Smartphone Apps of Obstacle Detection for Visually Impaired and its Evaluation

Shimakawa, Manabu; Matsushita, Kosei; Taguchi, Issei; Okuma, Chiharu; Kiyota, Kimiyasu

doi:10.1145/3325291.3325381

Cited by 14 publications

(7 citation statements)

References 4 publications

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“…It establishes obstacle relevance and danger level to notify the user accordingly. Shimakawa et al [13] can detect 4 categories of dangers (stairs, bicycle, crosswalk, sidewalk) by using CNN for obstacle detection. Abhinash et al [14] analyse 12 systems by comparing different CNN techniques and conclude that CNN is the most efficient deep learning technique for object detection and recognition as well as navigation systems.…”

Section: Object Recognition Obstacle Detection and Avoidance Navigati...mentioning

confidence: 99%

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Indoor Objects Detection and Recognition for Mobility Assistance of Visually Impaired People with Smart Application

Megavath

Indra

Al-Rasheed

et al. 2023

Preprint

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Visually impaired people are individuals who have a partial or complete loss of vision. This condition can vary in severity, from mild to profound, and can be caused by a variety of factors, including genetics, injury, illness, or aging. It's important to note that visually impaired people are a diverse group with different needs and abilities, and they should be treated with respect and given equal access to opportunities and resources. Smart applications can be extremely helpful for visually impaired people by providing them with information and assistance in navigating their environment. Moreover, can greatly enhance the independence and quality of life for visually impaired people. Many applications have been proposed with individual features set and other concerns due to are expensive, difficult to use, less affordable, less accessible and are an overhead while travelling. To solving these issues, in this paper we design an android Application - Smart Vision (SV) to aid the Visually Impaired people in every possible realm of daily pursuits like for their diurnal regressions around the house/office place, taking notes of their daily affairs, recognizing the people around, identifying the colours etc. Smart Vision would enable the visually impaired to have a better user experience as the whole working of the application is divided into 6 modules - Obstacle Avoidance and Navigation Module, Digital Assistant Module, Scene Description Module, Light Detection Module, Colour Detection Module and Face Detection Module, which can be easily selected by giving a single voice command. Smart Vision is exclusively designed by keeping the memory and battery constraints of the application within permissible limits ensuring the reliability, portability and cost effectiveness to the grieved end user to make life beautiful for them. Smart Vision enables detection of the desired object with a 90% accuracy, face recognition with an accuracy of 87%, colour detection with an approximate accuracy of 75%, Digital assistant module accuracy as 91% and light detection (for light and dark intensities) minimum accuracy is 82%. It has been interpreted that the Average Response Time is under 3 seconds which makes it a high-speed device because the Raspberry pi is used for connecting the components which reduces the transit time. Finally, a comparative study has been done with the existing topologies and it is so found that the Smart Vision is applicable for both indoor and outdoor environments.

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Section: Object Recognition Obstacle Detection and Avoidance Navigati...mentioning

confidence: 99%

“…Analysis/Accuracy [2], [13], [14] CNN Obstacle recognition, obstacle avoidance, indoor and outdoor navigation, and real-time location sharing.…”

Section: Reference Technique Implementedmentioning

confidence: 99%

Indoor Objects Detection and Recognition for Mobility Assistance of Visually Impaired People with Smart Application

Megavath

Indra

Al-Rasheed

et al. 2023

Preprint

View full text Add to dashboard Cite

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“…Kingdom of Saudi Arabia → Riyadh (5). Czech Republic → Prague Task 2 IC.R (Digital IC recorder) → "Touch Talker" (5 countries) (6). State of Israel → Jerusalem (7).…”

Section: [First Time Trial]mentioning

confidence: 99%

“…In response to such requests from special support schools and medical institutions in each prefecture, the faculty members of 13 NCTs took the lead in establishing the National KOSEN Assistive Technology (AT) Development Network (KOSEN-AT Net). In this network, each technical college has developed various devices and applications for special needs [5][6][7][8][9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Effects of Social Implementation Education for Assistive Device Engineers at NIT (KOSEN) through the Development of a Digital Reading Device for the Visually Impaired

Kiyota

Ishibashi

Shimakawa

et al. 2022

Sensors

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Assistive technology (AT) is any item, device, software, or product system used to enhance, maintain, or improve the functional abilities of people with disabilities. There are many people with disabilities in the world, including the visually impaired, the hearing impaired, and the physically impaired. We established the National KOSEN Support Equipment Development Network (KOSEN-AT) with technical college faculty members 10 years ago to assist these disabled and elderly people. However, Japan is facing the challenge of a rapidly aging society, and the digital transformation of assistive device development for people with disabilities has not been adequately addressed. A major reason for this is the lack of engineers in Japan who can develop products with an understanding of the needs of people with disabilities and the elderly. In this paper, we describe a new initiative of the GEAR 5.0 program, a practical engineer education program that will enable the development of assistive devices for the physically challenged and the elderly, which started in 2020 at the National Institute of Technology in Japan. We believe that it is necessary to educate technicians not only with conventional specialized skills, but also with a full understanding of the concept of disability and basic skills in assistive technology. Next, we developed “Touch Talker”, a digital text reading system for the visually impaired. As a part of the GEAR 5.0 program, we conducted an evaluation experiment in which students from a technical college experienced visual impairment in the same blindfolded environment as visually impaired people to evaluate the developed assistive device. To verify its importance, we developed a digital text-to-speech system for the visually impaired, “Touch Talker”, as part of the GEAR 5.0 program. We thought that by conducting evaluation experiments in the same blindfolded environment as visually impaired people, we could make technical college students aware of the difficulties of operating digital devices due to visual impairment. The results of the experiment showed that the developed “Touch Talker” was effective for both the visually impaired group and the blindfolded technical college student group. The evaluation results also showed a similar trend, confirming that the evaluation by blindfolded technical college students is effective for the development of assistive devices for the visually impaired. In addition, the technical college students who participated in the evaluation experiment were able to understand the difficulty of operating digital devices by experiencing visual impairment. It was suggested that the perspective of the people involved is important in the development of assistive devices.

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“…It will be helpful that some tool to detect properly the obstacles in front of their walking. We developed smartphone apps that detect obstacles using CNN (Convolutional Neural Network), a kind of Deep Learning (2)(3) . Since this method only determines whether there is an obstacle or not on the image, it is not possible to know where the obstacle is.…”

Section: Introductionmentioning

confidence: 99%

Smartphone Apps for Visually Impaired that Detects Obstacles and Obtains those Distances

Shimakawa

Minami

Okuma

et al. 2021

The Proceedings of the 9th IIAE International Conference on Industrial Application Engineering 2020

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The authors have been developing a smartphone app to support for visually impaired walking when they go out. This app has functions to detect obstacles from RGB camera image that hinder walking and to alert dangerous situation to the visually impaired. It uses CNN, a kind of deep learning technique, to detect obstacles, but it can detect only one obstacle from the image. Now we are trying to implement a multiple obstacles detect function into this app. This paper deals with a method to obtain the distance to the obstacles detected from the multiple obstacles detection.

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Smartphone Apps of Obstacle Detection for Visually Impaired and its Evaluation

Cited by 14 publications

References 4 publications

Indoor Objects Detection and Recognition for Mobility Assistance of Visually Impaired People with Smart Application

Indoor Objects Detection and Recognition for Mobility Assistance of Visually Impaired People with Smart Application

Effects of Social Implementation Education for Assistive Device Engineers at NIT (KOSEN) through the Development of a Digital Reading Device for the Visually Impaired

Smartphone Apps for Visually Impaired that Detects Obstacles and Obtains those Distances

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