Smartphone-based floor detection in unstructured and structured environments

Adorno, Jorge; DeLaHoz, Yueng; Labrador, Miguel A.

doi:10.1109/percomw.2016.7457136

Cited by 3 publications

(1 citation statement)

References 7 publications

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“…A considerable number of elderly people may fall and become injured because of aging. In this scope, a smartphone-based floor detection module for structured and unstructured environments that enables the identification of floors in front of the user is proposed in [78]. Structured environments are the areas that have a well-defined shape, and unstructured environments are the area with the unknown shape.…”

Section: Computer Vision-based Positioning and Localization Systemsmentioning

confidence: 99%

Indoor positioning and wayfinding systems: a survey

Kunhoth

Karkar

Al‐Maadeed

et al. 2020

Hum. Cent. Comput. Inf. Sci.

191

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Navigation systems help users access unfamiliar environments. Current technological advancements enable users to encapsulate these systems in handheld devices, which effectively increases the popularity of navigation systems and the number of users. In indoor environments, lack of Global Positioning System (GPS) signals and line of sight with orbiting satellites makes navigation more challenging compared to outdoor environments. Radio frequency (RF) signals, computer vision, and sensor-based solutions are more suitable for tracking the users in indoor environments. This article provides a comprehensive summary of evolution in indoor navigation and indoor positioning technologies. In particular, the paper reviews different computer vision-based indoor navigation and positioning systems along with indoor scene recognition methods that can aid the indoor navigation. Navigation and positioning systems that utilize pedestrian dead reckoning (PDR) methods and various communication technologies, such as Wi-Fi, Radio Frequency Identification (RFID) visible light, Bluetooth and ultra-wide band (UWB), are detailed as well. Moreover, this article investigates and contrasts the different navigation systems in each category. Various evaluation criteria for indoor navigation systems are proposed in this work. The article concludes with a brief insight into future directions in indoor positioning and navigation systems.

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Section: Computer Vision-based Positioning and Localization Systemsmentioning

confidence: 99%