The EU-SENSE project will provide an innovative technical solution to deal with selected shortcomings in CBRNe protection indicated in the ENCIRCLE Catalogue of Technologies. The created system will be a step-forward in chemical detection by developing a novel network of sensors that exploits advanced machine-learning and modelling algorithms for improved performance. The salient objectives of the project include development of an adaptable and multipurpose threat detection system (network of sensors, comprising both stationary and person-worn sensor nodes supported by environmental noise learning algorithm for false alarm rate reduction) and tools for enhancing situational awareness based on the sensor data (threat source location estimation and hazard prediction solutions). In general, the developed system will improve the threat detection capabilities and will increase state-of-the-art sensors reliability by networking and novel algorithms. Moreover, the project will implement a dedicated mode covering CB

The proposed solution aims to deliver a descriptive and predictive data analytics platform and related tools using state-of-the-art machine learning and artificial intelligence methods to prevent, detect, analyse, and combat criminal activities. AIDA will focus on cybercrime and terrorism, by addressing specific challenges related to law enforcement investigation and intelligence. While cybercrime and terrorism pose distinct problems and may rely on different input datasets, the analysis of this data can benefit from the application of the same fundamental technology base framework, endowed with Artificial Intelligence and Deep Learning techniques applied to big data analytics, and extended and tailored with crime- and task- specific additional analytic capabilities and tools. The resulting TRL-7 integrated, modular and flexible AIDA framework will include LE-specific effective, efficient and automated data mining and analytics services to deal with intelligence and investigation workflows, extensive content acquisition, information extraction and fusion, knowledge management and enrichment through novel applications of Big Data processing, machine learning, artificial intelligence, predictive and visual analytics. AIDA system and tools will be made available to LEAs through a secure sandbox environment that aims to raise the technological readiness level of the solutions through their application in operational environment with real data.

Law Enforcement Agencies (LEAs) across Europe face today important challenges in how they identify, gather and interpret terrorist generated content online. The Dark Web presents additional challenges due to its inaccessibility and the fact that undetected material can contribute to the advancement of terrorist violence and radicalisation. LEAs also face the challenge of extracting and summarising meaningful and relevant content hidden in huge amounts of online data to inform their resource deployment and investigations. In this context, the main objective of the TENSOR project is to provide a powerful terrorism intelligence platform offering LEAs fast and reliable planning and prevention functionalities for the early detection of terrorist organised activities, radicalisation and recruitment. The platform integrates a set of automated and semi-automated tools for efficient and effective searching, crawling, monitoring and gathering online terrorist-generated content from the Surface and the Dark Web; Internet penetration through intelligent dialogue-empowered bots; Information extraction from multimedia (e.g., video, images, audio) and multilingual content; Content categorisation, filtering and analysis; Real-time relevant content summarisation and visualisation; Creation of automated audit trails; Privacy-by-design and data protection. The project brings together industry, LEAs, legal experts and research institutions. It is expected that this collaboration will have significant impact on 1) ensuring the final system meets end-user LEA requirements, 2) enabling LEAs to access and examine terrorist generated content online bringing significant advantages to their operational capability, and 3) promoting industry’s enhanced understanding of operational LEA requirements and their market competitiveness in the field of online organised crime, terrorism and harmful-radicalisation.