2019
DOI: 10.1016/j.procs.2019.12.091
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iMars: Intelligent Municipality Augmented Reality Service for Efficient Information Dissemination based on Deep Learning algorithm in Smart City of Jeddah

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Cited by 12 publications
(7 citation statements)
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“…This SLR identified two applications where this technology can be applied for smart cities. The first is the study of [ 26 ] that analyses the application of AR service for efficient information dissemination based on a deep learning algorithm for the smart city of Jeddah in Saudi Arabia. Their proposed framework uses the system architecture of the iMARS system that consists of user alerts, deep learning, databases, and municipality services.…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…This SLR identified two applications where this technology can be applied for smart cities. The first is the study of [ 26 ] that analyses the application of AR service for efficient information dissemination based on a deep learning algorithm for the smart city of Jeddah in Saudi Arabia. Their proposed framework uses the system architecture of the iMARS system that consists of user alerts, deep learning, databases, and municipality services.…”
Section: Resultsmentioning
confidence: 99%
“…The SLR also discovered that AR could be effectively used for system management and monitoring. Studies included in this research, including [ 8 , 26 , 27 , 28 , 29 , 30 ], which illustrated how AR could be applied in areas such as real-time information dissemination, smart traffic monitoring, rent management, emergency management, lighting system management, and energy management to eliminate bottlenecks associated in such systems, and in turn, improve efficiency and productivity while reducing costs. Similar studies have also been conducted in other contexts to complement studies included in this SLR.…”
Section: Discussionmentioning
confidence: 99%
“…Markerless systems, which do not require predefined markers for tracking, are more prominently represented in the literature, with 30 articles in total. Among them, 21 articles explore location-based systems (e.g., [45]), 8 delve into superimposition-based systems (e.g., [46]), and only 1 investigates projection-based systems [47]. Additionally, 9 articles examine hybrid systems that combine elements from both marker-based and marker-less approaches (e.g., [48]).…”
Section: Ar Systemsmentioning
confidence: 99%
“…The marker is recognized through the camera of the smartphone and the digital augmentation is anchored on the marker as long as it is positioned in the field of view of the camera. This tracking method is easy to implement through native apps (Camera app) or via custom-build applications using AR development toolkits (Basori et al, 2019). Marker-based AR has high accuracy compared to other types of AR technology, particularly for indoor environments.…”
Section: Marker-based Armentioning
confidence: 99%