基于电子架构的车载冰箱物体检测系统优化研究  

Optimization research on object detection system for car refrigerator based on electronicarchitecture

作　　者：李盼 Li Pan(BYD Auto Industry Co.,Ltd.,Shenzhen 518118,China)

机构地区：[1]比亚迪汽车工业有限公司,广东深圳518118

出　　处：《汽车知识》2024年第11期62-64,共3页AUTOMOTIVE KNOWLEDGE

摘　　要：本文针对当前车载冰箱中物体检测准确率不高的问题,探讨基于电子架构的车载冰箱物体检测系统的优化策略,通过集成先进的传感器技术、嵌入式系统设计与深度学习模型,实现了车载冰箱内物品的精准识别与监测。本文重点论述了基于图卷积网络模型的箱体内物体检测,通过传感器采集的电容、环境数据等,经过数据清洗预处理,构建图模型,根据配置的模型参数进行训练,分析出箱体内是否存在物体。本文研究提升了车载冰箱的智能化水平,为汽车电子配件的发展提供了新的思路。This article addresses the issue of low accuracy in object detection in current car refrigerators and explores optimization strategies for an electronic architecture based car refrigerator object detection system.By integrating advanced sensor technology,embedded system design,and deep learning models,accurate recogni-tion and monitoring of items inside the car refrigerator are achieved.This article focuses on object detection inside a box based on graph convolutional network model.Through sensor collected capacitance,environmen-tal data,etc.,data cleaning and preprocessing are carried out to construct a graph model.Then,according to the configured model parameters,training is carried out to analyze whether there are objects inside the box.This study has improved the intelligence level of car refrigerators and provided new ideas for the development of automotive electronic components.

关 键 词：车载冰箱 物体检测 传感器 图卷积网络 

分 类 号：U467[机械工程—车辆工程]