Systems, methods, and devices for classifying and identifying waste in real-time

1. A device, comprising:

a processor;

a display; and

a camera;

wherein the device:

receives, by the processor, photographic input related to one or more waste items via the camera,

transmits, by the processor, and to a computer server, the photographic input related to the one or more waste items;

receives, from the computer server, an identification of the one or more waste items, based on evaluation of the transmitted photographic input using a trained machine learning model to recognize the one or more waste items,

classifies, by the processor, a disposal type for the one or more waste item items, and

provides, by the processor, a suggestion on the display for the disposal type of the one or more waste items,

wherein the suggestion on the display is color coded on the screen to coincide with the classified disposal type for the one or more waste items and encircles the one or more waste items and the suggestion further includes a confidence percentage in the classification of the disposal type for the one or more waste items,

wherein the disposal type for the one or more waste items includes one or more disposal types from the group of trash, recycling, and composting.

2. The device of claim 1 , wherein the display provides an option to take a single photographic image of the one or more waste items.

3. The device of claim 1 , wherein the display provides an option to take multiple photographic images of multiple waste items in addition to the one or more waste items.

4. The device of claim 1 , wherein the suggestion for the disposal type of the waste item is further audibly emitted from the device.

5. A method, comprising:

receiving, by a processor, photographic input, received from a camera, related to one or more waste items;

transmitting, by the processor, and to a computer server, the photographic input related to the one or more waste items;

receiving, from the computer server, an identification of the one or more waste items, based on evaluation of the transmitted photographic input using a trained machine learning model to recognize the one or more waste items;

classifying, by the processor, a disposal type for the one or more waste items; and

displaying, on a screen associated with the processor, a suggestion for the disposal type of the one or more waste items;

wherein the suggestion on the display is color coded on the screen to coincide with the classified disposal type for the one or more waste items and encircles the one or more waste items and the suggestion further includes a confidence percentage in the classification of the disposal type for the one or more waste items,

wherein the disposal type for the one or more waste items includes one or more disposal types from the group of trash, recycling, and composting.

6. The method of claim 5 , further comprising:

displaying, on the screen associated with the processor, an option to take a single photographic image of the one or more waste items.

7. The method of claim 5 , further comprising:

displaying, on the screen associated with the processor, an option to take a multiple photographic images of multiple waste items in addition to the one or more waste items.

8. The method of claim 5 , further comprising audibly emitting, by one or more speakers associated with the processor, the suggestion for the disposal type of the waste item.

9. The method of claim 5 , further comprising receiving, by the processor, an upload of the photographic input related to one or more waste items and applying the upload to train the processor by machine learning to identify the type of the one or more waste items.

10. The method of claim 5 , wherein identifying the one or more items includes object detection of the one or more waste items via a remote memory storage unit.

11. The method of claim 5 , wherein the photographic input is provided by the camera which is also associated with the processor.