Data fusion in Critical infrastructures

Usually, critical infrastructure systems combine the information coming from their sensors individually, without sharing any information regarding the state of their functioning with other infrastructures. However, during real-time situations, the combination of information regarding the functioning of different infrastructures may be effective. To this regard, I am developing a class of data fusion algorithms that allow the exchange of the possible cause of fault or threat affecting those systems, in order to increase their awareness. Such algorithms are based on the Transferable Belief Model and apply to dynamic topologies in order to keep into account the fact that during emergency situations the communications among the systems may be unavailable at certain times. The exchange of information among the infrastructures, based on such algorithms, may can be valuable for decision makers during emergency times to take proper countermeasures. More information on this topic will be found soon in two publications.