Systems and methods for enhancing waste disposal and energy efficiency using sensor and alternative power technologies

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.

2. The computer system of claim 1 , wherein the at least one processor and associated transceiver is further programmed to:

determine, based upon a level of waste detected by a level sensor, whether collection of waste in the waste compartment within the multi-compartment waste bin is required;

in response to determining that the collection of waste in the waste compartment within the multi-compartment waste bin is required, generate an alert including information corresponding to the multi-compartment waste bin for waste collection; and

transmit the alert, via wireless communication, to one or more client devices associated with at least one user to notify the at least one user that the collection of waste in the waste compartment within the multi-compartment waste bin is required.

3. The computer system of claim 1 , wherein the at least one processor and associated transceiver is further programmed to:

determine, based upon a level of recyclables detected by a level sensor, whether collection of recyclables in the recyclable compartment within the multi-compartment waste bin is required;

in response to determining that the collection of recyclables in the recyclables compartment within the multi-compartment waste bin is required, generate an alert including information corresponding to the multi-compartment waste bin for the collection of recyclables; and

transmit the alert, via wireless communication, to one or more client devices associated with at least one user to notify the at least one user that the collection of recyclables in the recyclables compartment within the multi-compartment waste bin is required.

4. The computer system of claim 1 , wherein the at least one sensor is a digital camera, and the sensor data includes digital image data.

5. The computer system of claim 1 , wherein the at least one processor and associated transceiver is further programmed to:

utilize machine learning techniques to analyze the sensor data to determine whether the item associated with the sensor data is plastic, aluminum, glass, or cardboard.

6. The computer system of claim 1 , wherein the at least one movable lid is configured to allow gravity to move the waste item into the waste compartment within the multi-compartment waste bin once the waste item is placed or dropped into the multi-compartment waste bin.

7. The computer system of claim 1 , wherein the at least one movable lid is configured to allow gravity to move the recyclable item into the recyclable compartment within the multi-compartment waste bin once the recyclable item is placed or dropped into the multi-compartment waste bin.

8. The computer system of claim 1 , wherein the at least one processor and associated transceiver is further programmed to:

receive location data from the multi-compartment waste bin; and

transmit the location data to a client device associated with at least one user.

9. The computer system of claim 1 , wherein the at least one processor is further programmed to store, in the at least one memory device, location data and user data received from one or more client devices of at least one user.

10. The computer system of claim 1 , wherein the at least one processor and associated transceiver is further programmed to:

generate one or more notifications including at least one of recycling practices, bin locations, recycling days alerts, non-recycling days alerts, and bulletins addressing recycling; and

transmit the one or more notifications to at least one of client devices and electronic signs.

11. The computer system of claim 1 , wherein the at least one processor and associated transceiver is further programmed to:

receive, from the at least one sensor, a location of one or more multi-compartment waste bins, wherein the one or more multi-compartment waste bins include at least one internal recyclable bin and one internal waste bin;

generate, using the received location, one or more maps including the one or more multi-compartment waste bins; and

transmit the one or more maps to one or more client devices for display on the one or more client devices.

12. The computer system of claim 11 , wherein the at least one processor and associated transceiver is further programmed to:

generate a route map using the generated one or more maps;

prioritize the location of the one or more multi-compartment waste bins in the route map, wherein the prioritization is performed based upon ae level of waste of each multi-compartment waste bin; and

transmit the route map to one or more waste collection providers.

13. A computer-implemented method 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, the multi-compartment waste bin including at least one moveable lid positioned within the multi-compartment waste bin, the method being implemented by at least one processor and associated transceiver in communication with at least one memory device and at least one sensor, the method comprising:

receiving 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;

utilizing 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 causing 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 causing 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.

14. The computer-implemented method of claim 13 further comprising:

determining, based upon a level of waste detected by a level sensor, whether collection of waste in the waste compartment within the multi-compartment waste bin is required;

in response to determining that the collection of waste in the waste compartment within the multi-compartment waste bin is required, generating an alert including information corresponding to the multi-compartment waste bin for waste collection; and

transmitting the alert, via wireless communication, to one or more client devices associated with at least one user to notify the at least one user that the collection of waste in the waste compartment within the multi-compartment waste bin is required.

15. The computer-implemented method of claim 13 further comprising:

determining, based upon a level of recyclables detected by a level sensor, whether collection of recyclables in the recyclable compartment within the multi-compartment waste bin is required;

in response to determining that the collection of recyclables in the recyclables compartment within the multi-compartment waste bin is required, generating an alert including information corresponding to the multi-compartment waste bin for the collection of recyclables; and

transmitting the alert, via wireless communication, to one or more client devices associated with at least one user to notify the at least one user that the collection of recyclables in the recyclables compartment within the multi-compartment waste bin is required.

16. The computer-implemented method of claim 13 , wherein the at least one sensor is a digital camera, and the sensor data includes digital image data.

17. The computer-implemented method of claim 13 further comprising:

utilizing machine learning techniques to analyze the sensor data to determine whether the item associated with the sensor data is plastic, aluminum, glass, or cardboard.