Systems and methods of sensor data fusion
Systems and methods of sensor data fusion including sensor data capture, curation, linking, fusion, inference, and validation. The systems and methods described herein reduce computational demand and processing time by curating data and calculating conditional entropy. The system is operable to fuse data from a plurality of sensor types. A computer processor optionally stores fused sensor data that the system validates above a mathematical threshold.
1 . A system for sensor data fusion for satellite management and utilization, comprising:
at least one computer processor including a memory;
at least one curation engine, at least one link engine, at least one fusion engine, at least one inference engine, and at least one validation engine;
at least one first sensor, being of a first sensor type, operable to measure a first parameter of a machine; and
at least one second sensor, being of a second sensor type, operable to measure a second parameter of the machine;
wherein the at least one computer processor is operable to analyze the first parameter and the second parameter;
wherein the at least one curation engine is operable to curate the first parameter and the second parameter, creating a curated first parameter and a curated second parameter, the at least one link engine is operable to link the curated first parameter and the curated second parameter, the at least one inference engine is operable to determine an inference from the curated first parameter and the curated second parameter, and the at least one validation engine is operable to validate the curated first parameter and the curated second parameter;
wherein the at least one link engine is operable to calculate a conditional entropy between the curated first parameter and the curated second parameter;
wherein the at least one link engine is operable to determine if the link between the curated first parameter and the curated second parameter is a non-existent link, a weak link, or a strong link via the conditional entropy;
wherein the at least one inference engine is operable to determine internal sensor damage for the at least one first sensor and/or the at least one second sensor based on the conditional entropy;
wherein the at least one fusion engine is operable to fuse the curated first parameter and the curated second parameter;
wherein the at least one fusion engine creates at least one new data set;
wherein the at least one computer processor does not store the curated first parameter and/or the curated second parameter until the at least one validation engine has validated the curated first parameter and the curated second parameter;
wherein the at least one computer processor is operable to instruct modification of the machine based on the at least one new data set and at least one query; and
wherein the modification of the machine includes adjusting an orientation of a satellite.
2 . The system of claim 1 , wherein the at least one curation engine is operable to use artificial intelligence to determine at least one property and/or sub-property of the first parameter and the second parameter for the at least one link engine to calculate the conditional entropy.
3 . The system of claim 1 , wherein the at least one first sensor and/or the at least one second sensor includes an accelerometer, a gyroscope, a force/torque sensor, a proximity sensor, a gear sensor, a magnetic sensor, a humidity sensor, an angle sensor, a temperature sensor, a 6-axis combo inertial sensor, a current sensor, a Light Detection and Ranging (LiDAR) sensor, radar sensor, ultrasonic sensor, visible spectrum camera, Global Positioning System (GPS) sensor, inertial measurement unit, infrared sensor, depth camera, load sensor, a thermal power sensor, a diode detector, and/or a spectrometer.
4 . The system of claim 1 , wherein the at least one new data set includes an accuracy value for the at least one first sensor and the at least one second sensor.
5 . The system of claim 1 , wherein the at least one link engine is operable to iteratively calculate the conditional entropy of weakly linked data until the at least one link engine calculates the non-existent link or the strong link.
6 . The system of claim 1 , wherein the at least one link engine is operable to link sensor data in real-time.
7 . A method for sensor data fusion for satellite management and utilization, comprising:
providing at least one computer processor including a memory;
providing at least one curation engine, at least one link engine, at least one fusion engine, at least one inference engine, and at least one validation engine;
at least one first sensor, being of a first sensor type, measuring a first parameter of a machine; and
at least one second sensor, being of a second sensor type, measuring a second parameter of the machine;
analyzing by the at least one computer processor the first parameter and the second parameter;
curating the first parameter and the second parameter via the at least one curation engine, creating a curated first parameter and a curated second parameter, linking the curated first parameter and the curated second parameter via the at least one link engine, determining an inference from the curated first parameter and the curated second parameter via the at least one inference engine, and validating the curated first parameter and the curated second parameter via the at least one validation engine;
calculating a conditional entropy via the at least one link engine between the curated first parameter and the curated second parameter;
determining if the link between the curated first parameter and the curated second parameter is a non-existent link, a weak link, or a strong link via the conditional entropy;
determining by the at least one inference engine internal sensor damage for the at least one first sensor and/or the at least one second sensor based on the conditional entropy;
fusing the curated first parameter and the curated second parameter;
creating via the at least one fusion engine at least one new data set;
wherein the at least one computer processor does not store the curated first parameter and/or the curated second parameter until the at least one validation engine has validated the curated first parameter and the curated second parameter;
instructing modification of the machine by the at least one computer processor based in part on the at least one new data set and at least one query; and
wherein the modification of the machine includes adjusting an orientation of a satellite.
8 . The method of claim 7 , wherein the at least one first sensor and/or the at least one second sensor includes an accelerometer, a gyroscope, a force/torque sensor, a proximity sensor, a gear sensor, a magnetic sensor, a humidity sensor, an angle sensor, a temperature sensor, a 6-axis combo inertial sensor, a current sensor, a Light Detection and Ranging (LiDAR) sensor, radar sensor, ultrasonic sensor, visible spectrum camera, Global Positioning System (GPS) sensor, inertial measurement unit, infrared sensor, depth camera, load sensor, a thermal power sensor, a diode detector, and/or a spectrometer.
9 . The method of claim 7 , further comprising categorizing via the at least one curation engine at least one property and/or sub-property of the first parameter and the second parameter for the at least one link engine to calculate the conditional entropy based in part on historical accuracy of previous categorizations using artificial intelligence.
10 . The method of claim 7 , wherein the at least one new data set includes an accuracy value for the at least one first sensor and the at least one second sensor.
11 . The method of claim 7 , further comprising iterating calculations so that the at least one link engine continuously calculates the conditional entropy of the weakly linked data until the at least one link engine calculates the non-existent link or the strong link.
12 . The method of claim 7 , further comprising dynamically adjusting via the at least one link engine the threshold for the non-existent link, the weak link, or the strong link.
13 . A system for sensor data fusion for satellite management and utilization, comprising:
at least one computer processor including a memory;
at least one curation engine, at least one link engine, at least one fusion engine, at least one inference engine, and at least one validation engine;
at least one first sensor of a first sensor type, operable to measure a first parameter of a machine; and
at least one second sensor of a second sensor type, operable to measure a second parameter of the machine;
wherein the at least one computer processor is operable to analyze data relating to the first parameter and the second parameter;
wherein the at least one curation engine is operable to curate the first parameter and the second parameter, creating a curated first parameter and a curated second parameter, the at least one link engine is operable to link the curated first parameter and the curated second parameter, the at least one inference engine is operable to determine at least one inference from the curated first parameter and the curated second parameter, and the at least one validation engine is operable to validate the curated first parameter and the curated second parameter;
wherein the at least one link engine is operable to calculate a conditional entropy between the curated first parameter and the curated second parameter based in part on at least one common property and/or common sub-property of the first parameter and the second parameter;
wherein the at least one link engine is operable to determine if the link between the curated first parameter and the curated second parameter is a non-existent link, a weak link, or a strong link via the conditional entropy;
wherein the at least one inference engine is operable to determine internal sensor damage for the at least one first sensor and/or the at least one second sensor based on the conditional entropy;
wherein the at least one fusion engine is operable to fuse the curated first parameter and the curated second parameter;
wherein the at least one computer processor does not store the curated first parameter and/or the curated second parameter until the at least one validation engine has validated the curated first parameter and the curated second parameter;
wherein the at least one fusion engine is operable to generate at least one new data set;
wherein the at least one computer processor is operable to instruct modification of the machine based on the at least one new data set and at least one query; and
wherein the modification of the machine includes adjusting an orientation of a satellite.
14 . The system of claim 13 , wherein the at least one first sensor and the at least one second sensors include an accelerometer, a gyroscope, a force/torque sensor, a proximity sensor, a gear sensor, a magnetic sensor, a humidity sensor, an angle sensor, a temperature sensor, a 6-axis combo inertial sensor, a current sensor, a Light Detection and Ranging (LiDAR) sensor, radar sensor, ultrasonic sensor, visible spectrum camera, Global Positioning System (GPS) sensor, inertial measurement unit, infrared sensor, depth camera, load sensor, a thermal power sensor, a diode detector, and/or a spectrometer.
15 . The system of claim 13 , wherein the at least one curation engine is operable to use artificial intelligence to categorize the at least one common property and/or common sub-property of the first parameter and the second parameter for the at least one link engine to calculate the conditional entropy based in part on historical accuracy of previous categorizations by the at least one curation engine.
16 . The system of claim 13 , wherein the at least one link engine is operable to link sensor data in real-time.
17 . The system of claim 13 , wherein the at least one new data set includes an accuracy value for the at least one first sensor and the at least one second sensor.
18 . The system of claim 13 , wherein the at least one link engine is operable to dynamically adjust the threshold for the non-existent link, the weak link, or the strong link.