Methods and systems for evaluating buildings
A method is provided herein for evaluating a physical building, utilizing an automated image capture apparatus, a spatial computing apparatus, a machine learning model, a blockchain network, and a computer processor, the method including capturing and analyzing images of the building, dividing the building into sections, identifying defective characteristic(s) in and assigning a status to each section, sharing the images and status identifiers with a remote user, the remote user reviewing the images and identifiers, and receiving feedback from the remote user. When a section lacks sufficient images to determine whether a defect is present, the section may be flagged, and a supplemental image(s) may be captured and provided by the remote user. When no additional images are needed, the section may be indicated as completed. Otherwise, the section may retain its flagged status, and the aforementioned steps may be repeated as necessary.
1. A method for evaluating a physical building, the method utilizing an automated image capture apparatus configured for being facially mounted on an operator, a spatial computing apparatus, a machine learning model, a file-sharing platform, a computer processor, and one or more non-transitory computer-readable media storing computer executable instructions; wherein the instructions, when executed by the computer processor, perform image analysis and run a machine learning model, the method comprising:
using the image capture apparatus in conjunction with the spatial computing apparatus, capturing a plurality of images of the physical building;
using the computer processor, analyzing the plurality of images;
identifying a first section and a second section of the physical building, wherein each of the first and second sections corresponds to a structural feature of the physical building or a portion of the structural feature, and wherein the plurality of images comprises a first image of the first section and a second image of the second section;
using the machine learning model, predicting whether each of the first and second sections comprises a defective characteristic;
generating a first status identifier for the first section and a second status identifier for the second section;
sharing the first and second images and the first and second status identifiers with a remote user;
transmitting feedback on the first and second sections from the remote user to the operator, wherein the feedback comprises indicating whether additional information is needed for the section;
for each section, as long as additional information is needed, iteratively:
indicating a flagged status for the section;
capturing a supplemental image of the flagged section;
sharing the supplemental image with the remote user; and
transmitting supplemental feedback from the remote user to the operator;
generating a report about the physical building, the report comprising at least the image and the status identifier of each of the first and second sections; and
if a defective characteristic is identified in the physical building, repairing the defective characteristic.
2. The method of claim 1 , wherein the machine learning model performs identifying the first and second sections.
3. The method of claim 1 , wherein the operator performs identifying the first and second sections.
4. The method of claim 1 , wherein, the report further comprises the supplemental image of the first or second section.
5. The method of claim 1 , wherein each of first and second status identifiers is selected from the group consisting of: comprises a defective characteristic, does not comprise a defective characteristic, and indeterminate status.
6. The method of claim 1 , wherein, prior to generating the report, the remote user indicates whether additional sections of the physical building should be identified and inspected.
7. The method of claim 1 , wherein, prior to generating the report, the machine learning model indicates whether additional sections of the physical building should be identified and inspected.
8. The method of claim 1 , the method further comprising producing a voice feed, the voice feed indicating attributes of the physical building.
9. The method of claim 1 , wherein the structural feature is selected from a floor, a ceiling, and a wall.
10. The method of claim 1 , the method further comprising using a geolocation apparatus to verify the physical building's location.
11. The method of claim 1 , the method further comprising, using an augmented reality apparatus, apprising the operator of the defective characteristic.
12. The method of claim 1 , the method further comprising, using an augmented reality apparatus, overlaying the first and second status identifiers on a visual field of the operator.
13. The method of claim 1 , wherein a generative machine learning algorithm automatically performs generating the report or a draft thereof.
14. The method of claim 13 , wherein the generative machine learning algorithm utilizes the first and second images and the first and second status identifiers to generate the report or draft thereof in a section-by-section fashion.
15. The method of claim 14 , the method further comprising the remote user reviewing the draft report.
16. The method of claim 15 , wherein the file-sharing platform is a blockchain-based writing platform.
17. The method of claim 14 , the method further comprising the operator reviewing the draft report.
18. The method of claim 1 , wherein the remote user is a building engineer or property assessor.
19. The method of claim 1 , the method further comprising utilizing a remote sensing method to assess a characteristic of the building.
20. The method of claim 19 , wherein the remote sensing method is Light Detection and Ranging (LIDAR).