AI Surveying System Automating Conditions via Environmental Data
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Solution Overview
Problem
Surveying techniques using laser light are susceptible to weather and environmental conditions, requiring manual adjustments and lacking automation, which hinders efficient data collection and operation.
Innovation Solution
A surveying system incorporating a camera, processor, and GNSS position measurement device that associates surveying conditions with photographic images and environmental data to generate an AI-estimated model for automating surveying operations, allowing for automatic setting of surveying conditions based on new data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual settings are performed by workers to cope with weather and environmental conditions, then surveying reliability is improved, but labor burden and operation time increase
Solution Approach 1:
The surveying apparatus automatically acquires environmental data (temperature, humidity, atmospheric pressure) and photographic images, then autonomously determines surveying conditions without worker intervention. The system serves itself by using its own sensors and processors to adapt to environmental changes, eliminating the need for manual adjustments while maintaining reliability.
Solution Approach 2:
The system continuously monitors environmental conditions through sensors and photographic images, feeds this information back to the processor, and automatically adjusts surveying conditions based on the feedback. This closed-loop control ensures reliable surveying under varying weather conditions while reducing operation time.
2Measurement precision
If manual adjustments are made to cope with environmental conditions, then surveying accuracy is maintained, but automation level remains low
Solution Approach 1:
The patent replaces manual mechanical adjustment operations with an automated information processing system. The processor analyzes environmental data and photographic images, then automatically determines optimal surveying conditions, substituting human decision-making with computational algorithms while maintaining surveying accuracy.
Solution Approach 2:
The system automatically changes surveying parameters (such as measurement intervals, power settings, and operational modes) based on environmental conditions. The processor adjusts these parameters dynamically without manual intervention, maintaining accuracy while achieving high automation.
3Productivity
If various settings are automatically performed to increase automation, then operation efficiency is improved, but device complexity increases
Solution Approach 1:
The surveying apparatus integrates multiple functions into a single system: environmental sensing (temperature, humidity, pressure sensors), photographic imaging, automated processing, and surveying operations. This multi-functional integration achieves high automation and efficiency without proportionally increasing complexity, as the system performs multiple tasks through unified components.
Solution Approach 2:
The patent combines environmental data acquisition, photographic image capture, and surveying condition determination into a single integrated process. The processor merges information from multiple sources (sensors and camera) to automatically determine surveying conditions, achieving efficiency gains while managing complexity through consolidation.
4Adaptability or versatility
If environmental data and photographic images are collected and processed, then adaptability to environmental conditions is improved, but data processing complexity increases
Solution Approach 1:
The system performs preliminary acquisition and organization of environmental data and photographic images before surveying operations begin. The processor pre-processes this data to identify key environmental factors, enabling rapid adaptation during actual surveying without complex real-time processing, thus improving adaptability while managing complexity.
Data Source
AI summary
Automation of surveying operations is achieved. When surveying is performed by a surveying apparatus, acquisition of a surveying condition, acquisition of surveying data, acquisition of image data, and acquisition of environmental data are performed. These pieces of data are associated with each other and are stored as learning data. On the basis of this learning data, an AI-estimated model for estimating a surveying condition by using image data of a surveying target and environmental data of a surveying site, is generated.