The term first responders usually refers to law enforcement, fire, and emergency medical personnel. These responders, however, are not the only assets that may be required in the aftermath of a strike on the homeland. In contrast, the more appropriate term, emergency responders, comprises all personnel within a community that might be needed in the event of a natural or technological (man-made) disaster or terrorist incident. These responders might include hazardous materials response teams, urban search and rescue assets, community emergency response teams, anti-terrorism units, special weapons and tactics teams, bomb squads, emergency management officials, municipal agencies, and private organizations responsible for transportation, communications, medical services, public health, disaster assistance, public works, and construction. In addition, professional responders and volunteers, private nonprofit, nongovernmental groups (NGOs), such as the Red Cross, can also play an important role in emergency response. As a result, the tasks that a national emergency response system would be required to perform are more complex than simply aiding victims at the scene of a disaster, carried out by several kinds of professional users with different roles and expertise. Moreover, emergency preparedness and response lifecycle is a complex process that consists of the preparation, response, and recovery from a disaster, including planning, logistical support, maintenance and diagnostics, training, and management as well as supporting the actual activities at a disaster site and post-recovery after the incident.

Developing and managing distributed systems is a complex task requiring expertise across multiple domains. This complexity considerably increases in swarm systems, which are highly dynamic and heterogeneous and require decentralised solutions that adapt to highly dynamic system conditions. The project TaRDIS focuses on supporting the correct and efficient development of applications for swarms and decentralised distributed systems, by combining a novel programming paradigm with a toolbox for supporting the development and executing of applications. TaRDIS proposes a language-independent event-driven programming paradigm that exposes, through an event-based interface, distribution abstractions and powerful decentralised machine learning primitives. The programming environment will assist in building correct systems by taking advantage of behavioural types to automatically analyse the component's interactions to ensure correctness-by-design of their applications, taking into account application invariants and the properties of the target execution environment. TaRDIS underlying distributed middleware will provide essential services, including data management and decentralised machine learning components. The middleware will hide the heterogeneity and address the dynamicity of the distributed execution environment by orchestrating and adapting the execution of different application components across devices in an autonomic and intelligent way. TaRDIS results will be integrated in a development environment, and also as standalone tools, both of which can be used for developing applications for swarm systems. The project results will be validated in the context of four different use cases provided by high impact industrial partners that range from swarms of satellites, decentralised dynamic marketplaces, decentralised machine learning solutions for personal-assistant applications, and the distributed control process of a smart factory.