Section: Partnerships and Cooperations

European Initiatives

FP7 & H2020 Projects

AGILE (H2020 project)

Participants : Emmanuel Baccelli, Cedric Adjih.

• Program: H2020 ICT-30-2015 Topic: Internet of Things and Platforms for Connected Smart Objects

• Project acronym: AGILE

• Project title: Adoptive Gateways for dIverse muLtiple Environments

• Duration: 2015-2017

• Coordinator: Emmanuel Baccelli

• Other partners: Canonical (UK), Eclipse IoT Foundation (IE), Mobistar (BE), Libelium (ES), Startupbootcamp IoT (SP), CREATE-NET (IT), iMinds (BE), Atos (SP), Rulemotion (UK), Jolocom (DE), Passau University (DE), Sky-Watch (DN), BioAssist (GR), Graz Technical University (AT), Eurotech (IT), IoTango (US).

• Abstract:

  The AGILE project is a 3-year H2020 project started in January 2016, which will deliver an integrated framework of open source tools and platforms that interoperate for enabling the delivery of adaptive, self-configurable and secure IoT elements (both software and hardware) that can be utilized in a variety of scenarios. Such tools target actors with heterogeneous skills, including entrepreneurs, researchers, and individuals, aiming to enable the realization of IoT applications respecting user privacy and data ownership.

Collaborations in European Programs, except FP7 & H2020

EU CHIST-ERA MACACO

Participants : Aline Carneiro Viana, Emmanuel Baccelli, Eduardo Mucelli.

• Program: EU CHIST-ERA, topic Context- and Content-Adaptive Communication Networks

• Project acronym: MACACO

• Project title: Mobile context-Adaptive CAching for COntent-centric networking

• Duration: 2013-2016

• Coordinator: Aline Carneiro Viana

• Other partners: INPT-ENSEEIHT at University of Toulouse, University of Birmingham (UK), SUPSI (Switzerland), CNR (Italy) and Federal University of Minas Gerais (Brazil)

• Abstract:

  MACACO (Mobile context-Adaptive CAching for COntent-centric networking ) is a 3-year CHIST-ERA European Project addressing the topic Context- and Content-Adaptive Communication Networks. It is funded by ANR in France, SNSF in Switzerland, and ESPRC in UK. It focus on data offloading mechanisms that take advantage of context and content information. Our intuition is that if it is possible to extract and forecast the behaviour of mobile network users in the threedimensional space of time, location and interest (i.e. ‘what’, ‘when’ and ‘where’ users are pulling data from the network), it is possible to derive efficient data offloading protocols. Such protocols would pre-fetch the identified data and cache it at the network edge at an earlier time, preferably when the mobile network is less charged, or offers better quality of service. This project has officially started in November 2013. The first annual report will be delivered before January 25, 2015.

ANR/BMBF SAFEST

Participants : Emmanuel Baccelli, Cedric Adjih, Oliver Hahm.

• Program: ANR/BMBF French-German partnership within CSOSG Framework

• Project acronym: SAFEST

• Project title: Social Area Framework for Early Security Triggers

• Duration: 2012-2015

• Coordinators: Emmanuel Baccelli (France), Jochen Schiller (Germany)

• Other partners: Freie Universitat Berlin, Fraunhofer, Hamburg University, Sagem, Daviko, FOS

• Abstract: Public spaces, such as airports, railway stations, or stadiums bring together large numbers of people on limited space to use security-sensitive infrastructure. These spaces pose two distinct challenges to public security: (a) detecting unauthorized intrusions and (b) monitoring large crowds in order to provide guidance in case of unexpected events (e.g., mass panic). To ensure the safety of the general public as well as individuals, we thus require a flexible and intelligent method for area surveillance. One example in which current monitoring systems proved to be dangerously inefficient is the Love Parade music festival in Duisburg, Germany, July 2010. Crowd control failed to provide guidance to a large crowd, resulting in a mass panic with 21 deaths and several hundred injured. In this particular case, overloaded communication infrastructure led to a lack of information about the density and the movement of the crowd, which in turn resulted in misjudgments on appropriate strategies to resolve the situation. This incident highlights the need for more sophisticated and reliable methods for area surveillance. The SAFEST project aims to analyse the social context of area surveillance and to develop a system that can fulfill this task, both in terms of technology as well as acceptance by the general public. The system will operate in distributed way, collect anonymised data, securely transfer this data to a central location for evaluation, and if necessary notify the operator and/or issue alerts directly to the general public. SAFEST addresses the following topics: (i) it proposes a solution for crisis management, addressing social, technical, and economic issues, (ii) it enhances the protection of the population against risks and dangers, including the evaluation of acceptance of said solution, and (iii) it addresses the protection of critical infrastructures by the means of a comprehensive technical solution. Project completed in 2015. One of its main result was the emergence of RIOT.