A Sensing Framework for Indoor Spatial Awareness for Blind and Visually Impaired Users

Abstract

In this paper, we present Bluetooth low energy (BLE)-based sensing framework that provides real time spatial awareness for blind and visually impaired (BVI) users while navigating independently through large public venues. The proposed framework includes the following functionalities using only the received signal strength indicator obtained from the BLE sensors: 1) determining the location of the user, 2) estimating the user's moving direction, and 3) detecting the proximity of landmarks next to the user. We evaluate these functionalities individually. Moreover, we incorporate the proposed framework in PERCEPT indoor navigation system and test it with BVI users in a large public venue. Testing results show that the location, moving direction, and landmark proximity computed by the framework, although not very accurate, provide sufficient information to enable BVI users to independently navigate in large indoor venues. This conclusion aligns with Nobel Prize winning findings that confirm the spatial nature of the entorhinal-hippocampal system and the existence of a positioning system in the brain.

Validation and Optimization Framework for Indoor Navigation Systems Using User Comments in Spatial-Temporal Context

“…Moreover, looking at area localization provides sufficient information to enable users to navigate in large indoor venues independently. This conclusion aligns with Nobel Prize winning findings that confirm the spatial nature of the entorhinal-hippocampal system and the existence of a positioning system in the brain as described in [41].…”

“…We developed an optimal BLE tag deployment scheme which minimizes the number of tags while ensuring that every zone in the venue is covered by at least three tags. This deployment algorithm along with the real-time localization algorithm is reported in [41].…”

An ARCore Based User Centric Assistive Navigation System for Visually Impaired People

“…Methods using direct sensing and dead reckoning [7] are no longer qualified options. Yang [8] proposed a Bluetooth RSSI-based sensing framework to localize users in large public venues. The particle filter was applied to localize the subject.…”

Sistema de Localização em Ambientes Internos usando Wi-Fi e algoritmo K-NN

“…Na Figura 6 o sistema ILS proposto alcançou o menor valor para o erro de localização RMSE com valor de desvio calculado igual a 2,87 metros na função média com o parâmetro ̂= 1 superando alguns trabalhos na literatura(ex. erro médio de localização RMSE de 6,7283m [17]).…”

“…Em pesquisas da literatura existem propostas que endereçam soluções para sistemas de localização em ambientes internos (Indoor Location System -ILS) baseado em tecnologias como RFID (Radio Frequency Identification), UWB (Ultra Wide Band) [5] [6], infravermelho, Wi-Fi (Wireless Fidelity) [7], Bluetooth [8], NFC (Near Field Communication) [9] [10], sinais magnéticos, processamento de imagens e sinais sonoros [11] e tecnologias combinadas [12]. Nestas pesquisas é possível destacar algumas questões a serem melhoradas em sistemas ILSs tais como a complexidade na instalação, configuração e utilização do sistema além do erro médio de localização que pode afetar a acurácia do sistema.…”