Automation of Inspection Reporting Using Artificial Intelligence

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This is a guest blog by Nick Heim, P.E.

Inspection ReportingInspection ReportingAs engineering professionals, we continually seek innovative ways to improve our industry, enhance efficiency, and ensure the safety of the public.

Today, I would like to highlight one piece of emerging technology that I believe will have a significant and immediate impact on inspection workflows — use of artificial intelligence to generate reporting.

How Does Automation of Inspection Reporting Using Artificial Intelligence Work?

The premise of this type of technology is ingesting inspection data (photos, videos, voice memos, etc.) and having artificial intelligence (AI) analyze the data to convert it into a written report format.

This will require a minimum amount of data to be included (e.g., describing what one is seeing during a site visit on a video recording) such that the software can convert the inspection data.

Instead of the time-consuming process of starting at a blank screen, generating a report from scratch, or modifying a report from a similar project, the idea here is to start with data that was already generated during the inspection to reduce the time frame from inspection to report.

Example Using InspectMind AI

An application that utilizes this type of technology is InspectMind AI.

Let’s walk through an example, assuming that you are back at your desk (web application) or field trailer/vehicle (mobile application) with inspection data in hand.

The process begins by entering some basic information, as shown in the image below. This is boilerplate information that will be included in the report.

  • Next, upload your inspection data to the application. The image below describes the basic setup and features, using a residential structural inspection as an example.

  • After selecting your report type/template and clicking the “Generate” button, the application will begin processing the inspection data.
  • After a few minutes, the report will be generated. The image below shows a portion of the output using a residential structural inspection as an example.

Common Questions About the Technology

With the recent, widespread use of artificial intelligence, there are questions from the inspection community about these types of technologies. Below are some common questions that I have received about the use of InspectMind AI.

Q: Am I able to edit the inspection report after it is processed?

A: Yes. The output of the application is a Microsoft Word file that can be edited by the inspector or other end users.

The goal here is to augment the inspector’s workflow while still giving them full control over the end deliverable. Just like non-AI generated deliverables, AI-generated deliverables should still be checked by humans for content and accuracy.

Q: Am I limited to the report template as shown in the example above?

A: No. Customers of the application can customize the report template based on the specifics of their business and individual workflows. This process involves uploading past reports to be ingested by the application. From there, the InspectMind team works to customize your template.

Q: What types of inspection can the application be used for?

  1. The application is general in nature, and not limited to any one specific inspection use case.Examples include:
  • Construction daily field reports
  • Parking structure condition assessment report
  • Residential structural engineering investigation report
  • Balcony inspection report
  • Complementary, high-level, initial business development report

Q: What happens to my data after it is uploaded?

A: All user data is securely stored on AWS S3 and can only be accessed by the user when they are logged into the application.

Q: Does the application learn from my specific inspection and reporting procedures?

A: The application only learns from the previous reports used during the initial template customization. However, use of reports generated on the InspectMind AI app for future learning is a realistic feature under consideration.

About the Author Nick Heim, P.E.

structurecarestructurecareNick Heim, P.E., is a civil engineer with six years of experience in the repair and restoration of existing structures. Nick is also the host of the AEC Engineering and Technology Podcast (“AECTECH”) and brings valuable insights and expertise to listeners worldwide.

Nick’s interests lie at the intersection between the built world and technology, and he can be found looking for the ever-changing answer to the question, “How can we do this better?” He can be found on LinkedIn, producing content about use of technologies in his civil engineering career and small business.

We would love to hear any questions you might have or stories you might share about the automation of inspection reporting using artificial intelligence.

Please leave your comments, feedback or questions in the section below.

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To your success,

Anthony Fasano, PE, LEED AP
Engineering Management Institute
Author of Engineer Your Own Success

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