Semiorder database for complex activity recognition in multi-sensory environments

A prototype semiorder database used for activity recognition in multi-sensory monitoring environments is described. Activities are spatio-temporal compositions of events, which are a type of atomic semantic units for such compositions. The focus is on the temporal composition of activities from events in the presence of bounded duration of temporal uncertainty in an event occurrence. Such temporal uncertainty forces the concurrency between event occurrences to be intransitive. Under certain assumptions, a subclass of partial orders, known as semiorders, models such intransitive concurrency appropriately. The semiorder database stores events and their semiorder temporal order of occurrences. A semiorder data model and the corresponding query language that embeds a semiorder pattern language are the main constituents of the semiorder database. We demonstrate this database and queries for activity recognition in a real time environment. The demonstration also includes a transducer subsystem for detection of events.