Enhancing Ultrasonic-Based Distance Measurement Accuracy Through Error Correction Mechanism

This paper introduces a pioneering approach to ultrasonic-based distance measurement using ultrasonic sensors. Recognizing the influence of diverse weather conditions on measurement accuracy, an error correction mechanism is proposed to enhance precision. An Artificial Neural Network (ANN) model is deployed and trained on diverse weather datasets to mitigate errors effectively. The proposed model achieves an impressive 98.42

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Publication Details

Published
2024-11-30
DOI
https://doi.org/10.1109/edkcon62339.2024.10870780
Primary Topic
Flow Measurement and Analysis
Type
article
Field-Weighted Citation Impact
0.00
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article

Enhancing Ultrasonic-Based Distance Measurement Accuracy Through Error Correction Mechanism

Prachi Bansal, Jadav Chandra Das, Aritra Mitra, Abhijit Paul et al.
Flow Measurement and Analysis
article

Enhancing Ultrasonic-Based Distance Measurement Accuracy Through Error Correction Mechanism

Prachi Bansal, Jadav Chandra Das, Aritra Mitra, Abhijit Paul, Bikash Debnath, Mudit Saraff
article en

Abstract

This paper introduces a pioneering approach to ultrasonic-based distance measurement using ultrasonic sensors. Recognizing the influence of diverse weather conditions on measurement accuracy, an error correction mechanism is proposed to enhance precision. An Artificial Neural Network (ANN) model is deployed and trained on diverse weather datasets to mitigate errors effectively. The proposed model achieves an impressive 98.42

Techno India University (IN), Ramakrishna Mission Vivekananda Educational and Research Institute (IN), Maulana Abul Kalam Azad University of Technology, West Bengal (IN)
Openalex Percentile: Top 70%
Flow Measurement and Analysis
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