Jin Young Shin, Sang Ho Lee, Kwang Hyun Go, Soo-Gon Kim, Seung Eun Lee
{"title":"AI Processor based Data Correction for Enhancing Accuracy of Ultrasonic Sensor","authors":"Jin Young Shin, Sang Ho Lee, Kwang Hyun Go, Soo-Gon Kim, Seung Eun Lee","doi":"10.1109/AICAS57966.2023.10168652","DOIUrl":null,"url":null,"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%.","PeriodicalId":296649,"journal":{"name":"2023 IEEE 5th International Conference on Artificial Intelligence Circuits and Systems (AICAS)","volume":"348 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE 5th International Conference on Artificial Intelligence Circuits and Systems (AICAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AICAS57966.2023.10168652","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
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%.