Repousser les limites de l'informatique ubiquitaire par l'utilisation des smartphones

Les smartphones occupent une place de plus en plus importante dans notre quotidien. Ils permettent d’accéder, en tout temps et en tout lieu, à de nombreux services facilitant la vie de l’utilisateur et jouent ainsi un rôle important dans nos modes de vie à l’ère de l’informatique ubiquitaire. De nombreux travaux ont montré par exemple qu’il était possible de proposer avec ces dispositifs mobiles bien plus que ce que l’on peut faire avec un simple ordinateur. L’espace des services qu’ils offrent s’est ainsi grandement étendu dans des domaines extrêmement variés. Cependant, leur mise en œuvre présente souvent des limites en raison des importantes contraintes importantes d’utilisation qu’elles font peser sur l’utilisateur, du déploiement infrastructurel qu’elles requièrent ou de la précision limitée qu’elles permettent d’atteindre. Dans cette thèse, nous nous proposons de repousser ces limites. Nous avons retenu la condition d’utilisation la condition d’utilisation la moins contraignante : celle d’un téléphone simplement tenu dans la main. Nous proposons alors HandRate, le premier système capable de suivre la fréquence cardiaque d’un utilisateur dans ce contexte d’utilisation. Nous exploitons ensuite ce même signal vibratoire de la main pour construire HoldPass, un système capable d’authentifier un utilisateur dans ces mêmes conditions d’utilisation. HandRate et HoldPass peuvent ainsi jouer un rôle important dans la lutte contre les maladies cardio-vasculaires et une authentification biométrique plus sûre et plus difficile à outrepasser. Pour ajouter du contexte à ces informations médicales, nous mettons à profit les avancées récentes du standard WiFi et proposons un algorithme, FUSIC, permettant de fournir une localisation plus précise à l’intérieur des bâtiments. Des prototypes de chacune de ces solutions ont été implantés sur du matériel réel et ont donné lieu à des expérimentations en vraie grandeur, incluant parfois la participation de centaines d’utilisateurs. Elles montrent des améliorations sensibles des performances tout en minimisant les contraintes d’utilisation

Electrochemical Determination of Epinephrine in Pharmaceutical Preparation Using Laponite Clay-Modified Graphene Inkjet-Printed Electrode

Epinephrine (EP, also called adrenaline) is a compound belonging to the catecholamine neurotransmitter family. It can cause neurodegenerative diseases, such as Alzheimer’s disease, Parkinson’s disease, Huntington’s disease and amyotrophic lateral sclerosis. This work describes an amperometric sensor for the electroanalytical detection of EP by using an inkjet-printed graphene electrode (IPGE) that has been chemically modified by a thin layer of a laponite (La) clay mineral. The ion exchange properties and permeability of the chemically modified electrode (denoted La/IPGE) were evaluated using multi-sweep cyclic voltammetry, while its charge transfer resistance was determined by electrochemical impedance spectroscopy. The results showed that La/IPGE exhibited higher sensitivity to EP compared to the bare IPGE. The developed sensor was directly applied for the determination of EP in aqueous solution using differential pulse voltammetry. Under optimized conditions, a linear calibration graph was obtained in the concentration range between 0.8 μM and 10 μM. The anodic peak current of EP was directly proportional to its concentration, leading to detection limits of 0.34 μM and 0.26 μM with bare IPGE and La/IPGE, respectively. The sensor was successfully applied for the determination of EP in pharmaceutical preparations. Recovery rates and the effects of interfering species on the detection of EP were evaluated to highlight the selectivity of the elaborated sensor

Sample Preparation Techniques for Electrochemical Analysis of Pesticides and Heavy Metals in Environmental and Food Samples

The development of an analytical methodology commonly includes sampling and sample pretreatment-preparation. The sample preparation step should provide the analytes (pesticides, heavy metals, drugs, dyes…etc.) in an adequate medium (typically aqueous or non-aqueous solution) to be detected and/or quantified. It is, therefore, necessary to ensure that the sample is homogeneous and free of interferents, as long as the preparation step is the most significant source of error in the analytical method development and is the most time-consuming step especially when solid samples are analyzed. Given its importance, this preparation step has a fundamental importance in the overall analytical method development, mainly when electroanalytical methods are applied. In this chapter, the steps involved in preparing samples for electrochemical analysis will be described in detail. Specifically, we will be focusing on the sample preparation techniques for the electrochemical analysis of pesticides and heavy metals, in environmental and food samples. For non-electrochemical readers, a brief introduction to the most commonly used electroanalytical methods will be described

Pushing the limits of ubiquitous computing through the use of smartphones

Les smartphones occupent une place de plus en plus importante dans notre quotidien. Ils permettent d’accéder, en tout temps et en tout lieu, à de nombreux services facilitant la vie de l’utilisateur et jouent ainsi un rôle important dans nos modes de vie à l’ère de l’informatique ubiquitaire. De nombreux travaux ont montré par exemple qu’il était possible de proposer avec ces dispositifs mobiles bien plus que ce que l’on peut faire avec un simple ordinateur. L’espace des services qu’ils offrent s’est ainsi grandement étendu dans des domaines extrêmement variés. Cependant, leur mise en œuvre présente souvent des limites en raison des importantes contraintes importantes d’utilisation qu’elles font peser sur l’utilisateur, du déploiement infrastructurel qu’elles requièrent ou de la précision limitée qu’elles permettent d’atteindre. Dans cette thèse, nous nous proposons de repousser ces limites. Nous avons retenu la condition d’utilisation la condition d’utilisation la moins contraignante : celle d’un téléphone simplement tenu dans la main. Nous proposons alors HandRate, le premier système capable de suivre la fréquence cardiaque d’un utilisateur dans ce contexte d’utilisation. Nous exploitons ensuite ce même signal vibratoire de la main pour construire HoldPass, un système capable d’authentifier un utilisateur dans ces mêmes conditions d’utilisation. HandRate et HoldPass peuvent ainsi jouer un rôle important dans la lutte contre les maladies cardio-vasculaires et une authentification biométrique plus sûre et plus difficile à outrepasser. Pour ajouter du contexte à ces informations médicales, nous mettons à profit les avancées récentes du standard WiFi et proposons un algorithme, FUSIC, permettant de fournir une localisation plus précise à l’intérieur des bâtiments. Des prototypes de chacune de ces solutions ont été implantés sur du matériel réel et ont donné lieu à des expérimentations en vraie grandeur, incluant parfois la participation de centaines d’utilisateurs. Elles montrent des améliorations sensibles des performances tout en minimisant les contraintes d’utilisation.Smartphones have increasingly become an important part of our everyday lives. By enabling anywhere-anytime access to numerous digital services, they have emerged as a key catalyst for ushering in the new era of ubiquitous computing and intelligent environment. Research in academia and industry has shown it is possible to offer with these mobile devices much more than what can be done with a simple computer. The space of services they offer spans a very diverse and wide spectrum of application, ranging from navigation, to digital healthcare and as far as the liquid identification. Nevertheless, the transition from academic labs to the market has fallen short of the expectations, in large part due to the significant constraints they place on the user, the infrastructural deployment they require or the limited accuracy in practice they offer. In this thesis, we aim at closing the gap between promise and market adoption. We have chosen the least restrictive usage condition : a phone simply held in the hand. We propose HandRate, the first smartphone-based system able to track the heart rate of a user by leveraging the hand vibrations induced by the cardiac cycle. We furthermore exploit this same hand vibration signal to build HoldPass, a system capable of authenticating a user. HandRate and HoldPass can thus play an important role in the fight against cardiovascular diseases and a biometric authentication that is more secure and more difficult to circumvent. To add context to this medical information, we take advantage of recent advances in the WiFi standard and propose an algorithm, FUSIC, to provide more accurate location inside buildings. Prototypes of each of these solutions have been implemented on real hardware and have led to full-scale experiments, sometimes involving hundreds of users. They show significant improvements in performance while minimizing usage constraints

Generating Mobility-Aware Traces for IoT Applications

This demonstration introduces a set of tools that enables the reproducible generation of traces for IoT applications taking into account mobility and fine-grained instantaneous energy consumption information. Our setup leverages the FIT IoT-Lab open testbed and its hundreds of nodes to enable researchers to remotely build datasets for their custom IoT/Edge scenarios. We demonstrate this through a sample scenario composed of 100 IoT nodes belonging to 3 mobility-aware applications and make the resulting datasets available to the community. The generation of these kinds of traces is important for designing and evaluating accurate mobility aware offloading algorithms for IoT and Edge Computing and, more specifically, for training Artificial Intelligence models

HandRate: Heart Rate Monitoring While Simply Holding a Smartphone

International audienceWe present HandRate, the first smartphone-based system using a standard sensor (accelerometer) for opportunistically computing heart rate while a user holds their phone. Fundamentally, HandRate revisits ballistocardiography (BCG), a century-old technique for monitoring heart activity by measuring the body movement caused by the cardiac cycle. Traditionally performed using custom hardware, attached to a subject's body, revisiting BCG for the smartphone, held in hand, faces several challenges. The hand is an external organ furthest from the aorta and subject to motion artifacts, leading to a weak and noisy signal, while the position the phone is held in can impact which accelerometer axis best captures BCG. HandRate addresses these challenges by introducing a design involving two modules operating in tandem: the first aimed at transforming the accelerometer readings into a single-dimensional signal oblivious to how the phone is held, while the second module making heartbeat predictions based on this signal. Results from testing HandRate using data collected from 18 subjects show that it can estimate heart rate with accuracy similar to or better than systems requiring special sensors and/active user participation

When FTM Discovered MUSIC: Accurate WiFi-based Ranging in the Presence of Multipath

International audienceThe recent standardization by IEEE of Fine Timing Measurement (FTM), a time-of-flight based approach for ranging has the potential to be a turning point in bridging the gap between the rich literature on indoor localization and the so-far tepid market adoption. However, experiments with the first WiFi cards supporting FTM show that while it offers meter-level ranging in clear line-of-sight settings (LOS), its accuracy can collapse in non-line-of-sight (NLOS) scenarios. We present FUSIC, the first approach that extends FTM's LOS accuracy to NLOS settings, without requiring any changes to the standard. To accomplish this, FUSIC leverages the results from FTM and MUSIC - both erroneous in NLOS - into solving the double challenge of 1) detecting when FTM returns an inaccurate value and 2) correcting the errors as necessary. Experiments in 4 different physical locations reveal that a) FUSIC extends FTM's LOS ranging accuracy to NLOS settings - hence, achieving its stated goal; b) it significantly improves FTM's capability to offer room-level indoor positioning

I Want to Know Your Hand: Authentication on Commodity Mobile Phones Based on Your Hand's Vibrations

INRIA Lille-Nord Europe : plate-forme Grid'5000International audienceWe present HoldPass, the first system that can authenticate a user while they simply hold their phone. It uses the heart activity as biometric trait sensed via the hand vibrations in response to the cardiac cycle-a process known as ballistocardiography (BCG). While heart activity has been used for biometric authentication, sensing it through hand-based ballistocardiography (Hand-BCG) using standard sensors found on commodity mobile phones is an uncharted territory. Using a combination of in-depth qualitative analysis and large-scale quantitative analysis involving over 100 volunteers, we paint a detailed picture of opportunities and challenges. Authentication based on Hand-BCG is shown to be feasible but the signal is weak, uniquely prone to motion artifacts and does not land itself to the common approach of alignment-based authentication. HoldPass addresses these challenges by introducing a novel alignment-free authentication scheme that builds on asynchronous signal slicing and a data-driven algorithm for identifying a reduced set of features for characterizing a user. We implement HoldPass and evaluate it using a multi-modal approach: a large-case study involving 112 volunteers and targeted studies with a smaller set of volunteers over a period of several months. The data shows that HoldPass provides an authentication accuracy and user experience on par with or better than state-of-the-art systems with stronger requirements on hardware and/or user participation

FUSIC, du Ranging WiFi de haute précision en présence de multi-trajet

International audienceLa récente standardisation par l'IEEE du protocole Fine Timing Measurement (FTM), une approche de calcul de distance par temps de vol fondée sur le WiFi, permet de faire le pont entre la littérature très riche sur la localisation en intérieur et l'adoption jusque-là timide par le marché. Cependant, les expériences menées avec les premières cartes implantant le FTM montrent une précision de l'ordre du mètre en ligne de vue directe (LDV) mais qui chute brutalement dans les scénarios où la ligne de vue est obstruée (NLDV). Dans ce travail, nous présentons FUSIC, une approche qui étend la précision du FTM dans ce contexte, sans modifier le standard. Pour cela, FUSIC combine les résultats du FTM et de l'algorithme MUSIC-tous les deux erronés quand la ligne de vue est obstruée-pour restituer une estimation correcte de la distance séparant les deux équipements. Des expériences menées dans 4 environnements montrent que a) FUSIC étend la précision du FTM en LDV aux conditions NLDV-atteignant ainsi son but premier ; et b) améliore significativement la capacité du FTM à fournir de la localisation en intérieur de haute précision