Section: Overall Objectives
Highlights of the Year
Electronic Sensors to measure the exposition of Health care worker to Tuberculosis
Direct observation has been widely used to assess interactions between healthcare workers (HCWs) and patients but is time-consuming and feasible only over short periods. We used a wireless sensors (RFID like) system to automatically measure HCW-patient interactions. Methods: We equipped 50 patient rooms with fixed sensors and 111 HCW volunteers with mobile sensors in two clinical wards of two hospitals. For 3 months, we recorded all interactions between HCWs and 54 patients under airborne precautions for suspected () or confirmed () tuberculosis. Number and duration of HCW entries into patient rooms were collected daily. Concomitantly, we directly observed room entries and interviewed HCWs to evaluate their self- perception of the number and duration of contacts with tuberculosis patients. The RFID was well accepted by HCWs. This original technique holds promise for accurately and continuously measuring interactions between HCWs and patients, as a less resource-consuming substitute for direct observation. The results could be used to model the transmission of significant pathogens. HCW perceptions of interactions with patients accurately reflected reality. Results are published in PLoS ONE 7(5): e37893. doi:10.1371/journal.pone.0037893 (See )
Network science as a tool to study the Complex Systems Science field: Dreams of Universality, Reality of Interdisciplinarity...
Using a large database (more than 215 000 records) of relevant articles, we empirically study the "complex systems" field and its claims to find universal principles applying to systems in general. The study of references shared by the papers allows us to obtain a global point of view on the structure of this highly interdisciplinary field. We show that its overall coherence does not arise from a universal theory but instead from computational techniques and fruitful adaptations of the idea of self-organization to specific systems. We also find that communication between different disciplines goes through specific "trading zones, i.e., sub-communities that create an interface around specific tools (a DNA microchip) or concepts (a network)  .
Equipex FIT (Futur Internet of Things)
Within the FIT project, DANTE is leading the IoT-LAB workpackage and testbeds (Internet of Things Lab). Through its IoT-LAB testbeds, the FIT project will provide a very large-scale infrastructure suitable for testing heterogeneous embedded communicating objects of all sorts. Going beyond the existing SensLAB testbed, a pioneering testbed for small wireless sensor devices, the five ECO testbeds developed within FIT will encompass the following test environments:
The testbeds will include a fleet of mobile robots which can be deployed to simulate a wide variety of different scenarios. The movement of each robot is controllable, and several smart objects can be embedded on each to simulate a Body Area Network. These mobile objects may act as an ad hoc network or use the fixed infrastructure that surrounds them to communicate via a real or emulated network. With full control of the network nodes and an access to the gateways these nodes are connected to, researchers are able to monitor their energy consumption as well as network-related metrics such as the end-to-end delay, throughput or overhead. DANTE leads the design of the software and hardware of all IoT-LAB nodes and a strong collaboration was set up with HiKoB company, created in 2011, an innovative startup in the field of sensor networking and embedded communicating measure.
Awards and honours
Classification of Content and Users in BitTorrent by Semi-supervised Learning Methods  was granted the best paper award at the 3rd International Workshop on Traffic Analysis and Classification (in conjunction with the 8th International Wireless Communications and Mobile Computing Conference, 2012). This result is part of M. Sokol PhD work, which is co-advised by Ph. Nain (Inria MAESTRO) and P. Gonçalves.
Best Paper Award : Classification of Content and Users in BitTorrent by Semi-supervised Learning Methods in 8th International Wireless Communications and Mobile Computing Conference (3rd International Workshop on Traffic Analysis and Classification).
K. Avrachenkov, P. Goncalves, A. Legout, M. Sokol.