Sound and touch based smart cane: Better walking experience for visually challenged

Megalingam, Rajesh Kannan; Nambissan, Aparna; Thambi, Anu; Gopinath, Aravind; Megha, Kumari

doi:10.1109/ihtc.2014.7147543

Cited by 26 publications

(2 citation statements)

References 3 publications

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“…Trials found in Literature include the GPS-included sensor-filled cane from Agrawal and Gupta [10]; circuitry-concentrated cane proposal from Damdhare and Sakhare [11]; proposal based on ultrasonic sensors by Dey et al [12]; voice-command by Koley and Mishra [13]; haptic alerts for obstacles by Wang and Kuchenbecker [14]; low cost approach by Kumar et al [15]; electronic sensors by Mahmud et al [16]; overall improved smart-cane by Maidenbaum et al [17] that would offer object type and detection with artificial intelligence (A.I.) by Mavarkar and Mundargi [18]; sound and touch input from Megalingam et al [19], Infrared sensor-based by Nada et al [20], Camera object detection with A.I. by Narayani et al [21]; acoustic obstacle detection feedback by Rodríguez et al [22]; Internet of Things approach by Sharmila [23] that, in a similar way to the Google Lens, requires wearing glasses and using the walking cane; a belt-like obstacle-avoidance system with A.I.…”

Section: Introductionmentioning

confidence: 99%

Smart Cane Developed with DFSS, QFD, and SDE for the Visually Impaired

et al. 2021

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This study shows an application of the Design for Six Sigma (DFSS) Methodology in the field of medical engineering. This research aims to demonstrate the application of a systematic design approach in the development of the “Ocane”, an innovative concept of smart cane for visually impaired patients which was thought of in answer to the end user’s needs, deploying an easy to transport, locate, and adjust element with ultrasonic sensors and tactile feedback. DFSS is an analytical design methodology meant to organize project workflow in a sequence of specific steps. Other standardized design procedures such as Quality Function Deployment (QFD) and Stylistic Design Engineering (SDE) have been used to support DFSS in terms of targeting customer requirements and focusing on aesthetics for ergonomics analysis, respectively. First, the QFD process is introduced and applied to gather the final customer needs, completing the analysis with benchmarking and similar-thought products on the market. Afterwards, a description of the DFSS methodology and application to the case study was deployed. Thereafter, the SDE procedure is exposed by identifying the “Ocane” concept and development, and moving towards the completion of an inventive product with a creative design and careful attention to visually impaired clients’ requirements.

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Section: Introductionmentioning

confidence: 99%

Smart Cane Developed with DFSS, QFD, and SDE for the Visually Impaired

et al. 2021

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“…A. Sfiiyan et al, [6] designed a fast-response smart cane equipped with infrared, ultrasonic and moisture sensors and controlled it with an 18F46K80 microcontroller. R. K. Megalingam [7] supported his smart cane with heat, obstacle detection, and Bluetooth modules; An Arduino module operated the system. The ultrasonic sensor calculated the distance and buzzed the user in case of danger.…”

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confidence: 99%

An Integrated IoT Smart Cane for the Blind and Visually Impaired Individuals

Abuelmakarem,

Abuelhaag,

Raafat

et al. 2024

SVU-International Journal of Engineering Sciences and Applicati

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The advancement of Internet of Things (IoT) technologies has paved the way for innovative solutions in various domains, including assisting visually impaired and blind (VIB) individuals. Smart canes with IoT capabilities enhance safety by providing real-time information about the user's surroundings, enabling them to avoid obstacles and potential hazards. This scientific article develops an intelligent cane for visually impaired and blind (VIB) people integrated with an IoT system. This smart device promotes independence and confidence for VIB individuals. The smart cane was designed using SolidWorks 3D modelling software. It detects water, obstacles, and fire. The IoT smart cane employs ultrasonic sensors to help VIB users go up and down the stairs and detect obstacles. The system is controlled via the Arduino module. The cane automatically notifies VIB users when it detects hazards. The family tracks the individual through the fixed MCU Node that sends the navigation to the family smartphone on the Blynk application. The system is calibrated versus different objects, and the blind location is sent to the family successfully through the Blynk mobile Application.

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