Augmented Reality and GPS-Based Resource Efficient Navigation System for Outdoor Environments: Integrating Device Camera, Sensors, and Storage

Abstract

Contemporary navigation systems rely upon localisation accuracy and humongous spatial data for navigational assistance. Such spatial-data sources may have access restrictions or quality issues and require massive storage space. Affordable high-performance mobile consumer hardware and smart software have resulted in the popularity of AR and VR technologies. These technologies can help to develop sustainable devices for navigation. This paper introduces a robust, memory-efficient, augmented-reality-based navigation system for outdoor environments using crowdsourced spatial data, a device camera, and mapping algorithms. The proposed system unifies the basic map information, points of interest, and individual GPS trajectories of moving entities to generate and render the mapping information. This system can perform map localisation, pathfinding, and visualisation using a low-power mobile device. A case study was undertaken to evaluate the proposed system. It was observed that the proposed system resulted in a 29 percent decrease in CPU load and a 35 percent drop in memory requirements. As spatial information was stored as comma-separated values, it required almost negligible storage space compared to traditional spatial databases. The proposed navigation system attained a maximum accuracy of 99 percent with a root mean square error value of 0.113 and a minimum accuracy of 96 percent with a corresponding root mean square value of 0.17.

Pedestrian Augmented Reality Navigator

“…This system, like all IMU-based systems, is prone to accumulating errors, often called drift. Singh et al [ 5 ] proposed an AR-based navigation system that uses a smartphone. The spatial data are stored as a CSV file, and the location identification is performed using a GPS receiver and the stored data.…”

An Enhancement of Outdoor Location-Based Augmented Reality Anchor Precision through VSLAM and Google Street View

“…The LAR application mainly relies on the positioning of the virtual content in the physical world to create a seamless blend of digital and real environments. The key metrics of LAR accuracy consist of the heading, vertical position, and horizontal position of the user’s device [ 5 , 6 ].…”

“…The key metrics of LAR accuracy consist of the heading, vertical position, and horizontal position of the user's device [5,6].…”

GPS-Induced Disparity Correction for Accurate Object Placement in Augmented Reality

“…Additionally, indoor-based approaches lack adequate outdoor application [23]. Although outdoor AR solutions employing GPS have been proposed, the inaccuracies associated with GPS can significantly hinder the precise localization and recognition of objects [24]. This study aims to address these challenges by proposing a technique that not only accurately displays objects within the AR environment but also corrects their positioning, thus enhancing both the user experience and the accuracy of AR advertising objects.…”