Semantic sensing system

Patent metadata

Field	Value
Publication number	US-12028928-B2
Application number	US-202318394767-A
Country	US
Kind code	B2
Filing date	Dec 22, 2023
Priority date	Jan 3, 2019
Publication date	Jul 2, 2024
Grant date	Jul 2, 2024

Abstract

A semantic sensing system includes a processor, a memory, a plurality of wireless communication enabled devices and at least one sensing element, the memory storing a plurality of mapped endpoints wherein the processor is configured to apply semantic drift or entropy to determine affirmative and non-affirmative circumstances based on inputs from the at least one sensing element to cause the system to perform semantic augmentation towards a first endpoint supervisor in relation with the affirmative and non-affirmative determinations.

First claim

I claim:

1. 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 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 first inferred semantic comprises a second activity and the determination that the first 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.

2. The semantic sensing system of claim 1 , wherein at least one among the at least one affirmative semantic and the at least one non-affirmative semantic is configured by the first endpoint supervisor.

3. The semantic sensing system of claim 1 , wherein at least one among the at least one affirmative semantic and the at least one non-affirmative semantic is associated with a semantic time.

4. The semantic sensing system of claim 1 , 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.

5. The semantic sensing system of claim 1 , 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 non-affirmative semantic or the at least one affirmative semantic in rapport with subsequent inferred semantics based on the inputs from the at least one sensor.

6. The semantic sensing system of claim 5 , wherein the system determines that the entropy between the at least one affirmative semantic and subsequent inferred semantics based on the inputs from the at least one sensor is within a likeable interval.

7. The semantic sensing system of claim 6 , wherein the likeable interval is associated with a semantic time.

8. The semantic sensing system of claim 6 , wherein the likeable interval is associated with an affirmative semantic.

9. The semantic sensing system of claim 1 , wherein at least one among the at least one affirmative semantic and the at least one non-affirmative semantic is determined based on web content parsing.

10. The semantic sensing system of claim 1 , wherein at least one among the at least one affirmative semantic and the at least one non-affirmative semantic is determined based on an operating manual parsing.

11. The semantic sensing system of claim 1 , wherein at least one among the at least one affirmative semantic and the at least one non-affirmative semantic is indicative of a first-third activity.

12. The semantic sensing system of claim 11 , wherein the at least one among the at least one affirmative semantic and the at least one non-affirmative semantic comprises an activity semantic.

13. The semantic sensing system of claim 11 , wherein the second inferred semantic comprises a fourth activity and a determination that the second inferred semantic is highly entropic with the at least one non-affirmative semantic is based on a high entropy between the third activity and the fourth activity.

14. The semantic sensing system of claim 1 , wherein the at least one among the at least one affirmative semantic and the at least one non-affirmative semantic is indicative of an intrinsic orientation.

15. 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.

16. A semantic sensing system of claim 15 , wherein:
the memory further storing the at least one affirmative semantic in association with an object of the first object type;
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 the third time.

17. The semantic sensing system of claim 16 , wherein the system generates semantic augmentation based on a determination that the second inferred semantic is non-affirmative by having a high entropy with respect to the at least one affirmative semantic.

18. 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 w

Assignees

• Lucomm Tech Inc

Inventors

• Cristache Lucian

Classifications

• G05D1/2467

  using a semantic description of the environment · CPC title

• G05D1/696

  involving a plurality of vehicles coupled together · CPC title

• G05D1/6987

  by centralised control off-board any of the vehicles · CPC title

• G05D2101/10

  using artificial intelligence [AI] techniques · CPC title

• G05D1/69

  Coordinated control of the position or course of two or more vehicles · CPC title