Systems and methods for probabilistic semantic sensing in a sensory network

A system comprising:

• one or more memories;
• and
• one or more processors, communicatively coupled to the one or more memories, to:
• receive raw sensor data from a plurality of sensors;
• generate semantic data based on the raw sensor data,
• the semantic data including a plurality of sensed event records,
• each sensed event record including one or more of:
• a first classifier that indicates an event detected by a corresponding sensor, of the plurality of sensors,
• a second classifier that indicates a probability that the first classifier is true,
• a third classifier that indicates a sensor location of the corresponding sensor, of the plurality of sensors, or
• a fourth classifier that indicates an event location at which the detected event occurred;
• generate a derived event record based on a group of sensed event records, of groups of sensed event records,
• the generated derived event record including:
• a fifth classifier that indicates an event detected by multiple sensors, of the plurality of sensors, and
• a sixth classifier that indicates a probability that the fifth classifier is true;
• and
• enable at least one application to perform a service based on the generated derived event record.

A non-transitory computer-readable medium storing instructions, the instructions comprising:

• one or more instructions, when executed by one or more processors, cause the one or more processors to:
• generate semantic data based on raw sensor data,
• the semantic data including a plurality of sensed event records that each indicate a corresponding event sensed by a corresponding sensor, of a plurality of sensors,
• each sensed event record including:
• a first classifier that indicates an event detected by the corresponding sensor, of the plurality of sensors,
• a second classifier that indicates a probability that the first classifier is true,
• a third classifier that indicates a sensor location of the corresponding sensor, of the plurality of sensors, and
• a fourth classifier that indicates an event location at which the detected event occurred;
• generate a derived event record based on a group of sensed event records, of groups of sensed event records,
• the generated derived event record including:
• a fifth classifier that indicates an event detected by multiple sensors, of the plurality of sensors, and
• a sixth classifier that indicates a probability that the fifth classifier is true;
• and
• enable at least one application to perform a service based on the generated derived event record.