Navigating Independence: The Smart Walking Stick for the Visually Impaired

Kaushal, Rajanish Kumar; Pavan Kumar, T V V; N, Sharath; Parikh, Swapnil; L, Natrayan; Patil, Harshal

doi:10.1109/icmcsi61536.2024.00022

2024 5th International Conference on Mobile Computing and Sustainable Informatics (ICMCSI) 2024

DOI: 10.1109/icmcsi61536.2024.00022

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Navigating Independence: The Smart Walking Stick for the Visually Impaired

Rajanish Kumar Kaushal,

T V V Pavan Kumar,

Sharath N

et al.

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Smart Stick Navigation System for Visually Impaired Based on Machine Learning Algorithms Using Sensors Data

Gharghan,

Kamel,

Marir

et al. 2024

JSAN

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Visually Impaired People (VIP) face significant challenges in their daily lives, relying on others or trained dogs for assistance when navigating outdoors. Researchers have developed the Smart Stick (SS) system as a more effective aid than traditional ones to address these challenges. Developing and utilizing the SS systems for VIP improves mobility, reliability, safety, and accessibility. These systems help users by identifying obstacles and hazards, keeping VIP safe and efficient. This paper presents the design and real-world implementation of an SS using an Arduino Nano microcontroller, GPS, GSM module, heart rate sensor, ultrasonic sensor, moisture sensor, vibration motor, and Buzzer. Based on sensor data, the SS can provide warning signals to VIP about the presence of obstacles and hazards around them. Several Machine Learning (ML) algorithms were used to improve the SS alert decision accuracy. Therefore, this paper used sensor data to train and test ten ML algorithms to find the most effective alert decision accuracy. Based on the ML algorithms, the alert decision, including the presence of obstacles, environmental conditions, and user health conditions, was examined using several performance metrics. Results showed that the AdaBoost, Gradient boosting, and Random Forest ML algorithms outperformed others and achieved an AUC and specificity of 100%, with 99.9% accuracy, F1-score, precision, recall, and MCC in the cross-validation phase. Integrating sensor data with ML algorithms revealed that the SS enables VIP to live independently and move safely without assistance.

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Smart Stick Navigation System for Visually Impaired Based on Machine Learning Algorithms Using Sensors Data

Gharghan,

Kamel,

Marir

et al. 2024

JSAN

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

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Navigating Independence: The Smart Walking Stick for the Visually Impaired

Cited by 1 publication

References 16 publications

Smart Stick Navigation System for Visually Impaired Based on Machine Learning Algorithms Using Sensors Data

Smart Stick Navigation System for Visually Impaired Based on Machine Learning Algorithms Using Sensors Data

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