Easily Guiding of Blind: Providing Information and Navigation - SmartNav

Duarte, Karen; Cecílio, José; Furtado, Pedro

doi:10.1007/978-3-319-18802-7_18

Cited by 1 publication

(1 citation statement)

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“…The localization algorithm uses nearness to beacons or proximity detection to compute the position of the user. Duarte et al [52] proposed a system to guide the people with VI through public indoor areas. The system namely, SmartNav consist of a smartphone (Android application) and BLE beacons.…”

Section: Related Workmentioning

confidence: 99%

Comparative analysis of computer-vision and BLE technology based indoor navigation systems for people with visual impairments

et al. 2019

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BackgroundConsiderable number of indoor navigation systems has been proposed to augment people with visual impairments (VI) about their surroundings. These systems leverage several technologies, such as computer-vision, Bluetooth low energy (BLE), and other techniques to estimate the position of a user in indoor areas. Computer-vision based systems use several techniques including matching pictures, classifying captured images, recognizing visual objects or visual markers. BLE based system utilizes BLE beacons attached in the indoor areas as the source of the radio frequency signal to localize the position of the user.MethodsIn this paper, we examine the performance and usability of two computer-vision based systems and BLE-based system. The first system is computer-vision based system, called CamNav that uses a trained deep learning model to recognize locations, and the second system, called QRNav, that utilizes visual markers (QR codes) to determine locations. A field test with 10 blindfolded users has been conducted while using the three navigation systems.ResultsThe obtained results from navigation experiment and feedback from blindfolded users show that QRNav and CamNav system is more efficient than BLE based system in terms of accuracy and usability. The error occurred in BLE based application is more than 30% compared to computer vision based systems including CamNav and QRNav.ConclusionsThe developed navigation systems are able to provide reliable assistance for the participants during real time experiments. Some of the participants took minimal external assistance while moving through the junctions in the corridor areas. Computer vision technology demonstrated its superiority over BLE technology in assistive systems for people with visual impairments.

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Section: Related Workmentioning

confidence: 99%