Managing Affective-learning THrough Intelligent atoms and Smart InteractionS

(co-financed by the European Commission under Grant agreement 687772)

2016-2018

MaTHiSiS is a H2020 project under the topic ICT-20-2015 Technologies for better human learning and teaching with a total cost of €7.618.584.

The MaTHiSiS learning vision is to provide a product-system for vocational training and mainstream education for both individuals with an intellectual disablity and non-diagnosed ones. This product-system consists of an integrated platform, along with a set of re-usable learning components (educational material, digital educational artefacts etc.), which will respond to the needs of a future educational framework, as drawn by the call, and provide capabilities for: i) adaptive learning, ii) automatic feedback, iii) automatic assessment of learner’s progress and behavioural state, iv) affective learning and v) game-based learning.

The MaTHiSiS consortium is coordinated by Atos Spain and consists of 18 beneficiary organizations from 9 different Member States collaborating, namely Spain, France, Greece, UK, Netherlands, Belgium, Italy, Lithuania and Germany.

 

 FORENsic evidence gathering autonomous senSOR

(co-financed by the European Commission under Grant agreement 653355)

2015-2018

The FORENSOR project aims to develop a novel, ultra-low-power, intelligent, miniaturised, low-cost, wireless, autonomous sensor (“FORENSOR”) for evidence gathering. The combination of built-in intelligence with ultra-low power consumption will make this device a true breakthrough for combating crime. FORENSOR is an EU Horizon 2020 funded project (call identifier: H2020-FCT-2014), under the grant agreement no: 653355. The project started on the 1st of September 2015 and will last for 36 months with a total cost of €4,9M.

FORENSOR aims to develop and validate a novel, ultra-low-power, miniaturised, low-cost, wireless, autonomous sensor (“FORENSOR”) for evidence gathering, able to operate for up to two months without infrastructure. FORENSOR will be manageable remotely, will preserve the availability and the integrity of the evidence collected, and comply with all legal and ethical standards, in particular those related to privacy and personal data protection. Secure and intelligent communications let such sensors join their forces towards robust evidence management and real time monitoring and control operations. The combination of built-in intelligence with ultra-low power consumption will make this device a true breakthrough for combating crime.

 Securing Critical Energy Infrastructure 

(co-financed by the European Commission under Grant agreement 700416)

2016-2019

SUCCESS is a H2020 project under the topic H2020-DRS-2015. The SUCCESS project will develop an overarching approach to threat and countermeasure analysis with special focus on the vulnerabilities introduced by Smart Meters. The project aims at designing, developing and validating on small scale field trials a novel holistic adaptable security framework which is able to significantly reduce the risks for additional potential cyber threats and attacks when next generation real time scalable unbundled smart meters are deployed along smart electricity grid, which enable innovative application and value added services within the emerging smart decentralized energy system paradigm.The project started on the 1st of April 2016 and will last for 30 months with a total cost of €5M. 

Advanced Video Surveillance archives search Engine for security applications

This project has received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement nr. 285024

2012-2015

ADVISE was a research project co-funded by the FP7-Security Workprogramme of the European Commission, aimed at designing and developing a unification framework for surveillance-footage archive systems. The ADVISE project results ease the work of law enforcement authorities in their fight against crime and terrorism, through negotiation of all relevant legal, ethical and privacy constraints, and through location based video archive selection and efficient evidence mining of multiple, heterogeneous video archives. In a context where surveillance systems are continuously growing in scale, heterogeneity and capabilities, two major obstacles have to be overcome. On the one hand, the variety of technical components of surveillance systems, producing video repositories with different compression formats, indexing systems, data storage formats sources, has to be addressed. On the other hand, the legal, ethical and privacy rules that govern surveillance and the produced content have to be taken into account. To address these two major issues, the ADVISE system was composed by two major components: the first one performing the semantically enriched, event based video analysis which offered efficient search capabilities of video archives and sophisticated result visualization, and the second one enforced the legal, ethical and privacy constraints that applied to the exchange and processing of surveillance data. In addition, in order to support interoperability, the exchanged content and the associated metadata has been transformed into a common format, while a dedicated ADVISE Engine has been developed to efficiently deal with each surveillance and collaborating authority’s technical and legal/ethical/privacy specificities.

Integrated Assessment of Societal Impacts of Emerging Science and Technology from within Epistemic Networks

This project has received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement nr. 288971

2012-2015

Keywords:

integrated assessment, technology assessment, data protection impact assessment, interdisciplinarity, responsible research and innovation

The EPINET project introduces a new approach to promote integration of technology assessment (TA) methods. It will develop methods and criteria to be used for more socially robust and efficient practices on the interfaces between TA and the world of policy makers and innovators. EPINET introduces the concept of epistemic networks as a way of conceptualising complex developments within emerging fields of sociotechnical innovation practices. It establishes a "soft" framework within which the plurality of different TA practices can be explored in a concerted manner. Four cases are investigated along with the development of this framework: wearable sensors, cognition for technical systems, synthetic meat and smart grids. "Integrating TA", it is claimed, is a task for empirical investigation in which implicit values of TA methodologies, disciplines and practices are spelled out and placed in relation to the practices they are meant to assess. EPINET develops a framework for integrating assessments through gradual co-production of methodologies and concepts (centrally that of "responsible innovation") together with innovators and policy makers. The challenges of "integrating assessments", we claim, can only be gradually worked out within such a holistic view of complex intersecting networks and practices.

Checking Assumptions aND promoting responsibility In smart Development projects

(co-financed by the European Commission)

 2017

This project will study aspects of the 'smart' agenda in which practitioners from the Social and Human Sciences (SSH) offer unique and valuable insights of relevance to innovators and researchers in the ICT – LEIT (Leadership in Enabling and Industrial Technologies) areas. Centred on topics concerning users, design, digital rights and critical infrastructures, CANDID will engage SSH and ICT - LEIT researchers in ´extended peer communications' aiming at Responsible Innovation.

A Privacy Impact Assessment Framework for data protection and privacy rights

2011-2012 

co-funded by the European Union under the Fundamental Rights and Citizenship Programme

The PIAF project aimed to encourage the European Union and its Member States to adopt a progressive privacy impact assessment (PIA) policy as a means of addressing needs and challenges related to privacy and to the processing of personal data. The 22-month project included, in its first phase, a review of PIA policies and practices in Australia, Canada, Hong Kong, Ireland, New Zealand, the US and UK to identify which elements may be used effectively to construct a model framework applicable to the EU. In the second phase, the project concluded empirical research with regard to factors that affect the adoption of a PIA policy in the EU Member States. Both phases concluded with workshops where the findings were presented and discussed. Eventually, the PIAF project was concluded with recommendations to the European Commission and the EU Member States as well as to organisations carrying out PIA. In addition, the project partners presented the their findings at numerous third-party workshops and conferences and prepared several papers in scholarly publications.

Availability

Address: 

Pleinlaan 2

1050 Elsene, Brussels

Belgium

+32 2 629 24 60

dpialab@vub.ac.be 

www.dpialab.org

www.dpialab.brussels

www.vub.ac.be/LSTS/dpialab

 

About us

d.pia.lab

Brussels Laboratory for Data Protection & Privacy Impact Assessments

Research Group on Law, Science, Technology & Society (LSTS)

Faculty of Law and Criminology

Vrije Universiteit Brussel

 

 

 

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