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A situation is an abstraction for a pattern of observations made by a distributed system such as a sensor network. Situations have previously been studied in different domains, as composite events in distributed event based systems, service composition in multi-agent systems, and macro-programming in sensor networks. However, existing languages do not address the specific challenges posed by sensor networks. This article presents a novel language for representing situations in sensor networks that addresses these challenges. Three algorithms for recognizing situations in relevant fields are reviewed and adapted to sensor networks. In particular, distributed commitment machines are introduced and demonstrated to be the most suitable algorithm among the three for recognizing situations in sensor networks.