FRADD：一個實現於AIoT閘道器的人臉辨識應用系統開發和佈署

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姓名

吳佳鴻(Chia-Hung Wu) 查詢紙本館藏

畢業系所

資訊工程學系在職專班

論文名稱

FRADD：一個實現於AIoT閘道器的人臉辨識應用系統開發和佈署
(FRADD：A Face Recognition Application Development and Deployment on AIoT Gateway)

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[完整記錄]

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至系統瀏覽論文 (2027-7-13以後開放)

摘要(中)

隨著AIoT設備逐漸變多，設備管理與佈署也變多，顯得更不容易管理且複雜，本研究以輕量級微服務架構，以人臉辨識服務作為範例，其識別內容包含性別、年齡、情緒、身分等，應用於AIoT閘道器上並進行拓展佈署與更換模型應用服務，只需要透過一個管理端即可佈署應用與資源分配至所有節點，讓服務可以快速應用及提升服務效率。以往用微服務架構設定過於複雜且架構應用服務資源損耗較高，本研究以輕量級微服務架構作為服務框架，在於管理端記憶體減少約25%，節點端記憶體減少約36%，將記憶體資源可用於更多應用服務。本研究實驗成果可應用於各個IoT、AIoT管理服務及拓展應用服務。

摘要(英)

With the gradual increase in the number of AIoT devices, device management and deployment also become more and more difficult to manage and complex, this study uses a lightweight microservice architecture with face recognition service as an example, in which the recognition content includes gender, age, emotion, identity, etc., applied to AIoT gateways and extended deployment and replacement of model application services, only through a single management terminal can deploy applications and resources Allocate to all nodes, so that services can be applied quickly and improve service efficiency. In this study, the lightweight microservice architecture is used as the service framework, which reduces the memory of the management side by 25% and the memory of the node side by 36%, making the memory resources available for more application services. The results of this study can be applied to various IoT and AIoT management services and extended application services.

關鍵字(中)

★ 物聯網
★ 智慧物聯網
★ 微服務架構
★ 容器化

關鍵字(英)

★ IoT
★ AIoT
★ Kubernetes
★ Container

論文目次

摘要 I
Abstract II
致謝 III
目錄 IV
圖目錄 VII
表目錄 X
第一章、緒論 1
1.1 研究背景 1
1.2 研究目的 3
1.3 論文架構 3
第二章、文獻回顧 4
2.1 IoT架構 4
2.1.1 雲計算(Cloud Computing) 5
2.1.2 霧計算(Fog Computing) 6
2.2 AIoT架構 7
2.2.1 邊緣計算(Edge Computing) 8
2.2.2 邊緣運算AIoT閘道器 9
2.3 人臉辨識 10
2.4 人臉辨識應用於AIoT 11
第三章、系統架構 12
3.1 MIAT方法論 12
3.1.1 IDEF0模組設計 13
3.1.2 GRAFCEF離散事件建模 14
3.2 資源管理與容器化技術 15
3.3 輕量級微服務架構與系統 17
3.4 人臉辨識AIoT閘道器應用平台系統架構 18
3.4.1 影片傳輸模組 20
3.4.2 AIoT閘道器應用平台模組 21
3.4.2.1 AIoT閘道器Master模組子系統 23
3.4.2.2 人臉辨識應用模組子系統 25
3.5 系統程式合成 27
第四章、實驗 32
4.1 實驗平台 32
4.1.1 軟硬體實驗環境 32
4.1.2 實驗資料集 35
4.2 人臉辨識實驗 37
4.2.1 性別與年齡測試實驗 38
4.2.2 情緒測試實驗 42
4.2.3 身分識別實驗 44
4.3 模型更換實驗 48
4.4 輕量級微服務架構資源測試 49
第五章、結論與未來展望 51
5.1 結論 51
5.2 未來展望 52
參考文獻 53

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指導教授

陳慶瀚

審核日期

2022-7-25

推文