文章基本信息

标题：Vacant Parking Lot Information System Using Transfer Learning and IoT
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作者：Edwin K Jose ; S. Veni
期刊名称：Journal of ICT Research and Applications
印刷版ISSN：2337-5787
电子版ISSN：2338-5499
出版年度：2018
卷号：12
期号：3
页码：207-218
语种：English
出版社：Institut Teknologi Bandung
其他摘要：Parking information systems have become very important, especially in metropolitan areas as they help to save time, effort and fuel when searching for parking. This paper offers a novel low-cost deep learning approach to easily implement vacancy detection at outdoor parking spaces with CCTV surveillance. The proposed method also addresses issues due to perspective distortion in CCTV images. The architecture consists of three classifiers for checking the availability of parking spaces. They were developed on the TensorFlow platform by re-training MobileNet (a pre-trained Convolutional Neural Network (CNN)) model using the transfer learning technique. A performance analysis showed 88% accuracy for vacancy detection. An end-to-end application model with Internet of Things (IoT) and an Android application is also presented. Users can interact with the cloud using their Android application to get real-time updates on parking space availability and the parking location. In the future, an autonomous car could use this system as a V2I (Vehicle to Infrastructure) application in deciding the nearest parking space.
关键词：Android application;CCTV surveillance;CNN;IoT;MobileNet;outdoor parking;TensorFlow;transfer learning;V2I
其他关键词：Android application;CCTV surveillance;CNN;IoT;MobileNet;outdoor parking;TensorFlow;transfer learning;V2I