As DARLENE will be used by police officers, a major objective was the elicitation of end-user requirements and the definition of use cases that realistically capture the conditions under which police operations are carried out. To this end, online surveys and co-creation workshops were carried out with the participation of police officers, following a systematic approach that led to the definition of the DARLENE architecture in a way that satisfies the needs of police, supports the foreseen use cases, and conforms to legal and ethical requirements.
A significant result is the wearable, portable prototype developed for police officers, which comprises an Augmented Reality helmet and a computation unit that implements advanced Artificial Intelligence (AI) to analyse in real-time user’s field of view. This prototype, entitled Wearable Edge Computing Node (WECN) is further evolved and updated based on hands-on interaction and evaluation with police officers in the planned training and piloting sessions. In a related line of research, AI methodologies have been developed for the other two computation layers of DARLENE, namely the cloud and the intermediate Patrol Car Edge Node (PCEN).
To interconnect the different computation layers of DARLENE, research has been focussed on the development of a private 5G infrastructure, while cyber-secure mechanisms have been developed for the authentication of different computation nodes. To allow for a personalized and adaptive AR experience, AR widgets have been designed that support different levels of detail that adapt to user preferences and stress status. Another interesting technological result has been the development of the DARLENE Command & Control application that visualises a 3D model of an operation site enriched with real-time information from AI algorithms. Further to this end, 3D reconstructions have been extracted from the project’s pilot sites.
Major effort has been put into defining a concrete ethical and legal framework for the application of DARLENE and the realisation of its piloting activities. To this end, extensive research has been performed on the ethical implications of the project with specific contributions in the way the proposed technology can be used to mitigate AI bias and limit the need for data storage via real-time analysis. Complementary activities to this end, have been the operation of an external Ethics Advisory Board and clearance from independent Ethics Committees prior to any research with human participation. In the same period, several horizontal activities took place to raise awareness concerning project results with extensive coverage by the press and media.
