Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Kanchan, S Maria Alice; Jose, Deepa V; Singh, Shivangi Title A name given to the resource Bio-Compatible CMOS-IC Based Obstacle Detection System Using IoT with ML Integration for Assistive Wearable Devices Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived 2025 IEEE 7th International Conference on Computing, Communication and Automation, ICCCA 2025; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICCCA66364.2025.11325666" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICCCA66364.2025.11325666</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105035151135?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105035151135?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant 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 Description An account of the resource 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. Subject The topic of the resource 1D-CNN; ESP32 microcontroller; IR Sensor; Random Forest; Skin-Embedded CMOS IC Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833156980-8; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online