AI Construction Log Generation With Template-Based Standardization
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Solution Overview
Problem
Existing construction management software applications require manual and time-consuming processes for generating construction activity logs, leading to potential human errors, omissions, and inconsistent data formats, which can cause miscommunication among project parties.
Innovation Solution
A computing platform utilizing generative AI models to automatically generate construction activity logs based on construction project data and predefined templates, determining the log type and populating input fields with relevant data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual processes are used to generate construction activity logs, then flexibility and adaptability are maintained, but time consumption and human error increase
Solution Approach 1:
The system enables automatic generation of construction activity logs by having the computing platform autonomously extract data from project information, determine appropriate log types, select templates, and populate fields without requiring manual intervention for each log entry
Solution Approach 2:
The patent replaces the manual mechanical process of log creation with an automated computational system that uses data extraction, template matching, and automatic population algorithms to generate logs efficiently and consistently
2Manufacturing precision
If manual processes are used to generate construction activity logs, then adaptability to different log types is maintained, but data consistency and standardization deteriorate
Solution Approach 1:
The system implements a universal template mechanism that can handle multiple types of construction activity logs through a single automated process, where templates define standardized structures that adapt to different log types while maintaining consistent data formats
Solution Approach 2:
The system changes parameters by dynamically selecting different templates based on the determined log type, allowing the same automated system to produce various log formats (daily logs, weekly reports, inspection records) while maintaining internal consistency through parameterized template fields
3Productivity
If automated generation is implemented, then time consumption and human error are reduced, but system complexity increases
Solution Approach 1:
The automated system is segmented into distinct functional modules: data extraction module, log type determination module (using AI), template selection module, and automatic population module. This segmentation allows each component to be developed and maintained independently while working together to achieve high productivity
Data Source
AI summary
A computing system is configured to: (i) generating a first prompt for input to a generative AI model, wherein the first prompt comprises input data and a request to determine a type of log to be generated, (ii) inputting the first prompt to the generative AI model, causing the model to output an indication of a type of log to be generated, (iii) based on the indication, obtaining a template for the type of log to be generated, (iv) generating a second prompt for input to a generative AI model, wherein the second prompt comprises the template for the type of log to be generated, the input data, and a request to generate a construction activity log of the indicated type, and (v) inputting the second prompt to the generative AI model thereby causing the generative AI model to generate a construction activity log of the indicated type.