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On-Street Parking Spot Detection for Smart Cities

机译:智能城市的路边停车位检测

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Car parking in crowded cities is a big problem. Drivers have to do a blind search to find a free on-street parking spot. Blind searching not only causes traffic congestion but also fuel and time consumption. Indoor parking garages have sensors or light systems to point out free spots, unfortunately, an indoor approach is not applicable to the on-street parking problem due to its expensive nature. In our proposed solution, parking spots are monitored with roadside cameras. First, street images taken by roadside cameras are collected to form a dataset. Second, a Convolutional Neural Network (CNN) based on this dataset is built. Then the trained CNN analyzes a new street image to check if there is a free spot or not. In this paper, a mobile application is also developed and presented. Our mobile application takes the user’s request and triggers the corresponding roadside cameras, and then notifies the driver about the available parking spots around the region and offers navigation to the spot upon the driver’s confirmation.
机译:在拥挤的城市中停车是一个大问题。驾驶员必须进行盲目搜索才能找到免费的路边停车位。盲目搜索不仅会导致交通拥堵,还会导致燃料和时间消耗。室内停车场具有传感器或照明系统以指出自由点,不幸的是,室内方法由于其昂贵的性质而不适用于路旁停车问题。在我们提出的解决方案中,停车位由路边摄像头监控。首先,收集路旁摄像机拍摄的街道图像以形成数据集。其次,基于该数据集构建卷积神经网络(CNN)。然后,受过训练的CNN会分析新的街道图像,以检查是否有空位。在本文中,还开发并展示了一种移动应用程序。我们的移动应用程序会接收用户的请求并触发相应的路边摄像头,然后将区域周围可用的停车位通知驾驶员,并在驾驶员确认后提供该位置的导航。

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