason, we investigate in this paper the different authentication methods available for smartphones and we comparatively position the smartglasses in the design space of authentication methods. We propose a new approach based on touch input on an arbitrary surface using thermal camera input. This approach aims to circumvent the lack of touch surface provided by smartglasses, while maintaining an acceptable level of security. [less ▲]

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See detailNot a Tile Out of Place: Toward Creating Context-Dependent User Interfaces on Smartglasses
Pecci, Isabelle; Martin, Benoît; Kacem, Imed et al

in Proceedings of the 9th International Conference on Human System Interaction (HSI'16) (2016, July)

Despite the rapid pace of gadgets released on the market, research in the area of usable interfaces for wearables is lagging behind. Smartglasses are new wearables that embed diverse sensors but also have ... [more ▼]

Despite the rapid pace of gadgets released on the market, research in the area of usable interfaces for wearables is lagging behind. Smartglasses are new wearables that embed diverse sensors but also have small displays, and this makes it hard for the wearer to visualize real-time data. To bridge this gap, the contribution of this paper is threefold. First, we propose a data representation model to combine applications and services that match user activities and contexts. Second, we present an approach of showing relevant services to the user based on 'tiles' (such as those in recent Microsoft Windows interfaces) while considering the device constraints. Finally, we suggest that combining those two aspects can open the way to personalized services for the end user, creating new ways of interacting with applications and devices. [less ▲]

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See detailLuST-LTE: A Simulation Package for Pervasive Vehicular Connectivity
Derrmann, Thierry UL; Faye, Sébastien UL; Frank, Raphaël UL et al

Presentation (2016, June 30)

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See detailToward a Characterization of Human Activities using Smart Devices: A Micro/Macro Approach
Faye, Sébastien UL; Louveton, Nicolas UL; Gheorghe, Gabriela UL et al

in Proceedings of the 7th IEEE INFOCOM International Workshop on Mobility Management in the Networks of the Future World (2016, April)

The emergence of new connected devices has opened up new opportunities and allowed to imagine concepts that bring computer sciences and social sciences closer together. In particular, today's increasingly ... [more ▼]

The emergence of new connected devices has opened up new opportunities and allowed to imagine concepts that bring computer sciences and social sciences closer together. In particular, today's increasingly sophisticated miniature sensors allow to track and understand human activities and behavior with a great precision. Taking different approaches and perspectives, we use in this paper smartwatches and smartglasses to explore these behaviors and show that these objects, considered by many as gadgets, have an important role to play in understanding the lives of individuals. The main objective of this work is to introduce two new scales of activity detection, which lacks a formal and consistent definition in the literature. First, we propose a model that precisely detects and interprets movements made by a person wearing smart devices. Then, we use this model to show different interactions between those micro-activities and bigger chunks of behaviors we call macro-activities. Using a new concept based on 3D visualization, we finally show that combining those two scales and using a limited dataset, it is possible to distinguish between different individuals when they are performing very similar activities. The findings of this study lead the way to enhanced user profiling. [less ▲]

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See detailContent and Context Aware Strategies for QoS Support in VANETs
Rizzo, Gianluca; Palattella, Maria Rita UL; Braun, Torsen et al

in Proc. of Int. Conf. on Advanced Information Networking and Applications (AINA-2016) (2016, March)

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See detailWebsite Fingerprinting at Internet Scale
Panchenko, Andriy UL; Lanze, Fabian UL; Zinnen, Andreas et al

in Proceedings of the 23rd Internet Society (ISOC) Network and Distributed System Security Symposium (NDSS 2016) (2016, February)

Detailed reference viewed: 216 (24 UL)