Fog Computing-Based System for Decentralized Smart Parking System by Using Firebase

Haposan Yoga, Pradika Napitupulu, I. Gde, Dharma Nugraha
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Abstract

The growth of vehicle number is unavoidable whilst the availability of parking is not directly proportional with this condition. Nowadays, many shopping centers do not have sufficient parking spot, causing customers to have difficulty in finding available parking spots. Research has been conducted to tackle the issue of finding available parking spots. Much of this research proposed the narrowband-Internet of things (NB-IoT) as a fog node. For communication purposes, this NB-IoT-based fog node has some shortcomings, such as security and privacy, lower data rate, higher cost in development, dependency with wireless system, and only covers one area. In this research, the fog computing was proposed to decentralize smart parking system by using Firebase to cover several areas or malls in one system and interface. Instead of using NB-IoT, this research employed decentralized local server as a fog node to deliver a fast data exchange. Firestore database (Firebase) was also used to secure, manage, and analyze the data in the cloud. Conjunctively, the Android application was created as a user interface to book and find the availability of parking spots. The Android application was built using Android Studio and implemented authentication to keep the data access secure and private. The testing scenario was done following the design unified modeling language (UML). The research results confirmed that the fog computing system successfully supported the decentralized smart parking system and was able to be implemented for covering several areas or malls in one system.
使用 Firebase 实现基于雾计算的分散式智能停车系统
车辆数量的增长是不可避免的,而停车位的供应却与这种情况不成正比。如今,许多购物中心没有足够的停车位,导致顾客很难找到可用的停车位。针对寻找可用停车位的问题,已经开展了一些研究。这些研究大多提出将窄带物联网(NB-IoT)作为雾节点。就通信目的而言,这种基于 NB-IoT 的雾节点存在一些不足,如安全性和隐私性、较低的数据传输速率、较高的开发成本、与无线系统的依赖性以及只能覆盖一个区域。在这项研究中,提出了利用 Firebase 将雾计算分散到智能停车系统中,在一个系统和界面中覆盖多个区域或商场。本研究没有使用 NB-IoT,而是采用了分散的本地服务器作为雾节点,以提供快速的数据交换。此外,还使用了 Firestore 数据库(Firebase)来保护、管理和分析云中的数据。同时,还创建了安卓应用程序,作为预订和查找停车位可用性的用户界面。该安卓应用程序使用 Android Studio 构建,并实施了身份验证,以确保数据访问的安全性和私密性。测试场景是按照统一建模语言(UML)设计完成的。研究结果证实,雾计算系统成功地支持了分散式智能停车系统,并且能够在一个系统中覆盖多个区域或商场。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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