Developing augmented reality tools to combat crime and terrorism

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DARLENE Augmented reality


Trilateral Reseach |
Dr Agata Gurzawska | Cluster Lead - Ethics, Human Rights and New Technologies

Date: 12 November 2020

Trilateral Research joins fourteen partners from across the EU in the recently launched three-year Horizon 2020 project DARLENE to develop innovative augmented reality (AR) tools which will improve situational awareness when responding to criminal and terrorist activities.

The project will investigate how cutting-edge AR technology combined with computer vision can be deployed to help law enforcement agencies (LEAs) make more informed and rapid decisions, especially in situations where time is of the essence and may make the difference between life and death.

Strengthening European public security

As threats to European public safety become more serious with each passing day, LEAs need to continuously undergo digital transformation to stay one step ahead of criminals and terrorists. Augmented reality (AR) holds massive potential for smart policing and unlocking the capacity to rapidly foster visual understanding of complex real-world scenes. Situational awareness is often critical to the survival and safety of officers and civilians in crime-fighting situations, and AR technology can greatly improve this vital skill by overlaying useful information directly on top of the real world. Currently available technologies, however, lack the processing capacity to deliver rapid, real-time scene interpretation necessary when responding to criminal and terrorist incidents.

The DARLENE project will combine innovative AR smart glass technology and powerful computer vision algorithms with 5G network architectures to allow agile processing of real-time data by LEAs even in high-pressure situations. The project aims to strengthen European public security by enabling LEAs to sort through massive volumes of data to better prevent criminal activities and respond more quickly and efficiently to crimes in progress.

The DARLENE solution will be developed in compliance with European societal values, fundamental rights and applicable legislation including privacy and protection of personal data. Strict adherence to the European Council ethical and legal requirements will be supported by an Ethics Board with invited external experts. Trilateral Research will develop an ethics and data protection protocol for the partners to address issues potentially raised by the project.

An ethical, data protection and social impact assessment of the DARLENE ecosystem will contribute to improving the confidence of citizens towards lawful use of AR technologies in law enforcement and public safety situations. Trilateral will also lead on building a community of end-users and security stakeholders that will guide the development process and evaluate the entire DARLENE ecosystem, thus paving the way to its field deployment and commercial uptake.

Meet the team

The DARLENE – ‘Deep AR Law Enforcement Ecosystem’ project was formally launched at a virtual kick-off meeting on 21-22 September 2020, which was attended by more than 40 representatives from partner organisations, including LEAs, research centres, academia and industry from across Europe. The meeting provided an opportunity to discuss the contributions of the different partners in relation to their areas of specialism and review the objectives of the project.

The project is coordinated by Dr Dimitrios Tzovaras from the Centre for Research & Technology Hellas (CERTH), one of the leading research centres in Greece. Other consortium members include FORTH – the Foundation for Research and Technology Hellas (Greece), Centre Tecnològic De Telecomunicacions De Catalunya (Spain), KU Leuven (Belgium), KEMEA – Center for Security Studies (Greece), Thales (France), eBOS (Cyprus), Youbiquo (Italy), Ertzaintza Basque local police (Spain), Polícia Judiciária (Portugal), the Bavarian Police Academy (Germany), Valencia local police (Spain), the Cyprus Police (Cyprus) and the Lithuanian police (Lithuania).

This project has received funding from the European Union’s Horizon 2020 Research and Innovation programme under grant agreement No 883297.

For more information please contact our team.

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