Disaster Control Management

Itea2 5. Call 01.01.2012


The goal of the DiCoMa project is to ensure effective management of large disasters and complex emergencies by providing a set of tools that aim to improve the effectiveness of decision makers in dealing with disasters by better training and in situ support in the field. This toolset will include:

Data Abstraction tools:
A Comprehensive set of tools designed to process and correlate information from a large variety of public and private sources, allowing the creation of a unified data set, which can be easily explored and understood by decision makers.

Simulation and Modelling Tools:
DiCoMa proposes to create a suite of simulation tools that model both human behaviour and natural phenomena (i.e. fires, earthquakes, weather patterns.). The models will be based upon extensive theoretical work and field experience.

Decision Support and Training tools:
DiCoMa intends to create applications to be used by decision makers during both real and simulated disasters, that presents information to the decision maker in a manner that is easily and quickly understood, proposes alternative actions, indicating the implication of each alternative Using simulation modelling, and disseminates decisions to all personnel, equipment, and agencies involved in the disaster response process.


In recent years, the world has seen some dramatic disasters, both natural and manmade. Some spectacular examples include the Indian Ocean Tsunami in 2004, Hurricane Katrina in the same year, the terrorist attacks in Madrid (2004), London (2005), and Mumbai (2007), most recently, the earthquakes in Haiti and Chile (2010).

Disasters such as these are far beyond the ability of a single agency (even one funded by a large, wealthy government) to deal with, and require cooperation between multiple agencies, frequently from multiple countries. Moreover, decision makers dealing with such disasters are frequently swamped with massive amounts of often-conflicting information, on which decisions need to be made in real-time. Adding this to the need to take into account, social, political and economic factors, it is no wonder that many incorrect decisions are made, worsening an already difficult situation. On the other hand effective training of such situations, especially in a multinational setting, requires an enormous effort and thus cannot be used very often.