Ultrasonic Large Scenario Model (ULSM): Vector Embedding System for Ultrasonic Echo Wave Characteristics

Shafait Azam, Mashnunul Huq, Andreas Pech

2025

Abstract

Ultrasonic sensors emitting ultrasound waves can be effectively used in Human Computer Interaction (HCI) to assist visually disabled humans. With the embedding of the sensor echoes into assistive tools, real-time spatial awareness for mobility is enhanced. Moreover, material identification aids object recognition by detecting different materials through their echo signatures. In this article, we study the use of ultrasonic sensors in HCI systems focusing on their ability to detect materials by analysing the ultrasonic wave characteristics. These services aim to improve the autonomy and security of people with visual impairments, offering a complete assistive solution for daily navigation and interaction processes. We have planned to create a vector database for storing these embeddings generated from reflected waves of various materials and objects. In this work, we propose a precise vector embeddings generation framework for ultrasonic systems using ResNet50 convolutional neural network. In the future, Generative AI will use these embeddings to serve a range of applications for greater autonomy and safety, providing an assistive travel and interaction solution for the visually impaired.

Paper Citation

in Harvard Style

Azam S., Huq M. and Pech A. (2025). Ultrasonic Large Scenario Model (ULSM): Vector Embedding System for Ultrasonic Echo Wave Characteristics. In Proceedings of the 14th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM; ISBN 978-989-758-730-6, SciTePress, pages 704-711. DOI: 10.5220/0013251600003905

in Bibtex Style

@conference{icpram25,
author={Shafait Azam and Mashnunul Huq and Andreas Pech},
title={Ultrasonic Large Scenario Model (ULSM): Vector Embedding System for Ultrasonic Echo Wave Characteristics},
booktitle={Proceedings of the 14th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM},
year={2025},
pages={704-711},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013251600003905},
isbn={978-989-758-730-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM
TI - Ultrasonic Large Scenario Model (ULSM): Vector Embedding System for Ultrasonic Echo Wave Characteristics
SN - 978-989-758-730-6
AU - Azam S.
AU - Huq M.
AU - Pech A.
PY - 2025
SP - 704
EP - 711
DO - 10.5220/0013251600003905
PB - SciTePress