AI Processor based Data Correction for Enhancing Accuracy of Ultrasonic Sensor

Jin Young Shin, Sang Ho Lee, Kwanghyun Go, Soohee Kim, Seung Eun Lee

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

The usage of various sensors in vehicles has increased with the generalization of advanced driver assistance systems (ADAS). To ensure the safety of drivers and pedestrians, considering the accuracy of measured sensor data is essential. In this paper, we propose a data correction system for enhancing the accuracy of distance data from an ultrasonic sensor utilizing an AI processor. The proposed system detects the motion of an object and adjusts the obtained distance data to align with an ideal gradient of sequential data. Experimental results of the proposed system show an error detection rate of 90.6%.

Original languageEnglish
Title of host publicationAICAS 2023 - IEEE International Conference on Artificial Intelligence Circuits and Systems, Proceeding
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350332674
DOIs
StatePublished - 2023
Event5th IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2023 - Hangzhou, China
Duration: 11 Jun 202313 Jun 2023

Publication series

NameAICAS 2023 - IEEE International Conference on Artificial Intelligence Circuits and Systems, Proceeding

Conference

Conference5th IEEE International Conference on Artificial Intelligence Circuits and Systems, AICAS 2023
Country/TerritoryChina
CityHangzhou
Period11/06/2313/06/23

Keywords

  • AI Processor
  • Data Correction
  • Ultrasonic Sensor

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