The continuous evolution of organised crime and terrorism makes it difficult for Law Enforcement Agencies (LEAs) to keep up with the latest and most advanced prevention and countermeasure solutions. The recent terrorist attacks that took place in various European cities and the increasing use of the Surface and Dark Web as well as of social media to organise and put in place serious criminal activities, such as the online child sexual exploitation and the humans, drugs and firearms trafficking, show the current inefficiency of LEAs with regard to the adoption of appropriate technological solutions. Still, the wealth of data available could already today — if exploited and co-related — enable early alerts for predicting and mitigating criminal and terrorist behaviours, provide evidence for constructing the crime timeline and identifying related actions and perpetrators during an investigation.
In such a context, CONNEXIONs helps LEAs to conduct the investigation and analysis processes in a more efficient and effective manner by improving their operational and situational awareness through the automated identification, interpretation, assessment, fusion, and correlation of evidence acquired from multiple heterogeneous big data sources.
CONNEXIONs achieves this objective by developing a next-generation investigation and prediction platform that builds upon the concept of multidimensional integration of heterogeneous multilingual and multimedia content (such as Web and social media), sensor data (such as signals from wearable and fixed sensors, as well as videos from drones, surveillance, and policemen wearable cameras), and the digital evidence trail in cyber (enabled and dependent) crimes.
The generation of automatic early warning alerts through the project platform will support police in predicting and preventing crime while the correlation and summarisation of evidence from multiple data sources will ease crime scene simulation and reconstruction. The police operator will finally navigate results in interactive mixed (augmented and virtual) reality and Internet of Things (IoT) environments.
Finally, the platform will integrate, semantically interpret, correlate and summarise multimodal content (multimedia evidence, reconstructed scenes and suspect profiles) for the visualisation of a crime timeline that would support the path-to-court and chain of custody of digital evidence.
The developed platform, tools, and technologies will be validated by the LEAs involved in the consortium in the context of a series of pilot use cases related to: (i) human trafficking investigation, (ii) counter terrorism security at large scale events, and (iii) serious crime investigation and training through 3D reconstruction.
To facilitate the uptake of the developed platform, tools and technologies, extensive training will be provided to the personnel of the LEAs involved through joint exercises based on hands-on experience and relevant training material.
Engineering is leading the research activities related to IoT data propagation and intelligence, dealing with the activation and control of sensors, intelligent data analytics and IoT information fusion. Furthermore, Engineering is also responsible for the investigative hypothesis simulation and analysis. Finally, Engineering is leader of the market analysis and exploitation plan.