My proposed contribution has as target to help the operation of reconstruction of the changed environment map.
Obviously a natural event, like an earthquake, can change a lot of entities that are part of an urban environment, but there are still some entities that may not have been affected by the catastrophe (e.g. a particular building or a particular historical monument). The main idea is to send some survey agents (humans or automatic) that start to explore the changed environment, and they describe it to a central system in a simple and natural “language” from their perspective. For example an agent can say that he “sees” a collapse “in front of” the “main square” of the city, or that there are survivors “between” two collapsed buildings. Of course each agent will use a different way to describe the environment depending on his background and his task. The presence of fire will be probably described in different ways by firemen and red cross operators.
The central system will then process the received informations and try to derive new information to help rescue and aid operations. One useful task is to reconstruct the new map of the environment as good as possible, making approximation when needed and trying to extrapolate new informations from the information given by the agents. This new map will be used for all the rescue operations cited before. Also a support to decision making tasks (e.g. path finding, settlements of rescue camps, etc.) can be furnished. Presentation of data can differ depending on the task the final user has to achieve and of course from his cultural background. Obviously the new information can not be precise, but still reduce risks for rescue missions and reduce time to send aid where it is needed, without scattering rescue forces in useless ways.
Problems involved in the process of description’s reconstruction of the changed environment are various and of different nature. Below these problems are briefly described.
First of all the process of “recognition of known places” has to be considered or, in other words, the process that determine all the entities that did not undergo changes after the natural catastrophe.
The second task that can be identified regards how human and automatic agents communicate with the central system, furnishing information regarding the description of the environment from their point of view. Humans use typically a natural language to communicate and automatic agents use a “mathematical” language. It has to be noted that different human agents can refer to the same thing using different expression depending on their culture and tasks they are involved in. A fireman will describe a fire in a different way it is described by a red cross operator, due to his experience and knowledge in the field.
Humans expressions give typically qualitative descriptions instead of quantitative ones and also they give only a partial description of the entities. The system that reconstructs the map has to take these aspects into account.
Finally the last task is related to the final reconstruction of map. At this point it is possible to suppose to have a set of “known entities” (quantitatively described), a set of “unknown entities” and a set of relations that relate entities belonging to the two previous sets that give a qualitative description of the “unknown entities”. The target is to infer new information from the given one. One operation that can be addressed is to create a quantitative description of “unknown entities” as close as possible to the real characteristics of the entity. It is also possible to find out new qualitative relations among known and unknown entities. Problems to take into account concern the time performance requirements (the process of reconstruction has to be fast to help rescue missions) and also problems of consistence (descriptions given by different agents can contradict each other).
Within the proposed work only the last task will be addressed. The hypotesis are that the description of “known and unknown entities” is available and also problems regarding interpretation of natural language and communications among humans and automatic agents are solved. Characteristics arising from this steps are still to be considered in the phase of map reconstruction, like the qualitative and incomplete description of environment; these characteristics will bias how the map reconstruction task will be developed.