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International Journal of Advances in Engineering & Scientific Research

INTELLIGENT SMART FOOTWEAR WITH AI-POWERED OBJECT DETECTION AND EMERGENCY ALERT SYSTEM FOR THE VISUALLY IMPAIRED

J.Sathishkumar, M.Dhivya, R. Lidiya & P. Sowmiya

Mr.J.Sathishkumar, Assistant Professor, Department of IT, Kongunadu College of Engineering and Technology, Trichy, Tamil Nadu, India.

Ms. M.Dhivya, Student, Department of IT, Kongunadu College of Engineering and Technology, Trichy, Tamil Nadu, India.

Ms. R. Lidiya, Student, Department of IT, Kongunadu College of Engineering and Technology, Trichy, Tamil Nadu

Ms. P. Sowmiya, Student, Department of IT, KongunaduCollege of Engineering and Technology, Trichy, Tamil Nadu

DOI : https://doi.org/ 10.5281/zenodo.19472344 Page No : 117-124

Published Online : 2026-04-08

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ABSTRACT

Blind people face a lot of difficulties in moving around safely and getting help in emergencies quickly when the environment keeps changing. Most of the current assistive devices do not have the ability to understand the environment intelligently and also cannot communicate reliably. This paper proposes an AI powered smart shoe system that brings together real time environmental sensing, vision-based perception and emergency notification using IoT. A small camera and ultrasonic sensors take pictures and measure the environment. Data processing is performed on an external computer using a YOLO based object detector, a Haar Cascade based face detector and OCR with text to speech conversion. Processed information is sent to an ESP32 microcontroller via UDP communication over a wireless link, and the user receives real time feedback through vibrations and buzzer alerts. During emergencies, location aware notifications are sent via Arduino IoT Cloud and internet-based SMS support is optional using cloud services. The prototype of such a system has been developed as a proof of concept and it has been tested for remote and instant monitoring, user feedback and obstacle detection functionalities that can help visually impaired users to be more mobile, independent and safe.

Keywords: Assistive Technology, Smart Footwear, Object Detection, YOLO, IoT, ESP32, Visually Impaired Navigation.

References:

[1] P. Xu, G. A. Kennedy, F. -Y. Zhao, W. -J. Zhang and R. Van Schyndel, "Wearable Obstacle Avoidance Electronic Travel Aids for Blind and Visually Impaired Individuals: A Systematic Review," in IEEE Access, vol. 11, pp. 66587-66613, 2023, doi: 10.1109/ACCESS.2023.3285396.

[2] F. A. Sharom, S. A. Che Kar, R. Abdullah, S. Mohamed and N. Ahmed, "Design and Implementation of an Arduino-Based Wearable Assistive System for Obstacle Detection in Blind Navigation," 2025 IEEE International Conference on Applied Electronics and Engineering (ICAEE), Shah Alam, Malaysia, 2025, pp. 1-6, doi: 10.1109/ICAEE65866.2025.11170895.

[3] A. S. Rao et al., "Wearable Assistive Device for Enhanced Navigation in Visually Impaired Individuals Using YOLO-Based Object Detection," 2025 Fifth International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT), Bhilai, India, 2025, pp. 1-7, doi: 10.1109/ICAECT63952.2025.10958989.

[4] H. Hamed and M. R. Khan, "AI-based Detection of Potholes Ahead of a Visually Impaired Person Using Ultrasonic Sensors Array and Camera for Blind Navigation," 2024 9th International Conference on Mechatronics Engineering (ICOM), Kuala Lumpur, Malaysia, 2024, pp. 448-453, doi: 10.1109/ICOM61675.2024.10652516.

[5] M. Z. Hasan, S. Sikder and M. A. Rahaman, "Real-Time Computer Vision Based Autonomous Navigation System for Assisting Visually Impaired People using Machine Learning," 2022 4th International Conference on Sustainable Technologies for Industry 4.0 (STI), Dhaka, Bangladesh, 2022, pp. 1-6, doi: 10.1109/STI56238.2022.10103268.

[6] K. S. Sharmila, D. L. N. Likitha, D. Masrath, D. H. Hruthika, A. N. Raji and B. Sruthi, "Real Time Object Recognition with Voice Guided Navigation for Visually Impaired using OpenCV," 2025 5th International Conference on Expert Clouds and Applications (ICOECA), Bengaluru, India, 2025, pp. 551-555, doi: 10.1109/ICOECA66273.2025.00100.

[7]P. Mohanraj, T. Rajasekar, N. Sivaelango, V. Sri Karthickraja and N. Vignesh, "Wearable Device for Visually Impaired using Deep Learning," 2024 3rd International Conference on Applied Artificial Intelligence and Computing (ICAAIC), Salem, India, 2024, pp. 348-352, doi: 10.1109/ICAAIC60222.2024.10575667.

[8] B. Jebaranjani, P. Venkadesh, A. Abhyshek Jose, A. Sakthibala, K. S. Dhayanidhi and S. Velumani, "YOLOv7-Based Intelligent System for Real-Time Object Detection and Assistive Navigation in Smart Accessibility Solutions using NLP Feedback (YOLO-AI)," 2025 8th International Conference on Circuit, Power & Computing Technologies (ICCPCT), Kollam, India, 2025, pp. 1981-1987, doi: 10.1109/ICCPCT65132.2025.11176785.

[9] S. K. S, A. Shanthi and L. Pavithra, "Deep Learning-Enabled Obstacle Detection and Navigation Aid for Visually Impaired Using YOLOv4-Tiny," 2025 International Conference on Sensors and Related Networks (SENNET) Special Focus on Digital Healthcare(64220), Vellore, India, 2025, pp. 1-6, doi: 10.1109/SENNET64220.2025.11136039.

[10] C. Selvarathi, R. Kannan, M. K, P. Pandiaraja, T. S. Venkateswaran and R. Arunraj, "Enhancing Accessibility for Visually Impaired on Integrating Object, Distance and Face Detection," 2024 8th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), Kirtipur, Nepal, 2024, pp. 1502-1507, doi: 10.1109/I-SMAC61858.2024.10714896

[11] M. Hemasri, C. Rupa and M. Yamini, "Virtual Circuited Smart Wearable Shoe for Real Time Navigation Assistance," 2025 International Conference on Information, Implementation, and Innovation in Technology (I2ITCON), Pune, India, 2025, pp. 1-6, doi: 10.1109/I2ITCON65200.2025.11210586.

[12] P. P, R. K. P, S. K, K. K, M. K and S. Radha, "Tracking and monitoring the safety of the child in the stroller," 2024 International Conference on Power, Energy, Control and Transmission Systems (ICPECTS), Chennai, India, 2024, pp. 1-5, doi: 10.1109/ICPECTS62210.2024.10780119.

[13] S. Saravanan, K. Muthumanickam, N. Subha and P. C. S. Mahesh, "Diagnosing Alzheimer Disease Using MRI Scan: A Deep Learning Approach," 2024 2nd International Conference on Sustainable Computing and Smart Systems (ICSCSS), Coimbatore, India, 2024, pp. 1047-1052, doi: 10.1109/ICSCSS60660.2024.10624909

[14] P. P, K. K, R. K. P, C.Ushapriya, P. C. S. Mahesh and M. K, "Assessing Secure Cloud Information Sharing Through Authentication and Encoded Indexing," 2024 8th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), Kirtipur, Nepal, 2024, pp. 1030-1037, doi: 10.1109/I-SMAC61858.2024.10714840

[15] Pandiaraja, P., Muthumanickam, K. (2022). Convolutional Neural Network-Based Approach to Detect COVID-19 from Chest X-Ray Images. In: Agrawal, D.P., Nedjah, N., Gupta, B.B., Martinez Perez, G. (eds) Cyber Security, Privacy and Networking. Lecture Notes in Networks and Systems, vol 370. doi: 10.1007/978-981-16-8664-1_21

[16] Bharathi, V., Monikavishnuvarthini, A., Dhakne, A., & Preethi, P. (2023). AI based elderly fall prediction system using wearable sensors: A smart home-care technology with IOT. Meas. Sens, 25, 100614.

[17] Preethi, P., Swathika, R., Kaliraj, S., Premkumar, R., &Yogapriya, J. (2024). Deep learning–based enhanced optimization for automated rice plant disease detection and classification. Food and Energy Security, 13(5), e70001.

[18] Ansari, S. A., & Zafar, A. (2023, March). A comprehensive study on video captioning techniques, benchmark datasets and QoS metrics. In 2023 10th International Conference on Computing for Sustainable Global Development (INDIACom) (pp. 1598-1603). IEEE.

[19] Avacharmal, R., Balakrishnan, A., Ranjan, P., Vandanapu, M. K., Mulukuntla, S., & Preethi, P. (2024, June). Leveraging reinforcement learning for advanced financial planning for effective personalization in economic forecasting and savings strategies. In 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT) (pp. 1-4). IEEE.

[20] Wajid, M. A., Ansari, S. A., Luqman, M., Siddiqui, M. K., & Wajid, M. S. (2025). GSR‐C2N: Graph Feature Extracted Spar‐Raven Optimized CNN Based Crypto Mining Framework. Concurrency and Computation: Practice and Experience, 37(15-17), e70146.

[21] Ansari, S. A., Ali, S., Luqman, M., & Ahmad, S. (2025, March). Deep Learning Enabled Secure IoT Module for Smart Agriculture in Diverse Environmental Conditions. In 2025 IEEE 14th International Conference on Communication Systems and Network Technologies (CSNT) (pp. 94-99). IEEE.

[22] Pandey, D., Jain, V., & Ansari, S. A. (2024, September). Adaptability of Blockchain in Wireless Sensor Networks: Challenges and Future Scope. In 2024 International Conference on Artificial Intelligence and Emerging Technology (Global AI Summit) (pp. 653-659). IEEE.

Cite this Article as: J.Sathishkumar, M.Dhivya, R. Lidiya & P. Sowmiya (2026), “intelligent smart footwear with AI-powered object detection and emergency alert system for the visually impaired”, International Journal of Advances in Engineering & Scientific Research, Volume 13, Issue 1, 2026, pp 117-124. DOI : https://doi.org/ 10.5281/zenodo.19472344

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