ICTLab > Research Projects

Research Projects

Together with most of the partners of this program, we are working on the two following projects.

ARCHIVES (Analysis and Reconstruction of Catastrophes in History within Interactive Virtual Environments and Simulations). The goal is to support historical research on past disasters with the help of advanced document image processing and analysis, information retrieval, machine learning, Geographical Information Systems (GIS) representation, expert user interaction and agent-based computer modelling. The case study considered is the Red River floods and their impacts on Hanoi over the past centuries.

SWARMS (Say and Watch: Automated image/sound Recognition for Mobile monitoring Systems). The objective of this project is to obtain a flexible and real-time monitoring network, which could supplement possibly existing (fixed) networks, and could then feed a decision-support system (through models and simulations of evolution scenarios) or support an advanced visualization of the phenomenon to monitor. The main idea is to study in a real context the feasibility of a smartphone-based monitoring network, where the devices are not only used as passive sensors but can also be actively used by their owners to transmit visual, voice and textual pieces of information to the monitoring system, in order to enable stakeholders to analyze and forecast information. Read More…

– ESCAPE is an ANR project that focus on the simulation of urban area evacuation in case of catastrophe. The simulator is based on the gama simulation platform and is based on agent-based modeling of the evacuation process: this allow to explore individually based strategy, including individual knowledge about evacuation plan, emotion during egress and individually based mobility model with several modes. The project focus on three case studies: chemical risk with industry explosion in the center of the city of Rouen (France), flash flood risk at the valley of Authion (France) and Hoa Binh dam break in the region of Hanoi – Red River (Vietnam).

– Gen* is an open source java library that make it possible to generate spatially explicit and socially connected synthetic population using any survey and GIS data. The toolkit is also available as a Gama plugin and can be used through the Kepler workflow management tool. How aim is to provide to computer scientist and none programmers the access to state of the art algorithms to solve synthetic population generation, explicit localization and network generation of synthetic entities. The library is under development but already provide several algorithms for each of this three part: gospl, spll and spin. See https://github.com/ANRGenstar/genstar for further information.

– AgroLD (The Agronomic Linked Data project): Recent advances in high-throughput technologies have resulted in tremendous increase in the amount of data in the agronomic domain. This data explosion in-conjunction with its heterogeneity presents a major challenge in adopting an integrative approach towards research. We are developing AgroLD, a knowledge system that exploits the Semantic Web technology and some of the relevant standard domain ontologies, to integrate information on rice species and in this way facilitating the formulation of new scientific hypotheses. The objective of this effort is to provide the community with a platform for domain specific knowledge, capable of answering complex biological questions. The current phase  covers information on genes, proteins, ontology associations, homology predictions, metabolic pathways, plant traits, and germplasm, on the Arabidopsis and rice species.