딥러닝 기반의 주차 층수 탐지 애플리케이션의 개발
Development of Deep Learning-Based Parking Floor Detection Application
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초록
본 연구에서는 딥러닝을 사용하여 실내 주차 층수 감지 애플리케이션 솔루션을 개발하였다. 이전에는 단순 대기압데이터를 기반으로 층수 예측을 수행했다. 그러나 본 연구에서는 이 솔루션을 사용하여 Android 및 iPhone에서 작동하는 애플리케이션을 개발하였다. Android 및 iPhone 플랫폼에 맞춘 모바일 애플리케이션의 특성에 최적화된 사용자 경험을 제공한다. 이러한 접근 방식은 주차 층수 파악을 더욱 효율적이고 직관적으로 만든다. 또한 사용자의 주차편의성을 크게 개선하고 궁극적으로 ESG(환경, 사회, 지배구조) 분야에 도움이 될 것이다.
Abstract
In this study, we develop an application to detect the number of indoor parking floors using deep-learning techniques. Previously, floor-number predictions relied solely on simple atmospheric pressure data. In this study, we expand this solution to create applications for both Android and iPhone platforms. This ensures that user experience is optimized for the unique characteristics of mobile applications on each platform. Our approach renders parking-space navigation more efficient and intuitive, thus significantly enhancing user convenience. Ultimately, this development contributes positively to environmental, social, and governance fields.
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