IP Library Granted Patent US 10,551,226
Granted Patent B2
US 10,551,226 · App. 14/946,121 · Granted Feb 4, 2020

System and method for scalable cloud-based sensor calibration

Inventors: Yong Luo (St. Petersburg, FL); Gustavo Armando Suarez (St. Petersburg, FL)
Assignee: JABIL INC.
G01D18/00H04L67/10H04L67/12
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Quick Facts
Patent No.
US 10,551,226
App. No.
14/946,121
Granted
Feb 4, 2020
Kind
B2
Abstract

A scalable sensor calibration system and method configured to calibrate and/or recalibrate sensors based on calibration parameters received from secure cloud storage. A plurality of calibration parameter sets for a plurality of sensors may be received from the secure cloud storage and successively transmitted to each of the plurality of sensors using a calibration system bus interface. Calibration output data generated by the sensors using the calibration parameters is received and used to create new, optimized calibration parameters sets.

Claims (22)

1. A computer system for calibrating both in-field and in-manufacture sensors, comprising:

a processor;

a communication interface operatively coupled to the processor, the communication interface having a plurality of calibrations modules each configured to receive a calibration parameter set from a remote cloud-based application via a computer network, wherein the remote cloud-based application assesses at least a use application and environmental factors prior to providing each of the calibration parameter sets;

a plurality of calibration system buses operatively coupled to the processor, wherein each of the calibration system buses transmits the received calibration parameter set for a particular one of the plurality of calibration modules to the respective ones of the sensors,

wherein each of the calibration system buses receives calibration output data from the in-field ones of the respective sensors in response to the calibration parameter being set using the transmitted parameter set, and

wherein the communications interface transmits the calibration output data to the remote cloud-based application over the computer network, thereby generating a new calibration parameter set received by the communication interface from the remote cloud-based application.

2. The computer system of claim 1 , wherein the calibration output data from the sensors comprises analog front end gain data and offset value data.

3. The computer system of claim 2 , wherein the calibration data output data comprises calibration coefficient value data.

4. The computer system of claim 3 , wherein the calibration coefficient value data comprises at least one of analog programmable gain coefficients settings, analog filter coefficients settings, digital filter coefficients settings, digital signal processor (DSP) algorithmic implementation coefficients settings, sensor manufacturing process correlated coefficients settings, sensor end user events correlated coefficients settings, sensor device temperature dependent analytic coefficients settings, sensor device voltage dependent analytic coefficients settings, sensor device process dependent analytic coefficients settings, sensor fusion implementation correlated coefficients settings, sensor module manufacturing process phase correlated coefficients settings, and sensor module manufacturing end user events correlated coefficients settings.

5. The computer system of claim 1 , wherein the calibration output data comprises sensor operation based on at least one of a minimum and maximum sensing value based on the calibration parameter set.

6. The computer system of claim 1 , wherein the calibration output data comprises sensor operation based on a plurality of predetermined sensing values, based on the calibration parameter set.

7. A method for calibrating both in-field and in-manufacture sensors, comprising:

receiving a calibration parameter set for one type of the in-manufacture sensors from a remote cloud-based application over a computer network, wherein the calibration parameter set is dependent upon at least a use application and environmental factors prior to providing the calibration parameter set;

providing the received calibration parameter set to each of the in-field sensors using one of a plurality of dedicated calibration system buses, each of which is dedicated to the one type of the in-manufacture sensors;

generating calibration output data from the in-field sensors in response to the calibration parameter set;

transmitting the calibration output data to the computer network for receipt over the dedicated bus; and

receiving a new calibration parameter set for the in-manufacture sensors in response to the calibration output data.

8. The method of claim 7 , wherein the calibration output data from the sensors comprises analog front end gain data and offset value data.

9. The method of claim 8 , wherein the calibration data output data comprises calibration coefficient value data.

10. The method of claim 9 , wherein the calibration coefficient value data comprises at least one of analog programmable gain coefficients settings, analog filter coefficients settings, digital filter coefficients settings, digital signal processor (DSP) algorithmic implementation coefficients settings, sensor manufacturing process correlated coefficients settings, sensor end user events correlated coefficients settings, sensor device temperature dependent analytic coefficients settings, sensor device voltage dependent analytic coefficients settings, sensor device process dependent analytic coefficients settings, sensor fusion implementation correlated coefficients settings, sensor module manufacturing process phase correlated coefficients settings, and sensor module manufacturing end user events correlated coefficients settings.

11. The method of claim 7 , wherein the calibration output data comprises sensor operation based on at least one of a minimum and maximum sensing value based on the calibration parameter set.

12. The method of claim 7 , wherein the calibration output data comprises sensor operation based on a plurality of predetermined sensing values, based on the calibration parameter set.

Assignments (2)
CHANGE OF NAME Recorded Apr 18, 2018
From: JABIL CIRCUIT, INC.
To: JABIL INC.
Reel/Frame 045969/0910 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 26, 2016
From: SUAREZ, GUSTAVO ARMANDO; LUO, YONG
To: JABIL CIRCUIT, INC.
Reel/Frame 037587/0307 →
Continuity (1)
Related Publication 20170146375A1 · May 25, 2017
Cited By (2)
US 12,348,916 US 12,618,697