Semantic sensing system

A semantic sensing system, comprising:

• a memory storing a plurality of endpoints associated with physical locations;
• the memory further storing a first identity of an assigned first supervisor of a first endpoint among the plurality of endpoints;
• at least one sensor;
• the memory further storing at least one affirmative semantic and at least one non-affirmative semantic associated with an object type,
• wherein at least one among the at least one affirmative semantic and the at least one non-affirmative semantic is indicative of a first activity;
• at least one processor and a computer program operable by the at least one processor to cause the at least one processor to detect a first object of a first object type at the first endpoint from among the plurality of endpoints based on one or more inputs from the at least one sensor;
• the computer program further being configured to cause the at least one processor to infer a first semantic and a second semantic at the first endpoint based on the one or more inputs from the at least one sensor;
• wherein the system generates semantic augmentation based on a determination that the first inferred semantic is affirmative by semantically matching the first inferred semantic with the at least one affirmative semantic at a first time and further based on a determination that the second inferred semantic is non-affirmative by semantically matching the second inferred semantic with the at least one non-affirmative semantic at a second time, wherein the semantic augmentation is directed to the assigned first supervisor based on the first identity;
• and
• wherein the second inferred semantic comprises a second activity and a determination that the second inferred semantic is highly entropic with the at least one affirmative semantic is based on a high entropy between the first activity and the second activity.

A semantic sensing system, comprising:

• a memory storing a plurality of endpoints associated with physical locations;
• the memory further storing a first identity of an assigned first supervisor of a first endpoint among the plurality of endpoints;
• at least one sensor;
• a wireless device comprising at least one wireless transceiver, the wireless device being comprised by a first object;
• the memory further storing a plurality of interests associated with the first object published via the wireless transceiver by a semantic flux associated with the wireless device;
• the memory further storing a plurality of capabilities associated with at least one sensor at a first endpoint;
• and
• at least one processor and a computer program operable by the at least one processor to cause the at least one processor to match the plurality of interests with the plurality of capabilities at the first endpoint based on semantic matching;
• wherein the system generates semantic augmentation based on a determination that the plurality of interests and capabilities are affirmatively matching at the first endpoint at a first time and that the plurality of interests and capabilities are non-affirmatively matching at the first endpoint at a second time and further, wherein the system generates semantic augmentation based on the determination that the plurality of interests are affirmatively matching the capabilities at the first endpoint at a third time, wherein the semantic augmentation is directed to the assigned first supervisor based on the first identity.

A semantic sensing system, comprising:

• a memory storing a plurality of endpoints associated with physical locations;
• the memory further storing a first identity of an assigned first supervisor of a first endpoint among the plurality of endpoints;
• at least one sensor;
• the memory further storing at least one affirmative semantic and at least one non-affirmative semantic associated with an object type;
• at least one processor and a computer program operable by the at least one processor to cause the at least one processor to detect a first object of a first object type at the first endpoint from among the plurality of endpoints based on one or more inputs from the at least one sensor;
• the computer program further being configured to cause the at least one processor to infer a first semantic and a second semantic at the first endpoint based on the one or more inputs from the at least one sensor;
• wherein the system generates semantic augmentation based on a determination that the first inferred semantic is non-affirmative by having a high entropy with respect to the at least one affirmative semantic at a first time and further based on a determination that the second inferred semantic is affirmative by semantically matching the second inferred semantic with the at least one affirmative semantic at a second time, wherein the semantic augmentation is directed to the assigned first supervisor based on the first identity;
• and
• wherein the system infers a counter-measure and applies the counter-measure to reduce the high entropy between the at least one among the at least one affirmative semantic or the at least one non-affirmative semantic in rapport with subsequent inferred semantics based on the inputs from the at least one sensor.

A semantic sensing system, comprising:

• a memory storing a plurality of endpoints associated with physical locations;
• the memory further storing a first identity of an assigned first supervisor of a first endpoint among the plurality of endpoints;
• at least one sensor;
• the memory further storing at least one affirmative semantic and at least one non-affirmative semantic associated with an object type;
• at least one processor and a computer program operable by the at least one processor to cause the at least one processor to detect a first object of a first object type at the first endpoint from among the plurality of endpoints based on one or more inputs from the at least one sensor;
• the computer program further being configured to cause the at least one processor to infer a first semantic and a second semantic at the first endpoint based on the one or more inputs from the at least one sensor;
• wherein the system generates semantic augmentation based on a determination that the first inferred semantic is affirmative by semantically matching the first inferred semantic with the at least one affirmative semantic at a first time and further based on a determination that the second inferred semantic is non-affirmative by semantically matching the second inferred semantic with the at least one non-affirmative semantic at a second time, wherein the semantic augmentation is directed to the assigned first supervisor based on the first identity;
• and,
• wherein the system infers a counter-measure and applies the counter-measure to reduce the high entropy between the at least one among the at least one affirmative semantic or the at least one non-affirmative semantic in rapport with subsequent inferred semantics based on the inputs from the at least one sensor.

A semantic sensing system, comprising:

• a memory storing a plurality of endpoints associated with physical locations;
• the memory further storing a first identity of an assigned first supervisor of a first endpoint among the plurality of endpoints;
• at least one sensor;
• a wireless device comprising at least one wireless transceiver, the wireless device being comprised by a first object;
• the memory further storing a plurality of interests associated with the first object published via the wireless transceiver by a semantic flux associated with the wireless device;
• the memory further storing a plurality of capabilities associated with at least one sensor at a first endpoint,
• wherein the capabilities at the first endpoint are published in association with at least two semantic fluxes,
• wherein each semantic flux among the at least two semantic fluxes is associated with a semantic group of sensors;
• and
• at least one processor and a computer program operable by the at least one processor to cause the at least one processor to match the plurality of interests with the plurality of capabilities at the first endpoint based on semantic matching;
• wherein the system generates semantic augmentation based on a determination that the plurality of interests and capabilities are affirmatively matching at the first endpoint at a first time and that the plurality of interests and capabilities are non-affirmatively matching at the first endpoint at a second time, wherein the semantic augmentation is directed to the assigned first supervisor based on the first identity.

A semantic sensing system, comprising:

• a memory storing a plurality of endpoints associated with physical locations;
• the memory further storing a first identity of an assigned first supervisor of a first endpoint among the plurality of endpoints;
• at least one sensor;
• the memory further storing at least one affirmative semantic and at least one non-affirmative semantic associated with an object type;
• at least one processor and a computer program operable by the at least one processor to cause the at least one processor to detect a first object of a first object type at the first endpoint from among the plurality of endpoints based on one or more inputs from the at least one sensor;
• the computer program further being configured to cause the at least one processor to infer a first semantic and a second semantic at the first endpoint based on the one or more inputs from the at least one sensor;
• wherein the system generates semantic augmentation based on a determination that the first inferred semantic is non-affirmative by having a high entropy with respect to the at least one affirmative semantic at a first time and further based on a determination that the second inferred semantic is affirmative by semantically matching the second inferred semantic with the at least one affirmative semantic at a second time, wherein the semantic augmentation is directed to the assigned first supervisor based on the first identity;
• and
• wherein the system infers an affirmative measure and applies the affirmative measure to cause an affirmative entropy between the at least one among the at least one affirmative semantic or the at least non-affirmative semantic in rapport with subsequent inferred semantics based on the inputs from the at least one sensor.

A semantic sensing system, comprising:

• a memory storing a plurality of endpoints associated with physical locations;
• the memory further storing a first identity of an assigned first supervisor of a first endpoint among the plurality of endpoints;
• at least one sensor;
• the memory further storing at least one affirmative semantic and at least one non-affirmative semantic associated with an object type;
• at least one processor and a computer program operable by the at least one processor to cause the at least one processor to detect a first object of a first object type at the first endpoint from among the plurality of endpoints based on one or more inputs from the at least one sensor;
• the computer program further being configured to cause the at least one processor to infer a first semantic and a second semantic at the first endpoint based on the one or more inputs from the at least one sensor;
• wherein the system generates semantic augmentation based on a determination that the first inferred semantic is affirmative by semantically matching the first inferred semantic with the at least one affirmative semantic at a first time and further based on a determination that the second inferred semantic is non-affirmative by semantically matching the second inferred semantic with the at least one non-affirmative semantic at a second time, wherein the semantic augmentation is directed to the assigned first supervisor based on the first identity;
• and
• wherein the system infers an affirmative measure and applies the affirmative measure to cause an affirmative entropy between the at least one among the at least one affirmative semantic or the at least non-affirmative semantic in rapport with subsequent inferred semantics based on the inputs from the at least one sensor.

A semantic sensing system, comprising:

• a memory storing a plurality of endpoints associated with physical locations;
• the memory further storing a first identity of an assigned first supervisor of a first endpoint among the plurality of endpoints;
• at least one sensor;
• the memory further storing at least one affirmative semantic and at least one non-affirmative semantic associated with an object type;
• at least one processor and a computer program operable by the at least one processor to cause the at least one processor to detect a first object of a first object type at the first endpoint from among the plurality of endpoints based on one or more inputs from the at least one sensor;
• the computer program further being configured to cause the at least one processor to infer a first semantic and a second semantic at the first endpoint based on the one or more inputs from the at least one sensor;
• and
• wherein the system generates semantic augmentation based on a determination that the first inferred semantic is non-affirmative by having a high entropy with respect to the at least one affirmative semantic at a first time and further based on a determination that the second inferred semantic is affirmative by semantically matching the second inferred semantic with the at least one affirmative semantic at a second time and further, wherein the system generates semantic augmentation based on a determination that a third inferred semantic is non-affirmative by semantically matching the third inferred semantic with the at least one non-affirmative semantic at a third time, wherein the semantic augmentation is directed to the assigned first supervisor based on the first identity.

A semantic sensing system, comprising:

• a memory storing a plurality of endpoints associated with physical locations;
• the memory further storing a first identity of an assigned first supervisor of a first endpoint among the plurality of endpoints;
• at least one sensor;
• the memory further storing at least one affirmative semantic and at least one non-affirmative semantic associated with an object type;
• the memory further storing the at least one affirmative semantic in association with an object of an object type;
• at least one processor and a computer program operable by the at least one processor to cause the at least one processor to detect a first object of a first object type at the first endpoint from among the plurality of endpoints based on one or more inputs from the at least one sensor;
• the computer program further being configured to cause the at least one processor to infer a first semantic and a second semantic at the first endpoint based on the one or more inputs from the at least one sensor;
• and
• wherein the system generates semantic augmentation based on a determination that the first inferred semantic is affirmative by semantically matching the first inferred semantic with the at least one affirmative semantic at a first time and further based on a determination that the second inferred semantic is non-affirmative by semantically matching the second inferred semantic with the at least one non-affirmative semantic at a second time and further, wherein the system generates semantic augmentation based on a determination that a third inferred semantic is affirmative by semantically matching the third inferred semantic with the at least one affirmative semantic at a third time, wherein the semantic augmentation is directed to the assigned first supervisor based on the first identity.