Paper ID:
IJSDIP_2026_VOLUME 14_ISSUE 1_93-98
Author's Name:
Sneha kumari , Ritesh kumar, Uttam kumar pandey
Volume:
14
Issue:
Issue 1
Year:
2026
Pages:
93-98
Abstract
Independent mobility and safety are greatly impacted by visual impairment. Conventional white canes don't have intelligent feedback or environmental awareness, but they can detect obstacles. In order to help visually impaired people, this research paper describes the design and implementation of an AI-based smart stick that is integrated with EarPods. The system recognizes objects, detects obstacles, and provides real-time voice feedback via EarPods using artificial intelligence, sensors, and audio guidance. The suggested solution is affordable, portable, and improves user independence, safety, and navigation.
Keywords
Smart Stick, Obstacle Detection, Artificial Intelligence, Visually Impaired, Earbuds, Assistive Technology.
References
1. Shoval, S., & Borenstein, J. (1998). The Guide Cane: A computerized travel aid for the active guidance of blind pedestrians (Proceedings of the IEEE International Conference on Robotics and Automation). IEEE.
2. 2.Munteanu, L., & Ionel, C. (2016). Smart Cane for the Blind based on Raspberry Pi. In Proc. IEEE CSSE (pp. 151-157). IEEE.
3. 3.Ni, C. C. (2019). Floating Blade: Electronic Cane with Data Logging and Object Identification. IEEE Transactions on Human-Machine Systems, 49(3), 268-275.
4. Akila, M., & Rajasekar, S. (2018). Smart Walking Stick for Visually Impaired People Using Ultrasonic Sensor and Arduino. International Journal of Innovative Research in Science, Engineering and Technology, 7(4), 4121–4126.
5. Sharma, K., & Gupta, P. (2020). IoT-Based Smart Walking Stick for Visually Impaired Individuals. International Journal of Engineering Research & Technology (IJERT), 9(7), 876–880.
6. U-blox AG. (2018). NEO-6M GPS Module Hardware Integration Manual. U-blox Documentation. Retrieved from https://www.u-blox.com
7. R. Tapu, B. Mocanu, T. Zaharia, 'Wearable Assistive Devices for Visually Impaired: A Survey,' Sensors, 2019.
8. B. Mandal, L. Li, 'Smart Cane for the Visually Impaired Using Computer Vision and IoT,' IEEE Transactions, 2020.
9. Arduino & Raspberry Pi Official Documentation.
10. TensorFlow Lite for Microcontrollers (Google Developers).
