Bio-Compatible CMOS-IC Based Obstacle Detection System Using IoT with ML Integration for Assistive Wearable Devices
- Title
- Bio-Compatible CMOS-IC Based Obstacle Detection System Using IoT with ML Integration for Assistive Wearable Devices
- Creator
- Kanchan, S Maria Alice; Jose, Deepa V; Singh, Shivangi
- Description
- The proposition presents an IoT-based skin-embedding assistive obstacle detection system for the visually impaired and elderly, integrating bio-compatible semiconductor material, infrared sensing, and cloud-based intelligence. The system comprises an embedded infrared sensor within a bio-compatible CMOS IC powered via an inductive NFC charger, with real-time data transmission to the Blynk mobile application using an external ESP32 BLE module. When obstacles are detected, the application provides immediate feedback through vibration or audio alerts. Simultaneously, the real-time readings are exported to Blynk Cloud for further analysis. The collected data can later be processed and analyzed using Python libraries TensorFlow and sklearn, employing Machine Learning models like 1D-CNN and CNN+RF to improve pattern prediction accuracy and optimize alert responsiveness. By integrating NFC-powered CMOS ICs with Bluetooth-Enabled infrared sensing, the design ensures minimal energy consumption and environmental impact. The machine learning algorithms accurately help in obstacle detection, making the system reliable with independent mobility and enhanced safety for individuals with visual, auditory, or cognitive impairments. 2025 IEEE.
- Source
- 2025 IEEE 7th International Conference on Computing, Communication and Automation, ICCCA 2025;
- Date
- 01-01-2025
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- 1D-CNN; ESP32 microcontroller; IR Sensor; Random Forest; Skin-Embedded CMOS IC
- Coverage
- Kanchan S.M.A., Christ University, Dept. Computer Science, Karanataka, Bengaluru, India; Jose D.V., Christ University, Dept. Computer Science, Karanataka, Bengaluru, India; Singh S., Christ University, Dept. Computer Science, Karanataka, Bengaluru, India
- Rights
- Restricted Access; Hardcopy may be available in the library
- Relation
- ISBN: 979-833156980-8;
- Format
- online
- Language
- English
- Type
- Conference paper
Collection
Citation
Kanchan, S Maria Alice; Jose, Deepa V; Singh, Shivangi, “Bio-Compatible CMOS-IC Based Obstacle Detection System Using IoT with ML Integration for Assistive Wearable Devices,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 18, 2026, https://archives.christuniversity.in/items/show/25926.