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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/21798
Title: | 基於邊緣計算的異常駕駛行為偵測平台之設計及實作 Design and Implementation of An Edge Computing Based Anomaly Detection Platform for Car Driving |
Authors: | Jia-Xing Liao 廖家興 |
Advisor: | 林風(Phone Lin) |
Keyword: | OBD-II,異常偵測,車輛,駕駛行為, OBD-II,anomaly detection,car,driving behavior, |
Publication Year : | 2021 |
Degree: | 碩士 |
Abstract: | OBD-II是一個標準的車輛診斷連接埠,目前被廣泛用於車輛診斷及維護。在這篇論文中,我們設計並實作了一個基於邊緣計算的異常駕駛行為偵測平台。該平台透過OBD-II連接埠,從車輛的引擎電子控制單元(Engine ECU)蒐集OBD參數資料,並使用一個預先訓練好的駕駛行為模型進行異常偵測。該平台能夠被安裝到一個稱為樹莓派(Raspberry Pi)的小型單主機板電腦中,並提供低延遲的異常偵測服務。 The OBD-II is a standard diagnostic port which has been widely used in the vehicle diagnostic and maintenance. In this thesis, we design and implement an edge-computing based anomaly detection platform (ECADP) for car driving, which collects the value of OBD parameters from the engine ECU of vehicle through OBD-II and detect anomalies with a pre-trained driving behavior model. The platform can be installed on a small single-board computer called Raspberry Pi. The anomaly detection service runs with low latency. |
URI: | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/21798 |
DOI: | 10.6342/NTU202004475 |
Fulltext Rights: | 未授權 |
Appears in Collections: | 資訊工程學系 |
Files in This Item:
File | Size | Format | |
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U0001-2912202010512900.pdf Restricted Access | 7.49 MB | Adobe PDF |
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