Indoor Localization for the Blind Based on the Fusion of a Metaheuristic Algorithm with a Neural Network Using Energy-Efficient WSN

Gharghan, Sadik Kamel; Al-kafaji, Rasha Diaa; Mahdi, Siraj Qays; Zubaidi, Salah L.; Ridha, Hussein Mohammed

doi:10.1007/s13369-022-07188-4

Cited by 8 publications

(3 citation statements)

References 96 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The system in [ 71 ] supports indoor localization targeting BVI individuals by fusing a metaheuristic algorithm with a Neural Network using energy-efficient wireless sensor networks. To optimize the performance of the Artificial Neural Network (ANN) and improve localization accuracy, the authors integrated the ANN with the following six different metaheuristic algorithms: the backtracking search algorithm (BSA), the crow search algorithm (CSA), the gravitational search algorithm (GSA), slime mould algorithm (SMA), the particle swarm optimization (PSO), and the multiverse optimizer-ANN (MVO).…”

Section: Resultsmentioning

confidence: 99%

Multi-Sensor Data Fusion Solutions for Blind and Visually Impaired: Research and Commercial Navigation Applications for Indoor and Outdoor Spaces

Theodorou

Tsiligkos

Μηλιώνης

2023

Sensors

View full text Add to dashboard Cite

Several assistive technology solutions, targeting the group of Blind and Visually Impaired (BVI), have been proposed in the literature utilizing multi-sensor data fusion techniques. Furthermore, several commercial systems are currently being used in real-life scenarios by BVI individuals. However, given the rate by which new publications are made, the available review studies become quickly outdated. Moreover, there is no comparative study regarding the multi-sensor data fusion techniques between those found in the research literature and those being used in the commercial applications that many BVI individuals trust to complete their everyday activities. The objective of this study is to classify the available multi-sensor data fusion solutions found in the research literature and the commercial applications, conduct a comparative study between the most popular commercial applications (Blindsquare, Lazarillo, Ariadne GPS, Nav by ViaOpta, Seeing Assistant Move) regarding the supported features as well as compare the two most popular ones (Blindsquare and Lazarillo) with the BlindRouteVision application, developed by the authors, from the standpoint of Usability and User Experience (UX) through field testing. The literature review of sensor-fusion solutions highlights the trends of utilizing computer vision and deep learning techniques, the comparison of the commercial applications reveals their features, strengths, and weaknesses while Usability and UX demonstrate that BVI individuals are willing to sacrifice a wealth of features for more reliable navigation.

show abstract

Section: Resultsmentioning

confidence: 99%

Multi-Sensor Data Fusion Solutions for Blind and Visually Impaired: Research and Commercial Navigation Applications for Indoor and Outdoor Spaces

Theodorou

Tsiligkos

Μηλιώνης

2023

Sensors

View full text Add to dashboard Cite

show abstract

“…In fact, up to 70% of individuals with visual impairments tend to avoid moving around independently in indoor spaces, perceiving shopping malls as one of the most challenging environments. When it is essential for them to go shopping, they must rely on getting help from sighted people, which not only undermines their confidence and independence, but also significantly affects their ability to gain more experience in carrying out indoor everyday activities [ 7 , 8 , 9 , 10 , 11 , 12 ].…”

Section: Introductionmentioning

confidence: 99%

The Aerial Guide Dog: A Low-Cognitive-Load Indoor Electronic Travel Aid for Visually Impaired Individuals

Zhang,

Pan,

Song

et al. 2024

Sensors

View full text Add to dashboard Cite

Most navigation aids for visually impaired individuals require users to pay close attention and actively understand the instructions or feedback of guidance, which impose considerable cognitive loads in long-term usage. To tackle the issue, this study proposes a cognitive burden-free electronic travel aid for individuals with visual impairments. Utilizing human instinctive compliance in response to external force, we introduce the “Aerial Guide Dog”, a helium balloon aerostat drone designed for indoor guidance, which leverages gentle tugs in real time for directional guidance, ensuring a seamless and intuitive guiding experience. The introduced Aerial Guide Dog has been evaluated in terms of directional guidance and path following in the pilot study, focusing on assessing its accuracy in orientation and the overall performance in navigation. Preliminary results show that the Aerial Guide Dog, utilizing Ultra-Wideband (UWB) spatial positioning and Measurement Unit (IMU) angle sensors, consistently maintained minimal deviation from the targeting direction and designated path, while imposing negligible cognitive burdens on users while completing the guidance tasks.

show abstract

“…In general, Human Activity Recognition (HAR) systems are categorized into radio frequency related, vision related, and wearable sensor related (Gharghan et al, 2022). In vision-related HAR systems, CV methods are utilized for distinguishing human actions from recorded images or videos.…”

Section: Introductionmentioning

confidence: 99%

Piece-Wise Linear Chaotic Mapping-based Beluga Whale Optimization Algorithm-based Indoor Activity Monitoring for Elderly and Visually Impaired Persons

Alzahrani,

Rizwanullah,

Osman

2023

Journal of Disability Research

View full text Add to dashboard Cite

Currently, the methods of mobile communications and Internet of Things (IoT) are designed to collect human and environmental data for various intelligent applications and services. Remote monitoring of disabled and elderly people living in smart homes is challenging. Localization and positioning in indoor surroundings need unique solutions. Moreover, positioning remains a crucial feature of any navigation system that assists visually impaired persons (VIPs) in mobility. Other indispensable features of a common indoor navigation system are obstacle avoidance, pathfinding, and abilities for user communication. In recent times, the arrival of smartphones, artificial intelligence, IoT, wearables, etc. makes it possible to devise indoor monitoring systems for smart homecare. Therefore, this study presents an Improved Beluga Whale Optimization Algorithm with fuzzy-based Indoor Activity Monitoring (IBWOA-FIMS) for elderly and VIPs. The presented IBWOA-FIMS technique mainly focused on the identification and classification of indoor activities of elderly and disabled people. To accomplish this, the IBWOA-FIMS technique employs an adaptive neuro fuzzy inference system (ANFIS) model for the indoor monitoring process. In order to improve the monitoring results of the IBWOA-FIMS technique, the IBWOA is used to adjust the parameters related to the ANFIS model. For illustrating the enhanced indoor monitoring results of the IBWOA-FIMS technique, a series of simulations were performed. The simulation values portrayed the betterment of the IBWOA-FIMS technique in terms of different metrics.

show abstract

Indoor Localization for the Blind Based on the Fusion of a Metaheuristic Algorithm with a Neural Network Using Energy-Efficient WSN

Cited by 8 publications

References 96 publications

Multi-Sensor Data Fusion Solutions for Blind and Visually Impaired: Research and Commercial Navigation Applications for Indoor and Outdoor Spaces

Multi-Sensor Data Fusion Solutions for Blind and Visually Impaired: Research and Commercial Navigation Applications for Indoor and Outdoor Spaces

The Aerial Guide Dog: A Low-Cognitive-Load Indoor Electronic Travel Aid for Visually Impaired Individuals

Piece-Wise Linear Chaotic Mapping-based Beluga Whale Optimization Algorithm-based Indoor Activity Monitoring for Elderly and Visually Impaired Persons

Contact Info

Product

Resources

About