Proposals must cover one or several of the scopes described below:

• To improve the decision making process, the quality of the basic input, i.e. data from sensors, needs to be significantly enhanced. Future detection devices need to target a broader spectrum of agents with higher sensitivity and selectivity at relevant response times, compared to existing devices. Their improved capability should preferably be demonstrated via benchmarking against current sensors as well as against agents of interest. The ability to rapidly detect hazards without sampling, preferably at safe distances, is desirable. The main scope of this call is development of technology and components (including algorithms for improved data extraction, risk assessment and spread prediction).
• Methodology for identification and characterisation of agents in complex bio-samples including sampling procedures also needs to be further developed. Methods that can initially provide indicative results for rapid response, but also provide data for deeper analysis such as characterisation of properties of relevance for protection and treatment, as well as identification of previously uncharacterised agents, are preferred. Such deeper analysis can be done in the field or in specialised analysis reference centres. Development of tools (or databases) necessary for the characterisation of non-standard or modified organisms and discrimination between natural/antagonistic origin of an outbreak is also required. As part of the DIM concept, sampling capability in different matrices should also be addressed.
• Incorporations of novel and/or disruptive technologies is also encouraged, for instance, development of detectors on unconventional platforms and usage of AI for agent classifications. It is essential that the research activities generates new and improved DIM capability according to requirements generated from the operational need of the MS military forces. There is a specific need to reduce logistics in military operations, so next generation CBRN DIM systems should strive towards being mobile, fieldable, modular, scalable and adaptable to the nature of the mission. Also the system should be user-friendly and be as autonomous as possible. Handling must not be entirely dependent on personnel with a scientific background.
• The interpretation of comprehensive DIM data into assessments of risk areas, mapping of strategic CBRN capacities and other decision making processes requires development of advanced methods to interpret and present the information (i.e. virtual reality/augmented reality, real-time data fusion methodologies, uncertainty analyses and dispersion model protocols). In addition, methods for background signal discrimination and prediction of potential dissemination source have to be improved.
• In order to achieve utilisation and adaptation of the latest scientific developments, realisation of the technology into products and to ensure applied usage of the systems, several partners are required. It must be outlined in the project proposal how the active involvement from industry, defence research organisations and academia as well as end users will be achieved.