Vision stick: An intelligent assistive device to support soldier mobility in visually impaired conditions
DOI:
https://doi.org/10.58524/app.sci.def.v3i2.662Keywords:
AI Vision, Assistive Technology, Dual-Mode Operation, Ultrasonic Sensors, Visually Impaired, Vision StickAbstract
The Vision Stick is an innovative assistive device designed to enhance the mobility and independence of visually impaired individuals by integrating AI-powered vision models and ultrasonic sensors into a traditional white cane. Visually impaired individuals face significant challenges in navigating their surroundings, often relying on conventional mobility aids that lack advanced environmental awareness. To address this, the Vision Stick operates in two modes: an online AI vision mode and an offline ultrasonic mode. In online mode, a camera and AI algorithms analyze the surroundings, providing real-time voice descriptions of obstacles, landmarks, and hazards, improving navigation and safety. In offline mode, an ultrasonic sensor detects nearby objects and provides audio feedback, ensuring uninterrupted guidance without internet access. The device retains the familiar structure of a white cane while incorporating lightweight embedded components for ease of use. By combining AI-driven environmental awareness with ultrasonic obstacle detection, the Vision Stick enhances safety, confidence, and autonomy for visually impaired individuals in diverse environments.References
Ahmed, S. H., Hu, S., & Sukthankar, G. (2023). The potential of vision‐language models for content moderation of children's videos. Proceedings of the 2023 International Conference on Machine Learning and Applications (ICMLA), 1237–1241. https://doi.org/10.1109/ICMLA58977.2023.00186
Abdel‐Rahman, A. B., et al. (2023). A smart blind stick with object detection, obstacle avoidance, and IoT monitoring for enhanced navigation and safety. Proceedings of the 2023 11th International Japan‐Africa Conference on Electronics, Communications, and Computations (JAC-ECC), 21–24. https://doi.org/10.1109/JAC-ECC61002.2023.10479623
Abir, W. A., Tosher, S. H., Nowrin, N. A., Hasan, M. Z., & Rahaman, M. A. (2023). A computer vision and IoT based smart stick for assisting vision-impaired people. Proceedings of the 2023 5th International Conference on Sustainable Technologies for Industry 5.0 (STI), 1–6. https://doi.org/10.1109/STI59863.2023.10465144
Agrawal, M. P., & Gupta, A. R. (2018). Smart stick for the blind and visually impaired people. Proceedings of the 2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT), 542–545. https://doi.org/10.1109/ICICCT.2018.8473344
Ashrafuzzaman, M., Saha, S., Uddin, N., Saha, P. K., Hossen, S., & Nur, K. (2021). Design and development of a low-cost smart stick for visually impaired people. Proceedings of the 2021 International Conference on Science & Contemporary Technologies (ICSCT), 1–6. https://doi.org/10.1109/ICSCT53883.2021.9642500
Chen, H., Wang, J., & Meng, M. Q.-H. (2022). Kinova Gemini: Interactive robot grasping with visual reasoning and conversational AI. Proceedings of the 2022 IEEE International Conference on Robotics and Biomimetics (ROBIO), 129–134. https://doi.org/10.1109/ROBIO55434.2022.10011896
Christopherson, P. S., Eleyan, A., Bejaoui, T., & Jazzar, M. (2022). Smart stick for visually impaired people using Raspberry Pi with deep learning. Proceedings of the 2022 International Conference on Smart Applications, Communications and Networking (SmartNets), 1–6. https://doi.org/10.1109/SmartNets55823.2022.9993994
De Silva, U., Fernando, L., Bandara, K., & Nawaratne, R. (2024). Video summarisation with incident and context information using generative AI. Proceedings of IECON 2024 – 50th Annual Conference of the IEEE Industrial Electronics Society, 1–6. https://doi.org/10.1109/IECON55916.2024.10905127
ESP32 BaseEncoder Docs: https://esp32.com/viewtopic.php?t=2461
Esp32 and audio (text to speech) : https://www.esp32.com/viewtopic.php?t=7294
Farooq, M. S., Shafi, I., Khan, H., Díez, I. D. L. T., Breñosa, J., Espinosa, J. C. M., & Ashraf, I. (2022). IoT enabled intelligent stick for visually impaired people for obstacle recognition. Sensors, 22, 8914. https://doi.org/10.3390/s22228914
GEMINI API - Docs: https://ai.google.dev/gemini-api/docs/vision
Hari, K., Chowdary, M. A., Sumathi, M., Sainadh, D., & Manikanta, T. (2024). Deployment of real-time object recognition in Raspberry Pi with Neural Compute Stick for blind and deaf people. Proceedings of the 2024 3rd International Conference on Applied Artificial Intelligence and Computing (ICAAIC), 305–310. https://doi.org/10.1109/ICAAIC60222.2024.10575567
Islam, R., & Ahmed, I. (2024). Gemini—the most powerful LLM: Myth or truth. Proceedings of the 2024 5th Information Communication Technologies Conference (ICTC), 303–308. https://doi.org/10.1109/ICTC61510.2024.10602253
Jivrajani, K., Patel, S. K., Parmar, C., Surve, J., Ahmed, K., & Bui, F. M. (2023). AIoT-based smart stick for visually impaired person. IEEE Transactions on Instrumentation and Measurement, 72, 1–11. https://doi.org/10.1109/TIM.2022.3227988
Merencilla, N. E., Manansala, E. T., Balingit, E. C., Crisostomo, J. B. B., Montano, J. C. R., & Quinzon, H. L. (2021). Smart stick for the visually impaired person. Proceedings of the 2021 IEEE 13th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), 1–6. https://doi.org/10.1109/HNICEM54116.2021.9731834
Moreira, F. W. R., Hermes, G., & de Lima, J. M. M. (2024). Development of a cross platform mobile application using Gemini to assist visually impaired individuals. Proceedings of the 2024 9th International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS), 559–566. https://doi.org/10.1109/ICIIBMS62405.2024.10792854
Mude, R., Salunke, A., Patil, C., & Kulkarni, A. (2022). IoT enabled smart blind stick and spectacles mountable eye-piece equipped with camera for visually challenged people. Proceedings of the 2022 International Conference on Industry 4.0 Technology (I4Tech), 1–5. https://doi.org/10.1109/I4Tech55392.2022.9952569
Patankar, N. S., Haribhau, B., Dhorde, P. S., Patil, H. P., Maind, R. V., & Deshmukh, Y. S. (2023). An intelligent IoT based smart stick for visually impaired person using image sensing. Proceedings of the 2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT), 1–6. https://doi.org/10.1109/ICCCNT56998.2023.10306645
Patil, A., Bendale, Y., Bhangare, P., & Patil, S. (2024). OdinEye: An AI based visual assistive device for the blind and partially sighted. Proceedings of the 2024 4th International Conference on Ubiquitous Computing and Intelligent Information Systems (ICUIS), 158–163. https://doi.org/10.1109/ICUIS64676.2024.10866520
Ram, G. K. S., & Muthumanikandan, V. (2024). Visistant: A conversational chatbot for natural language to visualizations with Gemini large language models. IEEE Access, 12, 138547–138563. https://doi.org/10.1109/ACCESS.2024.3465541
Sharma, H., Tripathi, M., Kumar, A., & Gaur, M. S. (2018). Embedded assistive stick for visually impaired persons. Proceedings of the 2018 9th International Conference on Computing, Communication and Networking Technologies (ICCCNT), 1–6. https://doi.org/10.1109/ICCCNT.2018.8493707
Suresh, K., Paulina. J., Jeeva. C., Rajkumar. K., Kalaivani. K., & Amsavarthini. R. (2022). Smart assistive stick for visually impaired person with image recognition. Proceedings of the 2022 International Conference on Power, Energy, Control and Transmission Systems (ICPECTS), 1–5. https://doi.org/10.1109/ICPECTS56089.2022.10047699
Vanitha, V., Saravanan, P., Gopi, A., Hemanathan, S., Kumar, B. K., & Kishore Kumar, S. (2024). Intelligent blind stick using digital image processing. Proceedings of the 2024 International Conference on Emerging Research in Computational Science (ICERCS), 1–5. https://doi.org/10.1109/ICERCS63125.2024.10895580
Yang, L., Wu, Z., Hong, J., & Long, J. (2023). MCL: A contrastive learning method for multimodal data fusion in violence detection. IEEE Signal Processing Letters, 30, 408–412. https://doi.org/10.1109/LSP.2022.3227818
Yuan, J., Yu, Y., Mittal, G., Hall, M., Sajeev, S., & Chen, M. (2024). Rethinking multimodal content moderation from an asymmetric angle with mixed-modality. In Proceedings of the 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 8517–8527. https://doi.org/10.1109/WACV57701.2024.00834
Zhai, Z. (2022). Rating the severity of toxic comments using BERT-based deep learning method. In Proceedings of the 2022 IEEE 5th International Conference on Electronics Technology (ICET), 1283–1288. https://doi.org/10.1109/ICET55676.2022.9825384
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