Smart Cane: Better Walking Experience for Blind People

Sharma, Tushar; Nalwa, Tarun; Choudhury, Tanupriya; Satapathy, Suresh Chand; Kumar, Praveen

doi:10.1109/cine.2017.22

Cited by 13 publications

(2 citation statements)

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“…Sharma et al [8] in their paper "Smart Cane: Better Walking Experience for Blind People" have used two types of sensors, the infra-red and ultrasonic sensors. There's a water sensor at the base of the smart cane that detects and dodges puddles.…”

Section: Literature Surveymentioning

confidence: 99%

Guiding and Navigation for the Blind using Deep Convolutional Neural Network Based Predictive Object Tracking

Alisetti,

Purushotham,

Mahtani

2019

IJEAT

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Indoor and outdoor Navigation is a tough task for a visually impaired person and they would most of the time require human assistance. Existing solutions to this problem are in the form of smart canes and wearable. Both of which use sensors like on - board proximity and obstacle detection, as well as a haptic or auditory feedback system to warn the user of stationary or incoming obstacles so that they do not collide with any of them as they move. This approach has many drawbacks as it is not yet a stand - alone reliable device for the user to trust when navigating, and when frequently triggered in crowded areas, the feedback system will confuse the user with too many requests resulting in loss of actual information. Our Goal here is to create a Personalized assistant to the user, which they can interact naturally with their voice to mimic the aid of an actual human assistance while they are on the move. It works by using its object detection module with a high reliability training accuracy to detect the boundaries of objects in motion per frame and once the bounding box crosses the threshold accuracy, recognize the object in the box and pass the information to the system core, where it verifies if the information needed to be passed onto the user or not, if yes it passes the converted speech information to the voice interaction model. The voice interaction model is consent-based, it would accept and respond to navigation queries from the user and will intelligently inform them about the obstacle which needs to be avoided. This ensures only the essential information in the form of voice requests is passed onto the user, which they can use to navigate and also interact with the assistant for more information.

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Section: Literature Surveymentioning

confidence: 99%

Guiding and Navigation for the Blind using Deep Convolutional Neural Network Based Predictive Object Tracking

Alisetti,

Purushotham,

Mahtani

2019

IJEAT

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“…• Ultraviolet (UV) radiation monitoring and alerts module; As shown in Table 1, the initiatives listed present descriptions, functional models, and an adequate representation of some IoT technologies. Concepts and functionalities have already been addressed in a vast number of initiatives by several authors [25][26][27][28][29][30][31], and they are increasingly customized. However, the operation and production logic does not change, the observed phenomena remain the same, and each component's cost is extremely high, making the prototypes not only heavy or expensive to implement but also challenging to reproduce.…”

Section: Introductionmentioning

confidence: 99%

Assistive Devices: Technology Development for the Visually Impaired

Garay

Zea-Vargas

Huallpa

et al. 2021

Designs

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Technology has been contributing significantly to the development of assistive devices for disabled persons (DPs). Many of these devices aim to assist people who are blind or visually impaired, providing them with friendlier ways to interact with their surroundings (obstacles, objects, and navigation). However, the high cost of these devices makes it difficult for DPs to purchase them. The development of an assistive device kit to be used by the visually impaired in controlled environments (indoor) or urban spaces (outdoor) is presented in this work with a didactic and detailed approach. This low-cost kit (USD 50 per device) consists of a Smart Cane, Smart Cap, and Smart Glove. The methodology addressed aims to support and encourage the reproduction, customization, and manufacture of new assistive devices with low cost and wide applicability. The devices are functional, benefit usability, and, due to the characteristics of the project and the materials used in their construction, do not impact the ergonomics of the visually impaired or disabled person who may use these devices. The devices that integrate the assistive kit can be used independently or combined. In addition to having detection, fall-control, navigation, and real-time tracking functions, they are independent of additional local infrastructure for their use.

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A Smart Cane to Help the Blind People Walk Confidently

Zhou

2018

IOP Conf. Ser.: Mater. Sci. Eng.

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Smart Cane: Better Walking Experience for Blind People

Cited by 13 publications

References 1 publication

Guiding and Navigation for the Blind using Deep Convolutional Neural Network Based Predictive Object Tracking

Guiding and Navigation for the Blind using Deep Convolutional Neural Network Based Predictive Object Tracking

Assistive Devices: Technology Development for the Visually Impaired

A Smart Cane to Help the Blind People Walk Confidently

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