Daniel Henry Mitchell

US Patent:

20220349622, Nov 3, 2022

Filed:

Apr 29, 2022

Appl. No.:

17/733756

Inventors:

- Milwaukee WI, US
Yonggon Lee - Brookfield WI, US
Brian Thomas Branecky - Oconomowoc WI, US
Barry Anthony Collins - Lebanon TN, US
Daniel Mitchell - Gallatin TN, US
Mohamed Mehdi Doura - Mt. Juliet TN, US

International Classification:

F24H 9/20
F24H 1/00
F24H 15/36
F24H 15/414
F23N 5/00

Abstract:

A fluid heating system including a burner unit is operated based on feedback control loops. The fluid heating system comprises a burner unit configured to heat a fluid, a sensor configured to sense a characteristic of the appliance, and a controller coupled to the burner unit and the sensor. The controller includes an electronic processor and a memory. The controller is configured to receive a first signal corresponding to the characteristic from the sensor, determine, based on the first signal, a first feedback loop control, control combustion of the burner unit based on the first feedback loop control, determine, based on the first feedback loop control, a second feedback loop control, and control combustion of the burner unit based on the second feedback loop control.

US Patent:

20220237668, Jul 28, 2022

Filed:

Apr 14, 2022

Appl. No.:

17/659255

Inventors:

- Atlanta GA, US
Dale Pollak - Hinsdale IL, US
Daniel Mitchell - Austin TX, US
Thomas Cuthbertson - Austin TX, US

Assignee:

Cox Automotive, Inc. - Atlanta GA

International Classification:

G06Q 30/02
G06N 7/00
G06N 20/00

Abstract:

This disclosure describes systems, methods, and devices related to linear regression models and machine learning models for generating vehicle prices. A device may receive information associated with a vehicle, information associated with a dealer selling the vehicle, and market information indicative of previous sales of similar vehicles. The device may generate probabilities of sale of the vehicle at respective price positions based on the information. The device may generate a price elasticity curve for the vehicle based on the probabilities of sale. The device may generate a vehicle score represented by a supply line that is associated with the vehicle based on the information. The device may identify a first intersection of the supply line and the price elasticity curve, generate a market rank based on the intersection, and generate a recommended price for the vehicle based on the market rank as an input to a machine learning model.

US Patent:

20190251586, Aug 15, 2019

Filed:

Feb 8, 2019

Appl. No.:

16/270991

Inventors:

- Atlanta GA, US
Dale Pollak - Hinsdale IL, US
Daniel Mitchell - Austin TX, US
Thomas Cuthbertson - Austin TX, US

Assignee:

Cox Automotive, Inc. - Atlanta GA

International Classification:

G06Q 30/02

Abstract:

This disclosure describes systems, methods, and devices related to predictive modeling for evaluating vehicles. A device may receive vehicle information including a make, model, and year of a first vehicle. The device may determine a competitive set of vehicles that are of the same make, model, and year as the first vehicle, and that have with an odometer reading and a daily sale rate during a period of time. The device may determine, based on the odometer reading, an odometer-adjusted Cost to Market for the first vehicle. The device may determine, based on the daily sale rate during the period of time, a Market Day's Supply of the first vehicle. The device may determine, based on the Market Day's Supply and the odometer-adjusted Cost to Market, a vehicle score of the first vehicle. The device may send presentation data indicative of the vehicle score.