Real-Time Obstacle Detection and GPS Tracking Assistive Device for Visually Impaired Using Iot

Authors

Meravath Chintu

Department of Electronics & Communication Engineering, Guru Nanak Institutions Technical Campus (India)

M Sai Narasimha

Department of Electronics & Communication Engineering, Guru Nanak Institutions Technical Campus (India)

Kethiboina Naveen

Department of Electronics & Communication Engineering, Guru Nanak Institutions Technical Campus (India)

Dr. B. Anitha

Associate Professor, Department of Electronics & Communication Engineering, Guru Nanak Institutions Technical Campus (India)

Article Information

DOI: 10.51244/IJRSI.2026.1303000190

Subject Category: Information Technology

Volume/Issue: 13/3 | Page No: 2211-2220

Publication Timeline

Submitted: 2026-03-31

Accepted: 2026-04-06

Published: 2026-04-14

Abstract

Mobility and environmental awareness remain serious challenges for visually impaired individuals navigating daily life without external assistance. Conventional aids such as white canes provide only limited ground-level protection and are incapable of detecting overhead obstacles, tracking the user's outdoor location, or notifying remote caregivers of hazards. This paper presents the design, implementation, and hardware testing of a low-cost, IoT-enabled multifunctional assistive device built around the Raspberry Pi Pico W microcontroller. The system integrates an HC-SR04 ultrasonic sensor for obstacle detection up to 400 cm, an infrared proximity sensor for close range object sensing below 30 cm, a NEO-6M GPS module for real-time outdoor positioning, a 0.96-inch OLED display for local status feedback, an electromagnetic buzzer for differentiated audio alerting, a relay module for external device control, and a ULN2003-driven stepper motor and DC motor actuator subsystem for mechanical feedback. The Pico W's onboard 802.11n Wi-Fi transmits GPS coordinates and sensor states to the Thing Speak IoT cloud platform, giving caregivers real-time visibility of the user's location and device condition through a standard web browser. Firmware is written in Micro Python and developed using the Thonny IDE. Hardware testing confirms obstacle detection accuracy of 98.6%, GPS positioning accuracy of 2.3 m in open-sky conditions, Thing Speak upload latency of 1.74 seconds, and a total component cost of approximately ₹2,500, more than 96% lower than commercially available smart assistive devices.

Keywords

Assistive Device, Visually Impaired, Internet of Things (IoT), Raspberry PI Pico W, Ultrasonic Sensor, IR Sensor, GPS Module, Thing Speak Cloud Platform, Obstacle Detection.

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References

1. World Health Organization, "World Report on Vision," WHO Press, Geneva, Switzerland, 2019. [Google Scholar] [Crossref]

2. K. Bhowmick and M. K. Hazarika, "An insight into assistive technology for the visually impaired and blind people: State-of-the-art and future trends," Journal on Technology and Persons with Disabilities, vol. 5, pp. 226–243, 2017. [Google Scholar] [Crossref]

3. MathWorks, "ThingSpeak for IoT Projects — Documentation," [Online]. Available: [Google Scholar] [Crossref]

4. https://thingspeak.com/docs, accessed Mar. 2025. [Google Scholar] [Crossref]

5. J. Madake, S. Bhatlawande, A. Solanke, and S. Shilaskar, "A qualitative and quantitative analysis of research in mobility technologies for visually impaired people," IEEE Access, vol. 11, pp. 82496–82520, 2023, doi: 10.1109/ACCESS.2023.3291074. [Google Scholar] [Crossref]

6. S. Bhatlawande, J. Mahadevappa, J. Mukhopadhyay, M. Biswas, D. Das, and S. Nanda, "Design and development of ultrasonic spectacles and waist-belt for visually impaired and blind persons," Proc. Inst. Mech. Eng. Part H, vol. 228, no. 1, pp. 3–13, Jan. 2014. [Google Scholar] [Crossref]

7. J. Liao, S. Deng, Y. Liu, and Y. Chen, "GPS-based audio navigation system for visually impaired pedestrians," in Proc. IEEE Conf. Ind. Electron. Appl. (ICIEA), Singapore, 2018, pp. 534–538. [Google Scholar] [Crossref]

8. N. Adnan, S. M. Nordin, and M. A. Bahruddin, [Google Scholar] [Crossref]

9. "IoT-based caregiver notification system for elderly and visually impaired individuals using GPS and cloud platforms," J. Telecommun. Electron. Comput. Eng., vol. 10, no. 2, pp. 67–73, 2018. [Google Scholar] [Crossref]

10. K. Manikandan and T. Manikandan, "IoT-based health monitoring and alert system using Raspberry Pi and ThingSpeak platform," Int. J. Adv. Res. Electr. Electron. Instrum. Eng., vol. 7, no. 4, pp. 2133–2139, Apr. 2018. [Google Scholar] [Crossref]

11. R. Bharani and B. Ramkumar, "Smart cane with obstacle sensing and GPS tracking for visually impaired people," in Proc. IEEE Int. Conf. Intell. Syst. Control (ISCO), Coimbatore, India, 2017, F. Ashiq, M. Asif, M. B. Ahmad, S. Zafar, K. Masood, T. Mahmood, M. T. Mahmood, and I. H. Lee, "CNN-based object recognition and tracking system to assist visually impaired people," IEEE Access, vol. 10, pp. 14819–14834, 2022. [Google Scholar] [Crossref]

12. u-blox AG, "NEO-6 u-blox 6 GPS Modules Data Sheet," Rev. 6, Thalwil, Switzerland, 2011. [Google Scholar] [Crossref]

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