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 sensor management and utilization, comprising:
at least one computer processor including a memory;
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 fusion engine is operable to fuse the first parameter and the second parameter in real time, thereby creating fused data, the at least one inference engine is operable to determine at least one inference from the first parameter and the second parameter in real time, and the at least one validation engine is operable to validate the first parameter and the second parameter in real time;
wherein the at least one inference engine determines the at least one inference by using artificial intelligence;
wherein the at least one validation engine is operable to create a statistical comparison between the at least one inference and at least one new inference and determine if the statistical comparison exceeds a predefined threshold to automatically validate the at least one inference in real time;
wherein the statistical comparison includes calculating a conditional entropy of data from the first parameter and the second parameter;
wherein the at least one computer processor is operable to instruct modification of the machine based on the automatically validated at least one inference; 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 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.
3 . The system of claim 1 , wherein the fused data includes at least one new data set, and wherein the at least one new data set includes an accuracy value for the at least one first sensor and/or the at least one second sensor.
4 . The system of claim 1 , wherein the at least one inference engine is operable to determine which of the at least one first sensor or the at least one second sensor the at least one computer processor responds to based in part on the at least one inference.
5 . The system of claim 1 , wherein the at least one inference includes a numerical value.
6 . The system of claim 1 , wherein the at least one inference includes a prediction of a future event based in part on the fused data.
7 . A method for sensor data fusion for sensor management and utilization, comprising:
providing at least one computer processor including a memory;
providing 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;
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;
fusing the first parameter and the second parameter via the at least one fusion engine in real time, thereby creating fused data, determining at least one inference from the first parameter and the second parameter via the at least one inference engine in real time, and validating the first parameter and the second parameter via the at least one validation engine in real time;
determining via the at least one inference engine the at least one inference by using artificial intelligence;
comparing via the at least one validation engine the at least one inference and at least one new inference via a statistical comparison, thereby creating a validated at least one inference;
wherein the new inference is generated in a sensor environment different from a sensor environment of the at least one inference;
wherein the statistical comparison includes calculating a conditional entropy of data from the first parameter and the second parameter;
instructing via the at least one computer processor modification of the machine based on the validated at least one inference; 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 , wherein the at least one inference includes a numerical value.
10 . The method of claim 7 , further comprising predicting via the at least one inference engine a future event based in part on the fused data.
11 . The method of claim 7 , further comprising filtering and/or indexing the first parameter and the second parameter by at least one parameter property.
12 . The method of claim 7 , further comprising determining via the at least one inference engine which of the at least one first sensor or the at least one second sensor the at least one computer processor responds to based in part on the at least one inference.
13 . The method of claim 7 , wherein the fused data includes at least one new data set, and 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.
14 . A system for sensor data fusion for sensor management and utilization, comprising:
at least one computer processor including a memory;
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 fusion engine is operable to fuse the first parameter and the second parameter in real time, thereby creating fused data, the at least one inference engine is operable to determine at least one inference from the first parameter and the second parameter in real time, and the at least one validation engine is operable to validate the first parameter and the second parameter in real time;
wherein the at least one inference engine determines the at least one inference by using artificial intelligence;
wherein the at least one validation engine is operable to create a statistical comparison between the at least one inference and at least one new inference, thereby creating a validated at least one inference;
wherein the at least one new inference is generated in a sensor environment different from a sensor environment of the at least one inference;
wherein the statistical comparison includes calculating a conditional entropy of data from the first parameter and the second parameter;
wherein the at least one computer processor is operable to instruct modification of the machine based on the validated at least one inference; and
wherein the modification of the machine includes adjusting an orientation of a satellite.
15 . The system of claim 14 , 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.
16 . The system of claim 14 , wherein the at least one inference engine is operable to determine which of the at least one first sensor or the at least one second sensor the at least one computer processor responds to based in part on the at least one inference.
17 . The system of claim 14 , wherein the at least one inference includes a numerical value.
18 . The system of claim 14 , wherein the at least one computer processor is operable to receive at least one query, wherein the at least one query is user and/or computer generated.
19 . The system of claim 14 , wherein the at least one inference includes a prediction of a future event based in part on the fused data.
20 . The system of claim 14 , wherein the fused data includes at least one new data set, and wherein the at least one new data set includes an accuracy value for the at least one first sensor and/or the at least one second sensor.