MEAN stack to enhance the advancement of parking application: A narrative review. (February 2019)

• Record Type: Journal Article
• Authors: Nugraha, Dian; Ahmed, Falah Y. H.
• Is Part Of: Journal of physics. Volume 1167(2019)
• Publication Date: 2019-02
• Subjects: Smart Parking -- Application technology -- Parking problem -- parking system Advancement -- MEAN Stack; Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1167/1/012075
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: Parking is becoming a problem, especially during rush hour. This is an effect of increasing number of private cars that demand of parking space to follow increase. In order to anticipate this key issue of parking, then the smart parking system has been developed. Advancement of smart parking has been a key concern to produce an application system with high performance, flexibility, and scalability in emerging technologies that can provide information about parking in real-time. The empirical study in this area has conducted various parking system reservations, monitoring, and guidance systems that can make parking process easier. This review emphasizes the aim to give a narrative review of the papers in our pool of papers to prove the evidence and provide an application technology advancement to produce a real-time parking system. The review has included 22 papers from our pool of papers which has examined, which are analyzed from used system technology to build the smart parking application. The narrative review was carried out to exposes the existing application parking and compared to parking application that have implemented a MEAN stack. Search terms used in the literature review are applications that have been elaborate a study of smart parking application as a key concern of this study. Synthesis of the papers on the pool has suggested that there is an optimistic reason that a MEAN stack approach might be effective to produce a real-time application high performance, flexibility, and scalability technologies from a smart parking application.