Our project aims to gain a deeper understanding of the operational procedures involved in resolving crimes, particularly focusing on data-driven evidence processing. This includes investigating the methods, tools, and type of evidence data utilized.

With this objective in mind, we aim to develop cutting-edge data analytics and artificial intelligence solutions to address the challenges of crime resolution while adhering to the regulations set by the European Union and its Member States regarding the collection of evidence data.

To achieve this, we plan to employ advanced forms of network analytics that enable the collaborative processing of sensor data and assumptions about the individuals involved. For instance, we will analyze data from cameras, number plate recognition systems, face detection systems, non-content data from communications, and other relevant sources. By leveraging this information, we can deduce approximate behavioral patterns of the perpetrators, aiding in the identification of suspects. 

The main development and coordination is carried out by an SME, whereas a specialized law firm (also SME) focuses on related fundamental right challenges. A university specialized in police training coordinates the training process, whereas a leading AI research institute assures the scientific quality of the solution. An ESP is responsible to create pseudo operational data (anonymized datasets). The main pilot shall be executed by a highly experienced
LEA with the support of a well renown research institute. Additional LEAs for the validation of the solution close the consortium partners. To measure the overall quality of the project a set of KPIs has been defined within the deliverables of each task/work package, meeting the requirements of the action.