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DC 欄位 | 值 | 語言 |
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dc.contributor.advisor | 林風(Phone Lin) | |
dc.contributor.author | Jia-Xing Liao | en |
dc.contributor.author | 廖家興 | zh_TW |
dc.date.accessioned | 2021-06-08T03:47:17Z | - |
dc.date.copyright | 2021-01-20 | |
dc.date.issued | 2021 | |
dc.date.submitted | 2021-01-11 | |
dc.identifier.citation | [1] M. Abadi, P. Barham, J. Chen, Z. Chen, A. Davis, J. Dean, M. Devin, S. Ghemawat, G. Irving, M. Isard, et al. Tensorflow: A system for largescale machine learning. In 12th USENIX symposium on operating systems design and implementation (OSDI 16), pages 265–283, 2016. [2] Y.S. Chou, Y.C. Mo, J.P. Su, W.J. Chang, L.B. Chen, J.J. Tang, and C.T. Yu. icar system: A lorabased low power wide area networks vehicle diagnostic system for driving safety. In 2017 International Conference on Applied System Innovation (ICASI), pages 789–791, 2017. [3] Elm Electronics Inc. ELM327 OBD to RS232 Interpreter [Online]. Avali able at https://www.elmelectronics.com/wp-content/uploads/2016/07/ ELM327DS.pdf (Accessed: January 2021). [4] U. Flaig and A. Sieber. Electronic control units of bosch edc systems. Technical report, SAE Technical Paper, 1988. [5] S. Hochreiter and J. Schmidhuber. Long shortterm memory. Neural computation, 9(8):1735–1780, 1997. [6] ISO. Road vehicles —Diagnostic systems —Part 2: CARB requirements for inter change of digital information, Feb 1994. [7] ISO. Road vehicles —Diagnostic systems —Keyword Protocol 2000 —Part 4: Re quirements for emissionrelated systems, Jun 2000. [8] ISO. Road vehicles —Controller area network (CAN) —Part 1: Data link layer and physical signalling, Dec 2015. [9] ISO. Road vehicles —Diagnostic communication over Controller Area Network (DoCAN) —Part 4: Requirements for emissionsrelated systems, Apr 2016. [10] J.S. Jhou, S.H. Chen, W.D. Tsay, and M.C. Lai. The implementation of obdii vehicle diagnosis system integrated with cloud computation technology. In 2013 Second International Conference on Robot, Vision and Signal Processing, pages 9– 12, 2013. [11] D. P. Kingma and J. Ba. Adam: A method for stochastic optimization. arXiv preprint arXiv:1412.6980, 2014. [12] P. Malhotra, A. Ramakrishnan, G. Anand, L. Vig, P. Agarwal, and G. Shroff. Lstmbased encoderdecoder for multisensor anomaly detection. arXiv preprint arXiv:1607.00148, 2016. [13] B. Nirmali, S. Wickramasinghe, T. Munasinghe, C. Amalraj, and H. D. Bandara. Vehicular data acquisition and analytics system for realtime driver behavior moni toring and anomaly detection. In 2017 IEEE International Conference on Industrial and Information Systems (ICIIS), pages 1–6, 2017. [14] F. Pezoa, J. L. Reutter, F. Suarez, M. Ugarte, and D. Vrgoč. Foundations of json schema. In Proceedings of the 25th International Conference on World Wide Web, pages 263–273, 2016. [15] Python Software Foundation. The Python Language Reference [Online]. Avaliable at https://docs.python.org/3/reference/ (Accessed: January 2021). [16] Raspberry Pi Foundation. Raspberry Pi Documentation [Online]. Avaliable at https://www.raspberrypi.org/documentation/ (Accessed: January 2021). [17] SAE International. Class B Data Communications Network Interface, Nov 1996. [18] SAE International. Diagnostic Connector Equivalent to ISO/DIS 150313: Decem ber 14, 2001, Jul 2012. [19] SAE International. E/E Diagnostic Test Modes, Feb 2012. [20] C. Toh. Wireless ATM and AdHoc Networks: Protocols and Architectures. Springer US, 1997. [21] B. Whitfield. PythonOBD [Online]. Avaliable at https://github.com/ brendan-w/python-OBD (Accessed: January 2021). [22] E.H. Yeh, P. Lin, X.X. Lin, J.Y. Jeng, and Y. Fang. System error prediction for business support systems in telecommunications networks. IEEE Transactions on Parallel and Distributed Systems, 31(11):2723–2733, 2020. [23] M. Zhang, C. Chen, T. Wo, T. Xie, M. Z. A. Bhuiyan, and X. Lin. Safedrive: on line driving anomaly detection from largescale vehicle data. IEEE Transactions on Industrial Informatics, 13(4):2087–2096, 2017. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/21798 | - |
dc.description.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。 | zh_TW |
dc.description.abstract | 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. | en |
dc.description.provenance | Made available in DSpace on 2021-06-08T03:47:17Z (GMT). No. of bitstreams: 1 U0001-2912202010512900.pdf: 7666171 bytes, checksum: 627eb90ebfd458ac165c77c3f6fef867 (MD5) Previous issue date: 2021 | en |
dc.description.tableofcontents | 摘要 i Abstract ii Contents iii List of Figures v List of Tables vi 1 Introduction 1 2 Data Collection Component 5 2.1 The OBDReader Class 5 2.1.1 API Functions 5 2.1.2 The load_command Function 7 2.1.3 The connect Function 8 2.1.4 The query_job Function 8 2.2 The DataRecorder Class 9 2.3 Data Collection Procedure 10 3 Anomaly Detection Component 14 3.1 The DataHandler Class 14 3.2 The LSTMDetection Class 15 3.2.1 API Functions 15 3.2.2 The predict Function 17 3.2.3 Detection Model 17 3.3 Detection Procedure 23 4 Warning Delivery Component 26 4.1 The WIFIConnect Class 26 4.2 The WarningHandler Class 27 4.2.1 The result_handler Function 27 4.2.2 The message_handler Function 28 5 Performance Issue 30 5.1 Model Performance 30 5.2 Platform Delay 33 5.2.1 Data Collection Delay 33 5.2.2 Anomaly Detection Delay 33 6 Conclusion 35 A OBD Data Collection 36 B Figures of Devices 39 Bibliography 41 | |
dc.language.iso | en | |
dc.title | 基於邊緣計算的異常駕駛行為偵測平台之設計及實作 | zh_TW |
dc.title | Design and Implementation of An Edge Computing Based Anomaly Detection Platform for Car Driving | en |
dc.type | Thesis | |
dc.date.schoolyear | 109-1 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 楊舜仁(Shun-Ren Yang),黃志煒(Chih-Wei Huang),劉光浩(Kuang-Hao Liu) | |
dc.subject.keyword | OBD-II,異常偵測,車輛,駕駛行為, | zh_TW |
dc.subject.keyword | OBD-II,anomaly detection,car,driving behavior, | en |
dc.relation.page | 43 | |
dc.identifier.doi | 10.6342/NTU202004475 | |
dc.rights.note | 未授權 | |
dc.date.accepted | 2021-01-12 | |
dc.contributor.author-college | 電機資訊學院 | zh_TW |
dc.contributor.author-dept | 資訊工程學研究所 | zh_TW |
顯示於系所單位: | 資訊工程學系 |
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