Smart Glasses Acoustic Warning for AGV Detection in Cleanrooms
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Solution Overview
Problem
Workers in cleanrooms with industrial equipment and automated guided vehicles (AGVs) often fail to recognize AGVs due to visual fatigue and noise interference, leading to potential collisions.
Innovation Solution
A work assistance system using smart glasses with an acoustic model to detect AGV warning sounds and issue warnings, and optionally display travel paths, ensuring workers are aware of AGV positions and movements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the automated guided vehicle emits a warning sound during travel, then the worker can be alerted to the vehicle's presence, but the worker may get used to the sound or fail to hear it due to noise interference from other equipment
Solution Approach 1:
The patent introduces a sound collecting unit and acoustic model as intermediary components between the AGV warning sound and the worker. The system collects sounds in the work area, processes them through an acoustic model to detect AGV-specific warning sounds, and provides feedback to the worker through a mobile terminal. This intermediary processing chain overcomes the direct limitation where workers cannot reliably perceive AGV warning sounds amidst other noise sources.
2Productivity
If the worker concentrates on work in a visually complex environment, then work efficiency is improved, but the worker becomes less aware of surroundings and may hit the automated guided vehicle
Solution Approach 1:
The patent implements a feedback mechanism where the sound collecting unit continuously monitors the work area, the acoustic model processes the sound data to detect AGV warning sounds, and the mobile terminal provides immediate feedback to the worker. This closed-loop feedback system allows workers to concentrate on their tasks while the system actively monitors and alerts them to potential hazards, resolving the contradiction between work concentration and environmental awareness.
Data Source
AI summary
Recording data in various environments is collected in a work area, and an acoustic model is constructed by machine learning using an acoustic feature extracted from the recording data as learning data. When a worker wearing smart glasses to which the acoustic model has been mounted performs work in the work area, an automated guided vehicle travels in the work area while emitting a warning sound. The smart glasses detect the warning sound emitted by the automated guided vehicle by inputting the acoustic feature extracted from the collected data of sounds into the acoustic model and issue a warning. Even when the worker is not aware of the warning sound emitted by the automated guided vehicle, the worker can surely recognize the automated guided vehicle by the warning issued by the smart glasses.