Periodic Reporting for period 2 - CREST (Fighting Crime and TerroRism with an IoT-enabled Autonomous Platform based on an Ecosystem of Advanced IntelligEnce, Operations, and InveStigation Technologies)
Reporting period: 2021-06-01 to 2023-02-28
CREST's overall objective was to improve the effectiveness and efficiency of LEAs intelligence, operation, and investigation capabilities, through the automated detection, identification, assessment, fusion, and correlation of evidence acquired from heterogeneous multimodal data streams. Such data streams include Web and social media sources and interactions, IoT-enabled devices (including wearable sensors), surveillance cameras (static, wearable, or mounted on UxVs), and seized devices and hard disks.
CREST offers: (i) crime and terrorism prediction and prevention through the generation of automatic early warning alerts based on the assessment of threats detected using targeted monitoring, tracking, and analytics technologies; (ii) improved operational capabilities enabled by an IoT ecosystem that facilitates adaptive and dynamic mission planning and navigation based on autonomous systems for better surveillance and distributed planning and management for supporting distributed operational command and control; (iii) improved situational awareness through advanced visual analytics, mobile applications, and projections in interactive augmented reality environments; (iv) enhanced investigation capabilities by increasing the confidence and trustworthiness of information sharing and digital evidence exchange based on blockchain technologies; and (v) Integrated platform based on ethics and privacy-by-design principles, implementing EU legal requirements, whilst being highly customisable to local legislation.
The adoption of the CREST solutions for enhancing the fight against security threats will have impact on how citizens and the civil society interact with the local LEAs and their use of technologies for fighting crime through shaping the citizens’ perception of safety and security, and increasing the security levels of communities and the resilience of Member States in dealing with current and future security threats.
The developed tools and platform were validated in a series of field tests and demonstrations in three Pilot Use Cases: (i) Protection of public figures in motorcades and public spaces, (ii) Counter terrorism security in crowded areas, and (iii) Cross-border fight against organised crime.
The CREST solution encompasses the entire lifecycle of law enforcement operations including intelligence gathering, mission planning, mission execution, and investigation. The services deployed are built upon the concept of multidimensional integration and correlation of heterogeneous multimodal data streams and delivery of pertinent information to different stakeholders in an interactive manner tailored to their needs.
In particular, CREST enhances the operational and (near) real-time situational awareness by developing an innovative prediction, prevention, operation, and investigation platform equipped with tools for:
• Threat detection and assessment;
• Dynamic mission planning and adaptive navigation for improved surveillance based on autonomous systems;
• Distributed command and control of law enforcement missions;
• Sharing of information and exchange of digital evidence based on blockchain;
• Delivery of pertinent information to different stakeholders in an interactive manner tailored to their needs.
CREST also conducted a number of dissemination and collaboration activities during the life of the project, including (i) participation in events, conferences and workshops; (ii) publication of scientific papers; (iii) generation of dissemination material; (iv) establishment of web and social media presence; (v) creation of synergies with related projects; and (vi) establishment of a stakeholder network. Moreover, an initial market analysis, exploitation plan, and business models were also delivered. Finally, the ethical, legal, and security guidelines and processes were set up and followed.
Hence, CREST had the following impacts: (i) Provision of novel, user-friendly technologies, tools and/or systems, addressing traditional or emerging forms of crime and terrorism at acceptable costs; (ii) Improved investigation capabilities, especially regarding quality and speed, through cutting-edge automated technologies; (iii) Increased efficiency and effectiveness of the information sharing among EU LEAs through the employment of blockchain technologies; (iv) Prevention and reduction of criminal and terrorist threats; and (v) harmonisation of information formats at international level, improved cross-border acceptance and exchange of court-proof evidence, standardised evidence collection and harmonised procedures in the investigation of trans-border crimes.
The final result of CREST is an innovative prediction, prevention, operation, and investigation platform and solutions which aim to improve the state-of-the-art in several scientific and technological fields, thus facilitating the implementation of the promised impact; these include:
(i) Information extraction and representation from multimodal stream data for enabling the accurate and timely interpretation of sensor readings based IoT fusion and perform visual analysis on multimodal data streams.
(ii) Artificial Intelligence for dynamic mission planning and adaptive navigation in autonomous systems for the better surveillance of
public areas by conducting dynamic UxV swarm optimisation and optimised rerouting in case of abnormal situations encountered during the execution of LEA operations.
(iii) Multimodal information analysis and correlation for threat detection for assessing threats and providing early warnings based on multimodal data analytics.
(iv) Distributed command and control of law enforcement missions and information sharing for facilitating the efficient collaboration of LEAs across organisational boundaries.
(v) Multimodal information delivery for improving situational awareness, through the provision of pertinent information based on visual analytics, augmented reality, and mobile applications for dynamic on-site information.