Method and apparatus for recycling feedstock identification

1 . A method for recycling feedstock identification, the method comprising:

Identifying a delivery portion of a recycling feedstock by providing at least one delivery identifier for delivery identification;

Recording at least one image of at least one portion of the delivery portion of the recycling feedstock;

Annotating at least one data identifier on the recorded at least one image, the data identifier identifying an impurity of the at least one portion of the delivery portion of the recycling feedstock;

Evaluating a quality level of the at least one portion of the delivery portion of the recycling feedstock based on the recorded at least one image and the at least one annotated data identifier; and

Deciding an acceptance of the delivery portion of the recycling feedstock based on the evaluated quality level of the at least one portion of the delivery portion of the recycling feedstock.

2 . The method according to claim 1 ,

wherein the data identifier further specifies a specification and/or an impurity level of the at least one portion of the delivery portion of the recycling feedstock per delivery.

3 . The method according to claim 2 ,

wherein the annotating the at least one data identifier on the recorded at least one image comprises labelling the recorded at least one image with the at least one annotated data identifier resulting in at least one enhanced image with computer-generated perceptual information.

4 . The method according to claim 1 ,

wherein the method further comprises:

performing a login process at a tablet using Multi-factor authentication, MFA, to start a Multi-user environment, wherein the at least one data identifier and the recorded at least one image are mapped to a specific user of the started Multi-user environment.

5 . The method according claim 1 ,

wherein the method further comprises:

mapping measured quality levels of multiple portions of the delivery portion of the recycling feedstock to the evaluated quality level of the recycling material; and/or

performing machine learning by building a model based on the measured quality levels of multiple portions of the delivery portion of the recycling feedstock and the evaluated quality level of the recycling material to improve the evaluation of the quality level of the recycling material.

6 . The method according to claim 1 ,

wherein the method further comprises:

scanning a bar code tagged to the recycling material, the bar code providing the at least one delivery identifier for delivery identification; and

evaluating the quality level of the at least one portion of the delivery portion of the recycling feedstock based on the recorded at least one image and the at least one annotated data identifier and the delivery identifier for delivery identification.

7 . The method according to claim 1 ,

wherein the method further comprises:

generating input data providing at least one parameter of the recycling material; and

evaluating the quality level of the at least one portion of the delivery portion of the recycling feedstock based on the recorded at least one image and the at least one annotated data identifier and the at least one parameter of the recycling material.

8 . The method according to claim 7 ,

wherein the input data is generated by user input.

9 . A computer-readable medium comprising instructions which, when executed by a computer, cause the computer to carry out the steps of the method of claim 1 .

10 . An apparatus for recycling feedstock identification, the apparatus comprising:

an image sensor which is configured to identify a delivery portion of a recycling feedstock by providing at least one delivery identifier for delivery identification and to record at least one image of at least one portion of the delivery portion of the recycling feedstock; and

a processor, which is configured to annotate at least one data identifier on the recorded at least one image, the data identifier identifying an impurity of the at least one portion of the delivery portion of the recycling feedstock; and the processor further configured to evaluate a quality level of the at least one portion of the delivery portion of the recycling feedstock based on the recorded at least one image and the at least one annotated data identifier, and to decide an acceptance of the delivery portion of the recycling feedstock based on the evaluated quality level of the at least one portion of the delivery portion of the recycling feedstock.

11 . The apparatus according to claim 10 ,

wherein the data identifier further specifies a specification and/or an impurity level of the at least one portion of the recycling material per delivery.

12 . The apparatus according to claim 10 ,

wherein the processor is further configured to perform a login process at a tablet using Multi-factor authentication, MFA, to start a Multi-user environment, wherein the at least one data identifier and the recorded at least one image are mapped to a specific user of the Multi-user environment.

13 . The apparatus according to claim 10 ,

wherein the processor is further configured to map measured quality levels of multiple portions of the delivery portion of the recycling feedstock to the evaluated quality level of the recycling material; and

wherein the processor is further configured to perform machine learning building a model based on the measured quality levels of multiple portions of the delivery portion of the recycling feedstock and the evaluated quality level of the recycling material to improve the evaluation of the quality level of the recycling material.

14 . The apparatus according to claim 10 ,

wherein the image sensor and the processor are further configured to scan a bar code tagged to the recycling material, the bar code providing the at least one delivery identifier for delivery identification; and

wherein the processor is further configured to evaluate the quality level of the at least one portion of the delivery portion of the recycling feedstock based on the recorded at least one image and the at least one annotated data identifier and the delivery identifier for delivery identification.

15 . The apparatus according to claim 10 ,

wherein the processor is further configured to generate input data providing at least one parameter of the recycling material; and

wherein the processor is further configured to evaluate the quality level of the at least one portion of the delivery portion of the recycling feedstock based on the recorded at least one image and the at least one annotated data identifier and the at least one parameter of the recycling material.

16 . The apparatus according to claim 15 ,

wherein the input data is generated by user input.

17 . A system for recycling feedstock identification, the system comprising a tablet with the apparatus according to claim 10 wherein the system further comprises:

a data base configured to map measured quality levels of multiple portions of the recycling material to the evaluated quality level of the recycling material

a cloud structure configured to perform machine learning by building a model based on the measured quality levels of multiple portions of the recycling material and the evaluated quality level of the recycling material to improve the evaluation of the quality level of the recycling material.