Posts tagged "iot"

LAAS/CNRS - LCC/CNRS - Laplace, Toulouse University

Keywords

E-nose, indoor air quality, multi-gas sensors, nanostructures, metal oxide semiconductors, sensitivity, selectivity, internet of thing (IoT).

Humans spend more than 90% of their time in a closed environment that contains several gaseous pollutants like VOCs (volatile organic compounds). Such gaseous contaminants in the indoor air may cause respiratory problems and chronical diseases. Many others gases such as CO2, CO, and NO2 from urban pollution and poor ventilation systems are also part of indoor air contaminants. Offices, meeting rooms, classrooms and practical workrooms in universities and / or schools may present VOC and /or CO2 levels that exceed the regulatory thresholds. Measuring and monitoring indoor air quality is therefore essential to ensure a better quality life in workspaces. This thesis has been carried out within the framework of the GIS neOCampus (groupement d’intérêt scientifique), led by Université Paul Sabatier UT3 and dedicated to the development of an innovative, connected and sustainable campus for a better quality life. We are interested in the development of miniaturized MOS (metal oxide sensors) gas sensors for the indoor air quality monitoring in offices and classrooms. The objective of this study is to control these pollution levels in order to correct them through measures to ventilate the premises. Making a decision about how to correct air quality is an essential step in the process. As part of this work, we have prepared several prototypes of miniaturized multi-gas sensors (4 sensors) integrated on their electronic card able to detect levels of indoor air pollution. The proximity electronics allows the control and recovery of data from these sensors, and an IOT (internet of things) type communication module based on the WiFi protocol linked to the "Cloud NeoCampus", remotely and wirelessly, generates indoor-air quality signal in real time. This multi-sensor is based on semiconductor sensors based on nanostructured metal oxides (SnO2, WO3, CuO) synthesized at the LCC (laboratoire de chimie de coordination).

Scientific goal

We have developed a new synthetic approach for the nanostructured metal oxides on the sensor platform in order to optimize the performance of the sensitive layer (stability, sensitivity, selectivity). We have studied very efficient associations of n-type and p-type MOS nanostructures based on multilayered implementation on silicon platforms. The gas responses have been measured in laboratories test benches and new measurement protocols (cycled temperature mode versus continuous operation mode) have been defined to selectively detect NO2 or VOCs compounds in air at ppm and sub ppm levels. In addition, PCA (principal components analysis) analyses have been set up to discriminate gas mixtures in test benches.

Contacts

philippe.menini_at_laas.fr, pierre.fau_at_lcc-toulouse.fr, vincent.bley_at_laplace.univ-tlse.fr

IRIT-SMAC/University of Palermo (Italy)

Context presentation

The development of sustainable smart cities requires the deployment of information and communication technology to ensure better services and available information at any time and everywhere. As IoT devices become more powerful and low-cost, the implementation of an extensive sensor network for an urban context can be expensive. This project proposes a technique for estimating missing environmental information in large-scale environments named HybridIoT. Our proposal enables providing information whereas devices are not available for an area of the environment not sufficiently covered by sensing devices. The contribution of our proposal is summarized in the following points:

-    limiting the number of sensing devices to be deployed in an urban environment;

-    the exploitation of heterogeneous data acquired from intermittent devices;

-    real-time processing of information;

-    self-calibration of the system.

HybridIoT exploits both homogeneous (information of the same type) and heterogeneous information (information of different types or units) acquired from the available sensing device to provide accurate estimates in the point of the environment where sensing devices are not available.

Figure 1 HybridIoT uses information from intermittent and mobile devices to provide accurate estimates.

Keywords

Smart City, Missing Data Estimation, Heterogeneous Data Integration

Scientific goal

HybridIoT enables estimating accurate environmental information under conditions of uncertainty arising from the urban application context in which the project is situated, and which have not been explored by the state-of-the-art solutions :

-    openness: sensors can enter or leave the system at any time without the need for any reconfiguration;

-    large scale: the system can be deployed in a large, urban context and ensure correct operation with a significant number of devices;

-    heterogeneity: the system handles different types of information without any a priori configuration.

Contact

Davide Guastella, Valérie Camps, Marie-Pierre Gleizes {davide.guastella, valerie.camps, marie-pierre.gleizes_at_irit.fr

Context Presentation

The development of sustainable smart cities requires the deployment of Information and Communication Technology (ICT) to ensure better services and available information at any time and everywhere. As IoT devices become more powerful and low-cost, the implementation of an extensive sensor network for an urban context can be expensive.

This thesis addresses the problem of estimating missing information in urban contexts. The objective is to estimate accurate environmental information where physical sensors are not available. The proposed solution, HybridIoT, uses the Adaptive Multi-Agent System (AMAS) to estimate accurate environmental information under conditions of uncertainty arising from the urban application context in which the project is applied, such as openness, heterogeneity and large-scale, which have not been explored by the state-of-the-art solutions.

Keywords

Smart city, Cooperative Multi-Agent Systems, Missing Information Estimation, Heterogeneous Data Integration

Scientific goals

- Limiting the number of ad hoc devices to be deployed in an urban environment

- The exploitation of heterogeneous data acquired from mobile, intermittent devices

- Real-time processing of information

- Self-calibration of the system

Contacts

davide.guastella@irit.fr, Marie-Pierre.Gleizes@irit.fr, valerie.camps@irit.fr

Context Presentation

Fog computing has emerged as a strong distributed computation paradigm to support applications with stringent latency requirements. It offers almost ubiquitous computation capacities over a large geographical area. However, Fog systems are highly heterogeneous and dynamic which makes IoT services placement decision quite challenging considering nodes mobility that may decrease the placement decision quality over time.

IoT-Fog Services placement problem needs to be thoroughly investigated to ensure the efficiency of such environments. In this thesis, we consider various parameters such as nodes mobility, energy efficiency and applications Quality of Service (QoS) requirements to propose efficient strategies for IoT services placement in the Fog.

Keywords

Internet of Things, Optimization, Mobility, Fog Computing, QoS, Energy.

Scientific goals

•    Propose efficient approaches for IoT applications (services) placement in the Fog,

•    Analyze their impact on the energy consumption of Fog infrastructures and the Quality of Service (QoS) of  applications.

Contacts

tanissia.djemai@irit.fr, patricia.stolf@irit.fr, monteil@laas.fr, jean-marc.pierson@irit.fr

Context Presentation

MyGates is a part of autOCampus project to experiment and validates the smart mobility particularly for electrics, connected and autonomous vehicles in a dense urban environment.

In that way, a gates management system for autonomous vehicles will make easier experiments. It combines an automatic license plate with a car model recognizer to make it usable for classic car. It also contains database to keep information over authorized car and application designed for security officer to give temporary authorization for delivering driver with a photo of the vehicle and the plate.

MyGates is designed to be added on existing gates and only create the automation system with SALTO automaton that already are managing gates. MyGates will belong to the AIoT platform that will come out in the regional platform of research and innovation (PRRI) context containing smart camera and other smart devices.

Keywords

Autonomous Vehicles, Gates, CNN, ALPR, Salto, Nvidia Jetson Nano, autOCampus

Scientific goals

•    Create automatic and connected gates managements with plate and car model recognition

•    Create a classifier with many classes that are very similar

Contacts

vincent-nam.dang@irit.fr, thiebolt@irit.fr

Context Presentation

On site access control exists almost everywhere in today's modern world. Keys have already been replaced by access cards in most places but accessOCampus aims to improve on these existing systems even more.

For less than 200€ (excluding the optional thermal camera) an accessOCampus client module can be built, this includes : NFC access card recognition, passcode entry, face recognition and a large screen for access related information. The system can also be locked down or forced open globally by an authorized security personnel via the easy to use web interface.

In theory, accessOCampus can be used to log who has entered any given zone and provide detailed information on those people. For instance, if any given access card is stolen we can detect who used it via face recognition either silently or to refuse access.This project could be implemented in select zones of Toulouse University to provide a low-cost high fidelity access system.

Keywords

neOCampus, IOT, Smart Building, Security, Access, Face Recognition

 Scientific goals

•    Provide a high security solution to restricted zones

•    Facilitate zone entry for the end user via face recognition•    Display easy to understand information

Contacts

gomme600@hotmail.com, Francois.Thiebolt@irit.fr

Context Presentation

The number of sensors in buildings is constantly increasing, thanks to more accessible costs and the obvious interest of their use for optimized management. In this thesis we are interested in the use of data from these sensors to detect anomalies in buildings. These data, which are very numerous, can be of unknown and heterogeneous types.An anomaly is defined as unexpected and undesirable behaviour in a system and may depend on the context. In order to be able to deploy an anomaly detection system as widely as possible, it is necessary to create a decision support tool for energy experts. To address these issues, a system based on cooperative multi-agent systems implementing AMAS theory is being developed that allows anomalies to be detected by supervised learning. The anomaly detection system must take advantage of the feedback from one or more experts who label certain instances as anomalies or non-anomalies. These feedback are used for learning. The system we develop allows the addition or removal of new sensors without interrupting the detection of anomalies.

The system classifies situations

Scientific Goals

- Improve energy efficiency

- Detect anomalies in real time

- Learn continuously from the expert feedback

Keywords

Multi-Agent Systems, Smart Buildings, Internet of Things, Supervised Learning, Anomaly Detection

Contacts

Maxime.houssin@irit.fr

Au cours des dernières années, l'Internet des objets (IoT) a évolué à une vitesse exceptionnelle permettant ainsi de connecter un nombre important d'objets hétérogènes (capteurs, actionneurs, smartphone, application, etc.). Les domaines d'applications sont ainsi très larges avec des applications industrielles (usine du futur), dans les collectivités (villes intelligentes, campus intelligent), écologiques et économiques (gestion de l'énergie) ou bien encore individuels (aide au diagnostic médical, confort de vie, domotique). De nombreux verrous sont à lever en terme de recherche notamment dû au nombre d’entités important (potentiellement plusieurs milliers, millions, milliards d’objets), à la quantité d’information « brut » générée et au besoin de construire de nouveaux usages à base de nouveaux services les plus intelligents possibles le tout sous des contraintes de qualité de service variées. Cette thèse se concentrera plus particulièrement sur ce dernier point. Les infrastructures à mettre en place pour déployer une architecture IoT font l’objet de travaux dans les organismes de standardisation (ETSI, OneM2M, etc) ou consortium industriel (OCF, OMA, etc) avec actuellement un rapprochement sensible vers les architectures de type fog ou edge computing (EdgeX). Le modèle classique de l’IoT amenant les devices à envoyer des informations via les gateways au cloud qui ensuite fournit les services aux applications trouve des extensions dans l’approche fog ou edge permettant de rapprocher les services au plus proche des usagers en s’appuyant notamment sur les gateways.

Figure 1 : « IoT services placement  in a Fog computing infrastructure »

Objectifs scientifiques

 L’objectif de la thèse est de concevoir un Framework autonome et intelligent pour  le placement et l’orchestration des services d’applications IoT sur une infrastructure hautement distribuée, dynamique et hétérogène , le but est de pouvoir  prendre en compte différents critères de qualité de services (QoS) et les coûts énergétiques  avec une gestion des  differents niveaux de virtualisation ( conteneur,VM, OSGi etc.) et une tolérance au passage à l’échelle, aux changements de contexte (etat et performances du réseau, mobilité utilisateurs), aux pannes et au anomalies.

Contacts

tanissia.djemai@irit.fr, patricia.stolf@irit.fr, jean-marc.pierson@irit.fr, monteil@laas.fr

La prolifération des objets connectés et la demande croissante d’une distribution fondée sur le contenu ont motivé le développement d'approches centrées sur les données. De nos jours, les personnes utilisent leurs appareils pour partager leurs propres contenus et ils sont intéressés par d’autres contenus sans avoir à se soucier de leur localisation. Pour faire face à cette demande, le concept de réseaux centrés sur l'information «Information-Centric Networking» a vu le jour. ICN propose une nouvelle architecture où les contenus sont récupérés en utilisant des noms de contenus uniques à la place des adresses de nœuds. Cette approche peut fournir un service d'infrastructure de réseau mieux adapté à l'utilisation actuelle en termes de distribution de contenus, de mobilité et de défaillances dans l’Internet des objets.

L’objectif de ce stage est de proposer une stratégie de caching qui tient compte des limitations des réseaux de capteurs. L’idée est d’utiliser des techniques de placement de données permettant de réduire les temps de réponses ainsi que l'énergie consommée par le réseau. 

Figure 1 : « Stratégie de caching qui consiste à cacher sur la moitié du trajet »

Objectifs scientifiques

Les objectifs du stage sont :

 Etude des stratégies de caching existantes dans les réseaux de capteurs 

 Proposer une stratégie optimale pour le placement des contenus

 Evaluation de performance (Consommation d’énergie, diversité, stretch, délais, …)

Contacts

Ilyes.Fathallah@irit.fr, Ghada.Jaber@irit.fr, Rahim.Kacimi@irit.fr