The problem of selecting correct counterparts to interact with is of particular relevance in open and dynamic environments. This problem increases when third parties may vary their behaviour at will. In this paper we examine the problem of service provider selection using trust and reputation techniques. Most approaches to service provider selection are based on the client's proper experiences about particular services from particular providers. A problem arises when no previous experience is available. To solve this problem, previous approaches have proposed that clients obtain the required reputation information from their acquaintances. In contrast, our work advocates an experience-based approach for service provider selection, in which clients use trust and reputation mechanisms to infer expectations of future providers' behaviour from past experiences in similar situations. We present some experimental results that support our proposal.

In this paper, we consider the route coordination problem in emergency evacuation of large smart buildings. The building evacuation time is crucial in saving lives in emergency situations caused by imminent natural or man-made threats and disasters. Conventional approaches to evacuation route coordination are static and predefined. They rely on evacuation plans present only at a limited number of building locations and possibly a trained evacuation personnel to resolve unexpected contingencies. Smart buildings today are equipped with sensory infrastructure that can be used for an autonomous situation-aware evacuation guidance optimized in real time. A system providing such a guidance can help in avoiding additional evacuation casualties due to the flaws of the conventional evacuation approaches. Such a system should be robust and scalable to dynamically adapt to the number of evacuees and the size and safety conditions of a building. In this respect, we propose a distributed route recommender architecture for situation-aware evacuation guidance in smart buildings and describe its key modules in detail. We give an example of its functioning dynamics on a use case.

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