The identification of waste and other environmental crimes poses a number of challenges for LEAs/BGs and other involved practitioners (e.g. environmental agencies, government agencies the police, tax authorities). In addition, the criminal prosecution process can be resource intensive (and there is a high standard of proof required to get a conviction). New technologies such as satellites, drones and deep learning/AI (and data merger with other datasets) are capable of providing synoptic high content data coverage of large areas of land or water, regularly and irrespective of inaccessibility or hazard. These can offer potential powerful solutions to the above issues surrounding the identification of environmental crime.
The ambition of EMERITUS is thus to explore and demonstrate how these technologies, integrated in single-entry point and scalable by-design platform, could improve the efficiency of environmental crime detection, intelligent risk profiling to reflect resources, reduce the risk for operators and provide a deterrent for offending.
Although other monitoring platforms and technology-specific solutions are currently at disposal LEAs/BGs, practitioners and decision-makers, the project intends to overcome the State-of-the-Art (SOA) bringing as unique selling proposition (USP) the following aspects:
1) Creation of a platform integrating diverse technologies to execute investigation protocols,
2) Integration of a dedicated waste-crime specific investigation protocol, to guide the use of the platform,
3) Strengthening cross-border perspective/vision providing an intelligence picture beyond national/local borders,
4) Creation of an integration layer scalable by design in order to allow in the long term to integrate other data sources/technologies,
5) Enabling collection of lawful court-proof of crime evidence, via blockchain experimentation and use of harmonized practices,
6) Community-based access, restricted access for partner LEAs/BGs, with a view on fostering international cooperation,
7) Integration of a dedicated training programmes including practical exercises (also embedded in the platform as reference experience/success cases) to empower LEAs/BGs in the use of such technologies,
8) High scalability of the solution, with possibility to progressively integrate other technological components.