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SNAVI: A Smart Navigation Assistant for Visually Impaired

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Intelligent Control, Robotics, and Industrial Automation (RCAAI 2022)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 1066))

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Abstract

Our lives are made easier by automated solutions based on the Internet of Things (IoT). Navigating from one place to another can be challenging for blind people. IoT can increase navigational confidence while simultaneously decreasing reliance on others. The goal is to make the device less bulky and to aid them with two ultrasonic sensors and a flame sensor, which will be cost-effective for blind people who can comfortably travel both indoors and outdoors with minimum sensor use. SNAVI: A Smart Navigation Assistant for the Visually Impaired might be molded into a stick for visually impaired persons so that they receive a notification through their headphones when a barrier is identified in front of them via two ultrasonic sensors, as well as the height of the obstacle. The obstruction might be stationary or moving, and the system can detect fire through a flame IR sensor and send voice alerts. This method helps vision-impaired people travel about with less stress.

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Acknowledgements

We would like to pay our gratitude to our Chancellor, Sri. Mata Amritanandamayi Devi is the guiding light and inspiration behind all our works toward societal benefit. We would also like to thank all the staff at Amrita Vishwa Vidyapeetham who have provided us the support and motivation in the completion of this work. This work would not have been possible without the infrastructure and support provided by the Discovery Labs, Department of Computer Science, Amrita Vishwa Vidyapeetham, Mysuru Campus.

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Authors and Affiliations

  1. Department of Computer Science, Amrita School of Computing, Amrita Vishwa Vidyapeetham, Mysuru Campus, Mysuru, India

    Madhu R Seervi & Adwitiya Mukhopadhyay

Authors
  1. Madhu R Seervi
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  2. Adwitiya Mukhopadhyay
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Corresponding author

Correspondence to Adwitiya Mukhopadhyay .

Editor information

Editors and Affiliations

  1. School of Engg., Computing and Math.,, University of Plymouth, Plymouth, UK

    Sanjay Sharma

  2. School of Electrical Sciences, Indian Institute of Technology Goa, Ponda, Goa, India

    Bidyadhar Subudhi

  3. Department of Mechatronics, Manipal Institute of Technology, Manipal, Karnataka, India

    Umesh Kumar Sahu

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Seervi, M.R., Mukhopadhyay, A. (2023). SNAVI: A Smart Navigation Assistant for Visually Impaired. In: Sharma, S., Subudhi, B., Sahu, U.K. (eds) Intelligent Control, Robotics, and Industrial Automation. RCAAI 2022. Lecture Notes in Electrical Engineering, vol 1066. Springer, Singapore. https://doi.org/10.1007/978-981-99-4634-1_70

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