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