论文标题

基于计算机视觉的停车优化系统

Computer Vision Based Parking Optimization System

论文作者

Chandrasekaran, Siddharth, Reginald, Jeffrey Matthew, Wang, Wei, Zhu, Ting

论文摘要

技术的改进与时间和时间相关的问题是线性相关的。人们已经看到,随着时间的流逝,人类面临的问题的数量也增加。但是,解决这些问题的技术也趋于改善。从车辆发明开始的最早的现有问题之一就是停车。多年来,使用技术解决此问题的便利性已经发展,但停车问题仍然无法解决。其背后的主要原因是停车不仅涉及一个问题,而且还包括内在的一组问题。这些问题之一是在分布式停车生态系统中检测停车位的占用。在分布式系统中,用户会发现优选的停车位,而不是随机停车位。在本文中,我们提出了一个基于Web的应用程序,作为在不同停车位中检测停车空间的解决方案。该解决方案基于计算机视觉(CV),并使用Python 3.0编写的Django框架构建。该解决方案可以解决占用检测问题,同时为用户提供基于可用性及其偏好确定块的选项。我们提出的系统的评估结果是有希望的和有效的。所提出的系统也可以与不同的系统集成,并用于解决其他相关的停车问题。

An improvement in technology is linearly related to time and time-relevant problems. It has been seen that as time progresses, the number of problems humans face also increases. However, technology to resolve these problems tends to improve as well. One of the earliest existing problems which started with the invention of vehicles was parking. The ease of resolving this problem using technology has evolved over the years but the problem of parking still remains unsolved. The main reason behind this is that parking does not only involve one problem but it consists of a set of problems within itself. One of these problems is the occupancy detection of the parking slots in a distributed parking ecosystem. In a distributed system, users would find preferable parking spaces as opposed to random parking spaces. In this paper, we propose a web-based application as a solution for parking space detection in different parking spaces. The solution is based on Computer Vision (CV) and is built using the Django framework written in Python 3.0. The solution works to resolve the occupancy detection problem along with providing the user the option to determine the block based on availability and his preference. The evaluation results for our proposed system are promising and efficient. The proposed system can also be integrated with different systems and be used for solving other relevant parking problems.

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