Project Ideas presented at the Celtic-Plus Proposers Day on 28 October 2015 in Antwerp
SooGREEN Consortium extension (Gwénaëlle Delsart, Orange Labs, FRANCE)

SooGREEN objectives

  • SooGreen-logoE2E Services (OTT, P2P, Web browsing, IOT/WoT) power consumption for network architecture, user equipment, and datacenters
  • Services ( VoLTE, M2M, IOT) network and caching Performance Optimization, including VRAN
  • Service Delivery Interaction between mobile networks and smart-grid: services adaptation, demand-response, renewable energy business model to evaluate investment opportunities
  • Technical Environment optimization for base stations (power conversion, power back-up) and central offices (cooling)

SooGreen was labelled as Celtic Plus project on 14 November 2014
The project activity has just started: 1st July 2015 up to 30th June 2018

Looking for the following additional expertise to enhance the current consortium:

  • Industry, Telco, SME, University/Research
  • New kind of services: OTT, P2P, web browsing, IOT/WOT, VoLTE, M2M, D2
  • Mobile Network: Optimization of Radio Access Network and Content
  • Delivery solutions, Energy consumption in Virtual Radio Access Network
  • Energy : Interaction between service delivery in mobile networks and smart-grid

Contact:

Gwénaëlle Delsart, Orange Labs, SooGREEN Project Coordinator
2 avenue Pierre Marzin, 22307 Lannion Cedex
E-mail: gwenaelle.delsart (at) orange.com
Tel: +33 2 96 07 33 53
https://soogreen.cms.orange-labs.fr/soogreen

Take advantage of mobile waves, WIFI…and the Telcos’s data for the environment (Pierre-Henri Simon, Orange, FRANCE)

Green-logoMobiles Waves…for forecasting pollution, weather…
Measuring rainfall with mobile phone networks is already used: The electromagnetic signals transmitted from one mobile telecommunication antenna to another are attenuated by rainfall.
The rise and fall of signal strength in each “link” provides an average measure how much rain is between them.

With the new range of wave length (5G…lower wave length than 4G), it can be worthwhile to look for: new use-cases (air pollution sensor), improving existing ones (weather predictions)

Local Waves (WIFI)…for health
It seems that WIFI could be used for cardiac tracking. Therefore, use-cases with local waves could be also researched.

Various sources of data (Local waves, Mobile waves, IoT’s data)
could be combined to reinforce the identification of a phenomenon
E.g. air pollution by crossing the analysis of mobile waves with the analysis of the heart rhythm (or others personal signals through local sensor)

Beside their usual business (voice, data), the Telcos could take advantage of:

  • their network (global and local) and also the future IoT network
  • their ability to gather and analyse a huge and various amount of data,
    … to bring new services to the society in relationship with hot issues (environment, health)

Because network is deployed and the data centers are operational it could be a big opportunity with low investment.

Main competences: transmission, radars, signal processing, data mining, big data analysis

Contact:

Pierre-Henri Simon, Orange, OLPS/OPENSERV
Via: valerie.blavette (at) orange.com

Secure and accurate road weather services composed from vehicle and RWS data (Patricia Ortiz, Innovalia, SPAIN)

Objectives:

  • In suburban road areas, there are some dangerous hot spots depending on dynamic weather conditions; local large predictions are needed
  • Sources: Roadside units (RSU) and combined roadside units, Road weather stations (RSU/RWS), Additional instrumentation in vehicles
  • All vehicles could take benefit, including the ones not equipped with CAN-bus readers, OBUs or Internet access.
  • A system allowing to warn any driver with practically any kind of on-board inRaod&Weatherstrumentation
  • Security mechanisms in place (user privacy and content protection to unauthorized access and modification)

Expertise needed:

  • Meteorological specialists both for large prediction and for computing local prediction using various vehicles and RSU data combined with large predictions.
  • Vehicle manufacturers / Vehicle OEM manufacturers
  • Cities and Road authorities
  • Sensor manufacturers
  • Network operators
  • School bus companies and truck operators

Contacts:

Patricia Ortiz, portiz (at) innovalia.org
Timo Sukuvaara, timo.sukuvaara (at) fmi.fi
Bertrand Ducourthial, Bertrand.Ducourthial (at) utc.fr

Smart City Micro Services (Steven Van den Berghe, Sirris, BELGIUM)

What if we could connect, understand and interact with individual things at the scale of a city; and use this to implement common goals (e.g. energy saving, transportation, …)Smart-City-Micro-Services1

1. Platform for Decision making on large scale heterogeneous IoT deployments.

  • Heterogeneous Behaviour
  • Heterogeneous Connectivity
  • Heterogeneous Goals

2. For things & people (e.g. mobile interactions)

Potential topics:

  • IoT connectivity
  • IoT platform services
  • Data analysis, simulation, visualisation, predictive mSmart-City-Micro-Services2odels

Contact:

Steven Van den Berghe
Senior Technology Advisor
Sirris
Steven.vandenberghe (at) sirris.be

digiPIL - the Digital Patient Information Leaflet (Alex Vakaloudis, Cork Institute of Technology, IRELAND)

Goal: Replace Patient Information Leaflets (PIL)

  • Public Health – Easy access to critical medicines information (during the course of treatment)
  • Patients, Physicians, Pharmacists – Improvement in patient compliance, Increased reporting of Adverse Drug Reactions, No interruptions to medication supply
  • Pharma companies – Simplification of supply-chain, Improved
  • Pharmacovigilance through
    increased ADR reporting and tackling of counterfeit medication

Outcome:

  • Recommendations for digital PIL delivery based on user-testing and field trials
  • Development of platforms to digitise PIL delivery and improve effect of medications

Impacts:

  • Increase patient awareness of critical medicines information
  • Improve patient compliance with dosing and administration
    Changes to EU Regulations

Schedule: 12-24 months

Looking for:
More Pharmaceutical companies – Access to electronic PIL, Project support/Endorsement
NGOs – Use cases, pilot studies
Regulatory Authorities – Project Endorsement and Collaboration

Contacts:

Dr Chris Edlin, PMTC: chris.edlin (at) pmtc.ie, www.pmtc.ie
Dr. Alex Vakaloudis: alex.vakaloudis (at) cit.ie, www.nimbus.cit.ie

Big Data for Earth Observation (Sébastien Lefèvre, Université Bretagne Sud / IRISA, FRANCE)

Vision: Earth Observation is today in the Big Data era

Motivation: Big Data from Space becomes real but technological challenges remain

Content:

  • efficient access to EO data
  • data pre-processing
  • data mining
  • visual analytics
  • evaluation methodology
  • validation (use cases)
  • towards exploitation (sustainable architecture and services)

Outcome:

Technological advances in IT that will support EO data/market growth
Impact: New technologies, new services for a fast growing market

Looking for partners/expertise in:

SMEs, Major IT companies, academics (if complementary skills)
Infrastructure for big data, EO-related use cases, Technologies for data analytics

Contact:

Prof. Sébastien Lefèvre, Université Bretagne Sud / IRISA
sebastien.lefevre (at) univ-ubs.fr, Tel: +33 6 45 33 09 41
Campus de Tohannic, 56000 Vannes, France
http://people.irisa.fr/Sebastien.Lefevre, http://www.irisa.fr/obelix

Wearable IoT Network Solution for Work Safety in Hazardous Industrial Environments - WINS@HI (Ayse Belma Kaya, Netas, TURKEY)

Main Goals:

  • Assessment of Risks and Preventing Accidents
  • Improving Work Safety of Underground Workers
  • In Case of Occupational Injuries and Hazards:WinsatHigh2
    • Tracking Location of Workers
    • Remote Health Monitoring
    • Guiding Emergency and Rescue Units

Content:

  • Wearable Sensor Networks
  • Wireless Underground/Indoor Communication
  • Data Analytics
  • Network Anomaly Detection and Monitoring Algorithms
  • Disaster/Emergency ManagementWinsatHigh1

Status: Project (WINS@HI) is labelled and about to start

Use Cases:

  • Mining Industry, Tunnels and Subways, …
  • Pre-Accident (e.g. health monitoring, location tracking, gas sensoring,
  • Post-Accident (e.g. guiding rescue teams, location detection)

Contacts:

A.Belma Kaya, R&D Director, belmas (at) netas.com.tr
Ersin Bayramoglu, Project Coordinator, ersin (at) netas.com.tr
Caner Aksoy, Technical Coordinator, caksoy (at) netas.com.tr

5G connected cloud-based video analytics (Cornelius Hellge, Fraunhofer HHI, GERMANY)

Project vision

  • 5G + video compression technologies (HEVC) + adaptive streaming
  • Enabler for robust mobile transmission of video data from large number of
  • video sensors to the cloud5G-cloud
  • Cloud + machine learning
  • Enabler for large scale video understanding

Project focus

  • Evaluate 5G specific features for high capacity and mobile links closely following 5G standardization: M-MIMO, Network slicing, low latency
  • Research on interaction between video compression, adaptive
    streaming, wireless link, and machine learning algorithms
  • Develop use cases and business plan

Expected outcome

  • Solution for secure, reliable, and adaptive mobile video analytics over 5G mobile links
  • Develop business cases
  • Facilitate use cases by new technologies and bring them closer to the market
  • Contribute to standardization

Schedule

  • Proposal submission e.g. to next call in 2016
  • Duration 3 years (Closely linked to 5G standardization timeline)

Contact:
Cornelius Hellge
cornelius.hellge (at) hhi.fraunhofer.de, Tel. +49 30 31002 239

SHAAPING - Support of Healthy Ageing through big data Analysis and multifactorial intervention on Preventing development of frailty in Pre-frail older population (Stefan van Baelen, iMinds, BELGIUM)

Development and deployment in elderly living environment of an open and scalable frame-work to prevent the frailty and launch appropriate interventions to mitigate the potential risk

Context:

  • By 2050 population 60+ is expected to reach Worldwide: 2 billions; EU: 150 millions, 80 millions in 2008

Frailty:

  • Progressive decline of healthy and independent living; Affects 15-20% of individuals 65+.
  • It can be reversible: early detection + appropriate intervention

Expected Impact:

  • 20% reduction of hospital admissions help people to remain healthy and maintain their independence at home;
  • Reduction the healthcare and care cost and improve the quality of life of family and relatives

Innovation:

  • Development of large scale steaming data analysis tools
  • Development of an open, interoperable and scalable platform dealing with sensitive data and privacy and ethic aspects
  • Characterization and detection of pre-frail persons: launching appropriate interventions to mitigate the potential risk

Targeted market:

  • Products and services for Ageing well
  • Silver Economy: $7 trillion per year (3rd largest economy in the world)
  • 3 trillion euros is the wealth of 65+ in EU

Contact:

Hassane Essafi, Program Coordinator, Institut CEA LIST
hassane.essafi (at) cea.fr, Tel: +33 16908 1387

From packet to info-oriented networks (Dimitri Papadimitriou, Alcatel-Lucent Bell N.V., BELGIUM)

Project objectives
Explore first order principles and network models to “design” info GTW

Main challenges
1. Universality and genericity® target replacement or “overlay”
2. Remove dependence on dest. locator-based only exchange
⇒Rethink localization function (e.g. information grouping)
3. Dynamics in spatial distribution of information without specialization (host vs. network nodes)
⇒Principle of performing routing decisions before “localization“ becomes inefficient if ever achievable (#routes ~ #data objects)

Project structure and expertise:
Step 1:

  • – Skills: TCS, comp./alg. learning theory, comp. intelligence (EA)
  • – Task: procedures, algorithms and proofs
  • – Outcome: theoretic validation

Step 2:

  • – Skills: stat. inference, data-driven/unsupervised ML, optimization (combinatorial, continuous, robust)
  • – Task: programs and numeric evaluation
  • – Outcome: alg. design choices and performance evaluation

Step 3:

  • – Skills: software development (HL), experimental evaluation
  • – Task: develop abstract protocol model/components
  • – Outcome: demonstrator

Contact:

Dimitri Papadimitriou (Bell Labs)
dimitri.papadimitriou (at) alcatel-lucent.com

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