Christopher D Heiser

20200097841, Mar 26, 2020

Sep 23, 2019

16/578810

- Campbell CA, US
Anand Ramesh - Campbell CA, US
Christopher Heiser - Campbell CA, US

G06N 5/04
G06N 20/00
G07C 5/00
H03M 7/30

Systems and methods include accessing streams of sensor data; constructing a corpus of seed sample data; initializing a first instance of a trained model using the corpus of seed sample data that: generates predictions of predicted sensor values; computing error values based on calculated differences between the actual sensor values and the predicted sensor values; transmitting the computed error values; initializing a second instance of the trained model based on an input of the corpus of the seed sample data, wherein the second instance of the trained model is identical to the first instance of the trained model, and wherein the second instance: generates inferences of predicted sensor values for each of the sensors based on the input of the corpus of seed sample data; reconstructing estimates of the actual sensor values based on a reconstruction computation with the parallel predicted sensor values and the error values.

20190174511, Jun 6, 2019

Dec 3, 2018

16/208411

- Campbell CA, US
Ioannis Petousis - Campbell CA, US
Owen Davis - Campbell CA, US
Christopher Heiser - Campbell CA, US

H04W 72/12
H04W 4/40
G06Q 10/02
G06Q 50/30
G08G 1/00

A system and method that enables autonomous mobility implementations to prioritize, offload, and process data in an efficient manner includes generating a prioritization model, training the prioritization model on a data corpus to generate a prioritization schedule, deploying the prioritization schedule to one or more autonomous vehicles, offloading data at a local content absorption node, processing data at the local content absorption node, and optionally transmitting data results from the processed data.

20190174514, Jun 6, 2019

Dec 3, 2018

16/208418

- Campbell CA, US
Ioannis Petousis - Campbell CA, US
Owen Davis - Campbell CA, US
Christopher Heiser - Campbell CA, US

H04W 72/12
H04W 4/40
G06Q 10/02
G06Q 50/30
G08G 1/00
H04W 4/021
H04W 4/02
G05D 1/00
G05D 1/02

A system and method that enables resource analysis within an intelligent content absorption network with autonomous mobility implementations includes generating a prioritization model, training the prioritization model on a data corpus to generate a prioritization schedule, deploying the prioritization schedule to one or more autonomous vehicles, offloading data at a local content absorption node, processing data at the local content absorption node, and optionally transmitting data results from the processed data.

20180261020, Sep 13, 2018

Mar 9, 2018

15/916546

- Campbell CA, US
Christopher Heiser - Campbell CA, US
Owen Davis - Campbell CA, US

G07C 5/00
H04W 4/44
G07C 5/08

A system and method that includes collecting vehicle sensor data, wherein prioritizing vehicle sensor data includes identifying a level of importance for each of a plurality of vehicle sensor data types included in the vehicle sensor data; generating a vehicle sensor data schedule, wherein generating the vehicle data schedule includes one or more of (i) identifying a transmission order for each of the plurality of vehicle sensor data types and (ii) identifying a storage scheme selected from a hierarchy of data storage types for each of the plurality of vehicle sensor data types; transforming vehicle sensor data into message data, wherein the transforming includes selectively converting one or more of the vehicle sensor data types of the vehicle sensor data to a messaging format based on the prioritization; and transmitting, via one or more selected communication networks, the message data according to the vehicle sensor data schedule.