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Context Presentation

This project is built in cooperation with Epurtek factory and INRAe who displays planted filters in Occitany, France and other countries. The actual network extends with the help of the regional GIS ‘EAU Toulouse and the national group of water Re-Use from Aqua-Valley and CapEnergy platforms. Major research and innovation issues are: 

1. To obtain and feed a pluri-topic data base from environmental sensors settled down into the filters for in-field, providing a spatially and temporally improved datasets that allows the implementation of deterministic models and open the black boxes of the filters sediment and soil. These models of transport and reaction (ex MIN3P) will describe the water and pollutants flows through the filters. This task started from cooperation between the research labs (UMR ECOLAB) at Toulouse, the university of La Rochelle, and UMR ECO&SOL from Montpellier.

 2. To demonstrate how the invertebrate addition in the filters will improve the purification efficiency in agreement with the biodiversity influence that governs natural ecosystem functioning. Research hypotheses will be tested in filter replicates at the level of lab microcosms, in campus pilots and across-campus comparisons.

 3. The assessment of biodiversity effects on filter benefits and services in terms of water quality providing, water quantity resource management, energy cost, recreational area for campus users, teaching and innovation supports.

 4. To provide a new generation filter that matches with the requirement of the recent European policies about water reuse quality and may be recognized as a new technology for local water cycle in our territories

Keywords

Planted Filter, Water, Biodiversity

Scientific goals

This garden provides the potential to become an outdoor living lab as a demonstrator of sustainable and low carbon solution for wastewater treatment and recycling though nature-based solution. The main challenge is to demonstrate the advantages of having a biodiverse and smart clean garden on a campus or a smart city, in terms of environment, economy, society (quality of life) and energy, by comparison with the classic filters. This implies an adaptative management of the water resource in cooperation with other research laboratories and stakeholders, as public water managers and private factories that wish to favor the ecological and energetic transition in this field.

Contacts

magali.gerino_at_univ-tlse3.fr, oceane.gilibert_at_univ-tlse3.fr, rahim.kacimi_at_irit.fr, arnaud.elger_at_univ-tlse3.fr

LEFE, SGE, IRIT, Toulouse University / IMFT, La Rochelle University / PME Epurteck

Keywords

Living Lab, water, filter, biodiversity, tomography

A Water oriented Living lab on the campus gets applied and fundamental research components with the main goal to reduce the surface area of the “regular” planted filters by making them more performing toward filtration with the involvement of an increased biodiversity. This demonstrator makes part of the LL implementation in the Interreg SUDOE Tr@nsnet Project. A cooperation between UT3 Direction du Patrimoine, SGE, UMR IRIT, UMR IMFT, U La Rochelle, PME Epurteck will lead to a bioinpired filter located next to IRIT to treat waste water of the A1 building. This biotech with enhanced biodiversity and soil metabolism for organic mater biodegradation, will increase the green area of the campus, will help at the air temperature regulation , and prevent of any smelt and musquitos for the neighbourhood. The earth worms (are ecological engineers that dig biostructure networks in the soil, that may largely influence the water parameters when flowing through this soil. The current tested research hypotheses is: « how does a burrow network buried in the macroporous substrates of soils influence the water infiltration capacities ? » This is run through the cooperation between research group in Physic “MacroPorous media and Biology” of UMR IMFT and the FERMAT X-ray tomography for images of 3D gallery networks of worms burrow, and modeling of water infiltration water flux in porous media; and the ecological team Bioref (Biodiversity, biological networks and Fluxes in aquatic and terrestrial ecosystems) of UMR Laboratory of Functional Ecology and Environment

Constant-head permeameter                               

Burrow network dig by one worm after 1 weak

Scientific goals

Create a demonstration of the biodiversity (earth worms) influence on the water infiltration in the planted filter.

Use the water oriented living lab connected with a serie of IoT sensors to explore further research hypotheses about organic mater degradation,  water and pollutant flow in this type of new filter generation.

Contact

magali.gerino_at_univ-tlse3.fr

IRIT – Université Toulouse 1 – Capitole

 Keywords

calibration, simulation, multi-agent system, AMAS    

In many fields of science and engineering, simulation is a key part in understanding phenomena or predicting their future evolution. It is also a useful tool for planners and decision-makers in order to guide them in their decisions. A simulation is a computer model of a real-world system that contains entities in interaction and that is used to understand and/or predict the evolution of the system it represents.  

 In order to be as close as possible to real phenomena, simulation models have to be calibrated. Several different calibration methods exist, from classical optimization methods to multi-agent systems and data assimilation. As most simulation models are complex systems, usual calibration methods are not really appropriate to account for dynamics changes. One way to handle those changes is to tune parameters values while the simulation is running, using data observed on the real system. One additional constraint is that models are seen as black boxes, i.e. the calibration system has no insight of the inner workings of the model. This means that the calibration system has to learn the influence of each parameter on each model observation.    

This work proposes a new online calibration method, CALICOBA, based on adaptive multi-agent systems, that aims to solve these problems. It features two kinds of agents: parameters and objectives. The role of objective agents is to estimate the distance of observations from the real data. Parameter agents take these distances to evaluate the best value the corresponding model parameter should take in order to minimize the distance computed by objective agents. Parameter agents have to learn their influence on each objective agent in order to compute the best value.    

For instance, in the case of a simple traffic model with two parameters (maximum vehicle speed and reaction time) and two observables (traffic density and mean vehicle speed). Lets assume that there is a data source for the actual roads represented by this model. The role of CALICOBA would be to take in the observed data and compare it to each observable in order to compute a distance for each. With this information, the parameter agents have to determine in which direction to modify their values in order to decrease these distances.    

As this is still a work in progress, the system has yet to be tested on traffic models, but it is planned for the near future.

Scientific goals

- Online self-calibration

- Automatic learning of model input/output interactions

Contact

Damien Vergnet – damien.vergnet_at_irit.fr

Frédéric Amblard – frederic.amblard_at_irit.fr

Elsy Kaddoum – elsy.kaddoum_at_irit.fr

Nicolas Verstaevel – nicolas.verstaevel_at_irit.fr

IRIT & LERASS – Toulouse University

Keywords

Simulation, réalité virtuelle, interaction phygitale

Design and development of a simulation platform to anticipate the impact of development projects on territories, particularly in terms of mobility.       

Simulation, rendu 3D et Interaction avancée

Scientific goals

Approach structured around 3 complementary research axes:

- Agent-based simulation : Simulate how traffic is distributed (qualitatively and quantitatively) in terms of

• Means of transport used,
• Distribution during the day
• Geographical distributionand as a function of the combination of
•  Urban development decisions (e.g., new bus station, subway, bicycle terminal)
• Changes in human behavior
• Economic considerations, PLU, etc.

-    3D display,  Virtual Reality : Make the results of the simulation understandable in a context of multi-actor mediation (from the architect to the citizens)

• Represent visually and in 3D the envisaged developments
• Tend towards a realistic representation

-    Managing the simulation thanks to Augmented Reality : Enable any decision-maker to simply express their suggestions in terms of planning using innovative interaction techniques

• Immersive interactive visualization
• Phygital Interaction: mixing digital data (representation means) and physical model (manipulation means)
• Gestural interaction

Contact

Emmanuel.Dubois_at_irit.fr

Le 12 mars 2021 de 14h à 18h se déroulera la demi-journée scientique neOCampus, en visioconférence:

https://zoom.us/j/91527338439?pwd=Q09nTVl2Nkc1WDg5S1JVdlJqR0ZyUT09

Les sujets de recherche des nouveaux doctorants ainsi que des stagiaires 2020-2021 seront présentés.

Le programme est disponible sur le lien suivant : ProgrammeJournéeNeOCampus_12mars2021_14H-VF

neOCampus - Marie-Pierre Gleizes

HybridIoT Estimation d’informations environnementales pour la ville durable - Davide Guastella

Des capteurs au service de la qualité de l’air - Aymen Sendi

SANDFOX Interface optimisée pour la gestion de l’énergie dans les bâtiments – IA pour la détection d’anomalies - Bérangère Lartigue

Un module auto-adaptatif pour l’intercompréhension dans un système multi-agent hétérogène - Guilhem Marcillaud

Calibration de modèles par système multi-agent adaptatif - Damien Vergnet

Intelligence Artificielle et Internet des Objets - François Thiébolt

Le 21 octobre 2020, le comité de programmation s’est réuni par vidéoconférence afin d’approuver les projets du quatrième et dernier appel à projets du programme Sudoe 2014-2020. 17 projets ont été approuvés dont 11 dans l’axe 1 et 6 dans l’axe 5, avec un montant FEDER programmé de 16 312 826.78 €.

Tr@nsnet : Living-Labs pour une transition écologique par l’intégration et l’interconnexion de réseaux hétérogènes complexes.

Porteur : Relations internationales de l'Université Toulouse IIIPaul Sabatier

Responsables MP Gleizes et G Zissis

Partenaires : Université Polyechnique de Madrid, Université de Lisbonne, Univesrité de Beira Interior Université de La Rochelle, FUSEAM Barcelone, CIRCE Zaragosse, CTA Séville

Date de début   01/10/2020

Date de fin       31/03/2023

Résumé : Tr@nsnet s’inscrit dans le défi de la Transition Écologique (TE) en proposant de définir un modèle de Living Lab (LL) dans un contexte d’Innovation Ouverte (OI). L’objectif est de créer un modèle générique de LL pour les universités (LLU), adaptable à la sphère privée. Il sera testé et validé sur des expérimentations; des réplications de démonstrateurs technologiques existants (smart light, IoT Home, coupl.électrique/thermique,..) et la création de nouveaux démonstrateurs (seconde vie des batteries, cycle de l’eau, mobilités,..). Ces expérimentations technologiques seront aussi des résultats importants du projet. Elles permettront d’évaluer l’intégration de réseaux de services complexes. Le modèle LLU proposé combinera le modèle du Cube d’Harmonisation (HC-Enoll), du Réseau Européen des Living Labs (Enoll), avec les outils du Regulatory Sandbox (RS), en prenant en compte les exigences commerciales et réglementaires (secteurs d’activités/territoires) des innovations. Tr@nsnet apportera un avantage qualitatif et profitera aux écosystèmes d’innovation de chaque région en ouvrant la recherche publique à l’industrie et aux utilisateurs.

Seront impliqués 5 campus universitaires comme bancs d’essai, ils profiteront aussi de l’expérience de 3 LL publics-privés de la zone SUDOE. Tous les partenaires de Tr@nsnet, contribueront ainsi à la TE : 5 universités seront prêtes à soumettre un dossier de labellisation auprès d’Enoll et 3 centres technologiques élargiront les connaissances en matière d’innovation. La diversité de ces partenaires et des régions auxquelles ils appartiennent, nous confronte à différentes approches qui enrichissent le projet et permettent des activités complémentaires. Tr@nsnet se veut innovant, il promeut la recherche technologique et l’étude de la réglementation qui favorise la croissance des entreprises innovantes, la responsabilisation et la protection des droits des consommateurs.

Le projet PIA Campus BTP et usages du numérique au travers de son porteur de projet, le lycée le Garros, vient d'être retenu sur l'appel à projet PIA. Nous avons contribué sur une fiche plateforme d'expérimentation sur un bâtiment à hauteur de 1 Million d'euros.

Lire le communiqué :

cp_orientation_et_formation_campusco_orientation_cmq (1)

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

neOCampus is a large operation with different kinds of projects and actors. Started in 2013, its goal is to improve the university campus user’s everyday life through data analysis for people, fluid consummation reduction, reduce building environmental footprint, etc.… Overall, it tends to make the campus smarter. All those projects have one common point: data. Including images, sensor logs, administrative data, configurations, we can find every kind of data and each must be stored somewhere.

This project is centered around this problem with a data management system architecture which is the data lake.The conception of this kind of solution must include handling every kind of data and making it possible to follow the life of a data from the input to the usage in a project. It does not only have to store every kind of data, it is needed to know what is stored, where and in the proper format to use it in the easiest way. When a new data has arrived, the system will automatically rawly store it, find the more valuable format, extract information from this data and make this knowledge available for any purpose.

 Keywords

Data Lake, Data Driven Project, Big Data, Data Management, Data Analysis

Scientific goal

•    To develop a datalake architecture to change the architecture of the data management system in neOCampus.

Contacts

dang.vincentnam@gmail.com, françois.thiebolt@irit.fr, olivier.teste@irit.fr