METHODS FOR ASSESSING CONDITIONING OF A TOTAL LOSS VEHICLE AND DEVICES THEREOF
A method, non-transitory computer readable medium, and apparatus that automated assessment of conditioning includes automatically analyzing one or more electronic images of a total loss property based on one or more prior condition assessments and condition guidelines rating data associated with the total loss property. A prior property conditioning of the total loss property is determined based on the analysis of the one or more obtained images. The determined prior property conditioning of the total loss property is provided.
1 . A method comprising:
automatically analyzing, by the computing apparatus, one or more electronic images of a total loss property based on one or more prior condition assessments and condition guidelines rating data associated with the total loss property;
determining, by the computing apparatus, a prior property conditioning of the total loss property based on the analysis of the one or more obtained images; and
providing, by the computing apparatus, the determined prior property conditioning of the total loss property.
2 . The method as set forth in claim 1 wherein the analyzing the one or more electronic images further comprises analyzing, by the computing apparatus, the one or more images with condition assessment artificial intelligence based on stored conditioning data encoded from one or more prior condition assessments and the condition guidelines rating data.
3 . The method as set forth in claim 2 further comprising:
identifying, by the condition management computing apparatus, one or more parts of the total loss property based on an identification of the total loss property;
wherein the one or more electronic images further comprise one or more electronic images of each of the identified one or more parts of the total loss property.
4 . The method as set forth in claim 3 wherein the analyzing the one or more electronic images and the determining the prior property conditioning of the total loss property further comprises:
analyzing, by the computing apparatus, the one or more electronic images for each of the one or more parts using the condition assessment artificial intelligence and the condition guidelines rating data for each of the one or more parts of the total loss property; and
determining, by the computing apparatus, a prior part conditioning for each of the one or more parts of the total loss property based on the analysis of the one or more electronic images for each of the one or more parts of the total loss property and the prior property conditioning of the total loss property based on the prior part conditioning for each of the one or more parts of the total loss property.
5 . The method as set forth in claim 4 further comprising:
obtaining, by the computing apparatus, a part weighting factor for each of the one or more parts of the property;
wherein the determining the prior property conditioning of the total loss property based on the prior part conditioning for each of the one or more parts of the total loss property is further based on applying the part weighting factor for each of the one or more parts of the property on the prior part conditioning for each of the one or more parts of the total loss property.
6 . The method as set forth in claim 5 further comprising:
obtaining, by the computing apparatus, two or more categories of the one or more parts of the property, each of the two or more categories having a category weighting factor, wherein the part weighting factor for each of the one or more parts of the property in each category is based on the category weighting factor.
7 . The method as set forth in claim 1 further comprising determining, by the computing apparatus, a loss appraisal of the property based on an obtained current market value of the property adjusted by the determined prior property conditioning of the total loss property.
8 . A non-transitory computer readable medium having stored thereon instructions for automated assessment of conditioning comprising executable code which when executed by one or more processors, causes the one or more processors to:
automatically analyze one or more electronic images of a total loss property based on one or more prior condition assessments and condition guidelines rating data associated with the total loss property;
determine a prior property conditioning of the total loss property based on the analysis of the one or more obtained images; and
provide the determined prior property conditioning of the total loss property.
9 . The medium as set forth in claim 8 wherein for the analyze the one or more electronic images, the executable code when executed by the one or more processors further causes the one or more processors to:
analyze the one or more images with condition assessment artificial intelligence based on stored conditioning data encoded from one or more prior condition assessments and the condition guidelines rating data.
10 . The medium as set forth in claim 9 wherein the executable code when executed by the one or more processors further causes the one or more processors to:
identify one or more parts of the total loss property based on an identification of the total loss property;
wherein the one or more electronic images further comprises one or more electronic images of each of the identified one or more parts of the total loss property.
11 . The medium as set forth in claim 10 wherein the executable code when executed by the one or more processors for the analyze the one or more electronic images and the determine the prior property conditioning of the total loss property further causes the one or more processors to:
analyze the one or more electronic images for each of the one or more parts using the condition assessment artificial intelligence and the condition guidelines rating data for each of the one or more parts of the total loss property; and
determine a prior part conditioning for each of the one or more parts of the total loss property based on the analysis of the one or more electronic images for each of the one or more parts of the total loss property and the prior property conditioning of the total loss property based on the prior part conditioning for each of the one or more parts of the total loss property.
12 . The medium as set forth in claim 11 wherein the executable code when executed by the one or more processors further causes the one or more processors to:
obtain a part weighting factor for each of the one or of the parts of the property;
wherein the determine the prior property conditioning of the total loss property based on the prior part conditioning for each of the one or more parts of the total loss property is further based on applying the part weighting factor for each of the one or more parts of the property on the prior part conditioning for each of the one or more parts of the total loss property.
13 . The medium as set forth in claim 12 wherein the executable code when executed by the one or more processors further causes the one or more processors to:
obtain two or more categories of the one or more parts of the property, each of the two or more categories having a category weighting factor, wherein the part weighting factor for each of the one or more parts of the property in each category is based on the category weighting factor.
14 . The medium as set forth in claim 8 wherein the executable code when executed by the one or more processors further causes the one or more processors to:
determine a loss appraisal of the property based on an obtained current market value of the property adjusted by the determined prior property conditioning of the total loss property.
15 . A computing apparatus comprising:
a processor; and
a memory coupled to the processor which is configured to be capable of executing programmed instructions stored in the memory to:
automatically analyze one or more electronic images of a total loss property based on one or more prior condition assessments and condition guidelines rating data associated with the total loss property;
determine a prior property conditioning of the total loss property based on the analysis of the one or more obtained images; and
provide the determined prior property conditioning of the total loss property.
16 . The apparatus as set forth in claim 15 wherein for the analyze the one or more electronic images, the processor coupled to the memory is further configured to be capable of executing at least one additional programmed instruction stored in the memory to:
analyze the one or more images with condition assessment artificial intelligence based on stored conditioning data encoded from one or more prior condition assessments and the condition guidelines rating data.
17 . The apparatus as set forth in claim 16 wherein the processor coupled to the memory is further configured to be capable of executing at least on additional programmed instruction stored in the memory to:
identify one or more parts of the total loss property based on an identification of the total loss property;
wherein the one or more electronic images further comprises one or more electronic images of each of the identified one or more parts of the total loss property.
18 . The apparatus as set forth in claim 17 wherein the processor coupled to the memory is further configured for the analyze the one or more electronic images and the determine the prior property conditioning of the total loss property to be capable of executing at least one additional programmed instruction stored in the memory to:
analyze the one or more electronic images for each of the one or more parts using the condition assessment artificial intelligence and the condition guidelines rating data for each of the one or more parts of the total loss property; and
determine a prior part conditioning for each of the one or more parts of the total loss property based on the analysis of the one or more electronic images for each of the one or more parts of the total loss property and the prior property conditioning of the total loss property based on the prior part conditioning for each of the one or more parts of the total loss property.
19 . The apparatus as set forth in claim 18 wherein the processor coupled to the memory is further configured to be capable of executing at least one additional programmed instruction stored in the memory to:
obtain a part weighting factor for each of the one or more parts of the property; wherein the determine the prior property conditioning of the total loss property based on the prior part conditioning for each of the one or more parts of the total loss property is further based on applying the part weighting factor for each of the one or more parts of the property on the prior part conditioning for each of the one or more parts of the total loss property.
20 . The apparatus as set forth in claim 19 wherein the processor coupled to the memory is further configured to be capable of executing at least one additional programmed instruction stored in the memory to:
obtain two or more categories of the one or more parts of the property, each of the two or more categories having a category weighting factor, wherein the part weighting factor for each of the one or more parts of the property in each category is based on the category weighting factor.
21 . The apparatus as set forth in claim 15 wherein the processor coupled to the memory is further configured to be capable of executing at least one additional programmed instruction stored in the memory to:
determine a loss appraisal of the property based on an obtained current market value of the property adjusted by the determined prior property conditioning of the total loss property.