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Home / Archives / Volume-6 / Issue-3 / Article-2

Volume - 6 | Issue - 3 | september 2024

VocalVision: Smart Wheelchair Maintenance with Pressure Sensors and Machine Learning
Sujithra G.  , Chinnakotla Sreeharsha, Kondeti Sai Nikhitha, Sangavi S.
Pages: 210-221
Cite this article
G., Sujithra, Chinnakotla Sreeharsha, Kondeti Sai Nikhitha, and Sangavi S.. "VocalVision: Smart Wheelchair Maintenance with Pressure Sensors and Machine Learning." Journal of Electrical Engineering and Automation 6, no. 3 (2024): 210-221
Published
11 July, 2024
Abstract

The Vocal Vision system introduces an innovative approach to enhancing electric wheelchair maintenance and control. It utilizes a network of sensors embedded within the wheelchair's wheels to gather real-time data on tire pressure, temperature, tread wear, and alignment. This data is wirelessly transmitted to a central control unit. Advanced algorithms, incorporating machine learning and predictive analytics, analyze the data to detect irregularities and predict maintenance needs. Users can control direction, speed, and perform complex maneuvers with precision using voice commands and eye gestures. The wheelchair integrates OpenCV for eye gesture recognition and Google Speech Recognition API for voice commands, enabling intuitive control methods. This proposed method introduces a new assistive technology for individuals with disabilities, leveraging cutting-edge technologies.

Keywords

Pressure Sensor Machine Learning Predictive Analytics Sustainability Cost-Efficiency

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