Highway engineering drawing quantity and price integrated cost preparation method and system based on ai enhancement

By combining AI multimodal recognition technology and rule engine, end-to-end automation of highway engineering cost preparation has been achieved, solving the problems of low efficiency, poor accuracy and difficulty in data traceability in existing technologies, and realizing integrated management and dynamic updating of map, quantity and price.

CN121598913BActive Publication Date: 2026-07-21GUANGDONG TOONE TECH CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
GUANGDONG TOONE TECH CO LTD
Filing Date
2026-01-28
Publication Date
2026-07-21

AI Technical Summary

Technical Problem

Existing technologies suffer from low efficiency, poor accuracy, and difficulty in data traceability in highway engineering cost estimation, especially in their insufficient ability to identify linear structures and stationing systems, making it impossible to form an integrated data management and control system that combines maps, quantities, and prices.

Method used

AI multimodal recognition technology is used to process design drawings, realizing an end-to-end automated process from drawing parsing to quantity calculation and pricing. Data traceability and dynamic updates are achieved through an integrated management framework for drawings, quantities and prices, and automatic correlation between quantities and costs is achieved by combining a rule engine.

Benefits of technology

It improves the efficiency and accuracy of cost estimation, supports input of design data in multiple formats, ensures data reliability and management efficiency, and enables rapid dynamic updates when drawings are changed.

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Abstract

The application relates to the field of highway engineering digital management and artificial intelligence technology, and provides a highway engineering quantity-price integration cost preparation method and system based on AI enhancement. The method comprises the following steps: obtaining a design drawing to be processed; based on the AI multi-modal recognition capability, the input design drawing is processed, automatic extraction, calculation and cleaning are performed, and a multi-level engineering quantity combination dataset based on standard EBS classification and coding is formed; the engineering quantity combination dataset is automatically associated to the budget cost item, the list sub-item or the quota sub-item based on the rule engine, and the cost data of each stage is generated according to the different preparation depth and data category requirements of the cost of different stages; the data of each link from input to output is penetrated or traced back, and a quantity-price integration management framework is generated; when the design drawing changes, the related engineering quantity combination dataset and cost are updated based on the quantity-price integration management framework to generate standardized cost data and reports.
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