US 11,897,690 B1
Systems and methods for enhancing waste disposal and energy efficiency using sensor and alternative power technologies
Matthew Megyese, Phoenix, AZ (US); Sarah Ann Lockenvitz, Scottsdale, AZ (US); Paul Bates, Mesa, AZ (US); Nicholas Carmelo Marotta, Scottsdale, AZ (US); Cathy Jo Roth, Queen Creek, AZ (US); Austin Rowley, Mesa, AZ (US); and Jared Wheet, Mesa, AZ (US)
Assigned to STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY, Bloomington, IL (US)
Filed by State Farm Mutual Automobile Insurance Company, Bloomington, IL (US)
Filed on Sep. 11, 2020, as Appl. No. 17/018,813.
Claims priority of provisional application 62/972,488, filed on Feb. 10, 2020.
Claims priority of provisional application 62/949,776, filed on Dec. 18, 2019.
Claims priority of provisional application 62/939,903, filed on Nov. 25, 2019.
Int. Cl. B65F 1/00 (2006.01); B65F 1/16 (2006.01); B65F 9/00 (2006.01); G06N 20/00 (2019.01); G08B 21/18 (2006.01); B07C 5/342 (2006.01); H04B 1/38 (2015.01); H04B 1/3827 (2015.01)
CPC B65F 1/004 (2013.01) [B07C 5/3422 (2013.01); B65F 1/1607 (2013.01); G06N 20/00 (2019.01); G08B 21/182 (2013.01); H04B 1/3827 (2013.01); B07C 2501/0054 (2013.01); B65F 2001/008 (2013.01); B65F 2210/128 (2013.01); B65F 2210/138 (2013.01); B65F 2210/1443 (2013.01); B65F 2210/168 (2013.01)] 17 Claims
OG exemplary drawing
 
1. A computer system for enhancing waste disposal, and directing waste and recyclables to corresponding compartments within a multi-compartment waste bin including a waste compartment and a recycling compartment, wherein the multi-compartment waste bin includes at least one moveable lid positioned within the multi-compartment waste bin, the computer system including at least one processor and associated transceiver in communication with at least one memory device and at least one sensor, the at least one processor and associated transceiver programmed to:
receive sensor data associated with an item from at least one sensor, wherein the sensor data is generated by the at least one sensor located proximate to a multi-compartment waste bin;
utilize machine learning techniques to analyze the sensor data to determine whether the item is a waste item or a recyclable item;
if the item is determined to be a waste item from analysis of the sensor data, automatically cause the multi-compartment waste bin to move the at least one moveable lid to direct the waste item, after being placed within the multi-compartment waste bin, to move toward a waste compartment within the multi-compartment waste bin by opening the waste compartment and closing the recycling compartment within the multi-compartment waste bin; and
if the item is determined to be a recyclable item from analysis of the sensor data, automatically cause the multi-compartment waste bin to move the at least one moveable lid to direct the recyclable item, after being placed within the multi-compartment waste bin, to move toward a recyclable compartment within the multi-compartment waste bin by opening the recycling compartment and closing the waste compartment within the multi-compartment waste bin to facilitate separation of waste and recyclables into dedicated waste compartments and recyclable compartments, and the collection of recyclable items.