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系統識別號 U0026-1011201822103700
論文名稱(中文) 智慧物聯網應用框架之設計與實作
論文名稱(英文) Design and Implementation of an Intelligent Application Framework on Internet of Things
校院名稱 成功大學
系所名稱(中) 電腦與通信工程研究所
系所名稱(英) Institute of Computer & Communication
學年度 107
學期 1
出版年 107
研究生(中文) 李仕雄
研究生(英文) Shih-Hsiung Lee
學號 Q38044024
學位類別 博士
語文別 英文
論文頁數 123頁
口試委員 口試委員-黃能富
口試委員-蔣依吾
口試委員-洪西進
口試委員-黃仁竑
召集委員-陳俊良
口試委員-詹寶珠
口試委員-黃悅民
口試委員-謝錫堃
指導教授-楊竹星
中文關鍵字 物聯網  基於權杖授權服務  心跳偵測  盲訊號分離  物件偵測  影像前處理及辨識 
英文關鍵字 Internet of Things  Token-based Authorization Service  Heart beats detection  Blind Source Separation  Object detection  Image processing and recognition 
學科別分類
中文摘要 在本論文中,主要探討智慧物聯網的應用框架設計及實作。物聯網是表示數十億個互聯的設備,設備上通常搭載著感知器和通訊裝置。如何使其成為一個智慧終端是重要的議題。而物聯網裝置一般來說是具備低功耗、有限儲存空間和低處理能力的特點,關於可靠性,運算性能,安全性及保密性來說都相當有限。因此本論文探討如何整合雲端平台技術及如何實現邊緣運算,來達到智慧終端的實現。而物聯網的架構從宏觀角度來看,分為三個階層:感知層、網路層及應用服務層。本論文研究的範圍,從感知層擷取感知器的資料,進而分析資料。透過網路層的通訊能力將資料傳送至雲端,實現多個應用情境。並且針對資料提出有效的解決演算法,如盲訊號分離來處理多重感知器問題,影像前處理和及時物件計數及辨識演算法。
在應用情境及框架面上,本論文設計及實作包含以下幾個領域: 智慧醫療照護、智慧工業及智慧綠能等主題。在智慧醫療照護應用情境中,我們實作了二種應用情境。(1) 心率偵測應用在孕婦照護及登山者。(2) 影像偵測應用在指甲、頭髮及頭皮的照護上。在智慧工業上,我們採用了工業用相機實作一個及時高效率的工業檢測情境。 在智慧綠能上,我們實作一個智慧插座,有效監控電壓電流的資訊,並且透過此資訊訓練一個模型達到智能的控制效果。
在研究的過程中發現要實現更好的智慧終端,需仰賴邊緣運算裝置。本篇論文使用一個具備圖形處理核心的嵌入式裝置做為邊緣運算裝置,比雲端平台更能及時地將運算結果回饋給終端。此外,針對資料處理的演算法,我們也提出了一些新穎的算法可以有效應用在智慧物聯網框架中。
而當資料傳送至雲端平台時,一般智慧終端裝置會藉由RESTful API存取雲端上的服務。而雲端伺服器如何驗證及授權數十億裝置的權限是一大挑戰。除此之外,個人使用智慧終端裝置時,伴隨著隱私性資料或安全性的問題。因此在智慧物聯網應用框架中,我們提出一個基於權杖的授權服務架構。透過權杖,裝置可以更安全的存取雲端服務。而權杖是經由第三方驗證中心頒布,可以提高其可靠度及安全性。權杖具備高度隱私性的特色,能使敏感性資料不輕易地被揭露。權杖僅在一段時間內有效或當權杖計數超過系統定義的閥值會失去其作用,藉此降低裝置被駭的風險。本論文所提出的基於權杖的授權服務架構會應用在本論文的情境中,尤其對於在醫療穿戴式裝置上更顯得重要。在各章節會分別介紹各個應用情境、應用框架及實驗結果。
英文摘要 In this thesis, we mainly discuss the application framework and implementation of the intelligent Internet of Things. The Internet of Things represents billions of interconnected devices. The devices are usually equipped with sensors and communication modules. How to make it become a smart terminal device is an important topic. IoT devices are generally characterized by low power consumption, limited storage space, and low processing capacity. They are quite limited in terms of reliability, computing performance, security, and confidentiality. Therefore, this work explores how to integrate cloud platform technology and how to implement edge computing to achieve the realization of smart terminals. The architecture of the Internet of Things is divided into three levels from a macro perspective: the perception layer, the network layer, and the application service layer. The scope of this work is to extract the data of the sensors from the perceptual layer and analyze the data. Furthermore, it can achieve multiple application scenarios by transmitting data to the cloud through the communication capabilities of the network layer. Add to this, we propose some effective intelligent algorithms for the data, such as blind source separation algorithm for handling with multiple sensors, image preprocessing algorithm and real time object counting and recognition algorithm.
On the application scenario and framework side, this thesis discusses and implements the following areas: smart health care, smart industry and smart green energy. In the context of smart health care applications, we have implemented two application scenarios. (1) Heart rate detection is applied to pregnant women and mountain climbers. (2) Image detection is applied to the care of nails, hair and scalp. In the smart industry, we have used industrial cameras to implement a real time and efficient industrial inspection scenario. In Smart green energy, we implement a smart plug that effectively monitors voltage and current information and we train a model to achieve an intelligent control through this information.
In the course of the research, it was found that to achieve a better intelligent terminal, it is necessary to rely on the edge computing device. This thesis uses an embedded device with a graphics processing core as the edge computing device, which can return the operation result to the terminal timely than the cloud platform. In addition, for the algorithm of data processing, we also propose some novel algorithms that can be effectively applied in the intelligent Internet of Things framework.
Add to this, when the data is transmitted to the cloud platform, the smart terminal device accesses the service on the cloud through the RESTful API generally. How cloud servers verify and authorize the permissions of billions of devices is a challenge. In addition, personal use of smart terminal devices is accompanied by privacy issues or security issues. Therefore, in the intelligent IoT application framework, we propose a token-based authorization service architecture. Through the token, the device can access the cloud service more securely. The token is released by a third-party verification center to improve its reliability and security. The token has a highly private feature that makes sensitive data not easily revealed. The token is only valid for a period of time or when the count of token does not exceed the system-defined threshold. Thereby, the token-based authorization service can reduce the risk of the device being hacked. The token-based authorization service architecture proposed in this thesis will be applied in the context of this work, especially for medical wearable devices. It is important obviously. Each application scenario, application framework, and experimental results are presented in each chapter.
論文目次 Table of Contents
摘要 i
Abstract ii
Acknowledgements iv
Table of Contents v
List of Tables viii
List of Figures ix
Chapter 1. Introduction 1
1.1. Background 1
1.2. Motivation and Aim of the Research 2
1.3. Organization of the Thesis 4
Chapter 2. TBAS:Token-based Authorization Service 5
2.1. Introduction 5
2.2. Related Works 6
2.2.1. OpenID 6
2.2.2. OAuth 7
2.3. TBAS 9
2.3.1. Authorization Check Layer 10
2.3.2. Generating a Token 10
2.3.3. Granting a Token 11
2.3.4. Mobile Device Binding 11
2.4. Application Scenario of Pregnant Women 13
2.4.1. Platform Deployment 13
2.4.2. Token Request and Generation of Wearable Medical Device 14
2.4.3. Token Security and Data Privacy Protection 15
2.4.4. Differences among Token, OpenID and Oauth 16
2.4.5. Features of Management Platform 16
2.5. Application Scenario of mountaineers 19
2.5.1. An Intelligent Emergency Rescue Assistance System 20
2.5.2. Design of Wearable Device 21
2.5.3. Altitude Sickness and Hypothermia Detection 22
2.5.4. Climber’s Posture Recognition 23
2.5.5. Event Reminding 23
2.5.6. Beacon Signal for Search and Rescue 24
2.5.7. Experimental Results 24
Chapter 3. Intelligent Algorithms for Heart Rate Detection 27
3.1. Intelligent Heart Rate Monitoring Algorithms 27
3.1.1. Introduction 27
3.1.2. Problem Definition 27
3.1.3. Proposed Algorithm 28
3.1.4. Preprocessing Steps 28
3.1.5. Dynamic Time Wrapping 29
3.1.6. Empirical Algorithm 31
3.1.7. Experimental Results 34
3.2. GPSO-ICA: Independent Component Analysis based on Gravitational Particle Swarm Optimization 38
3.2.1. Problem Definition 38
3.2.2. Background 39
3.2.3. Independent Component Analysis 41
3.2.4. Particle Swarm Optimization 43
3.2.5. Gravitation Searching Algorithm 44
3.2.6. Particle Swarm Optimization based ICA 46
3.2.7. Proposed Algorithm 48
3.2.8. Experimental Results 48
Chapter 4. Smart Camera Sensors in Internet of Things 57
4.1. A Real Time Object Recognition and Counting System 57
4.1.1. Problem Definition 57
4.1.2. Background 57
4.1.3. System Overview 60
4.1.4. Preloading 61
4.1.5. Motion Estimation for Dropping Frames 62
4.1.6. Object Recognition 63
4.1.7. Matching Template 64
4.1.8. Counting 66
4.1.9. Experimental Results 66
4.2. Fingernails Analysis Management System 70
4.2.1. Problem Definition 70
4.2.2. Background 71
4.2.3. The Proposed System 72
4.2.4. Fingernails Image Preprocessing 73
4.2.5. Biometric Authentication Using Fingernails 76
4.2.6. Experimental Results 76
4.3. An Intelligent Hair and Scalp Analysis System 80
4.3.1. Problem Definition 80
4.3.2. Background 81
4.3.3. Proposed Methods 83
4.3.4. Preprocessing 84
4.3.5. Detection of Baldness Status 85
4.3.6. Detection of Scalp Status 87
4.3.7. Parameter Adjustment based on Different Lighting Conditions 88
4.3.8. Experimental Results 89
Chapter 5. Smart Plug in Internet of Things 95
5.1. Problem Definition 95
5.2. Background 95
5.2.1. Smart Plug 96
5.2.2. Communication Protocol on Smart Plug 96
5.2.3. Energy Management System 97
5.2.4. Data Analysis of Smart Plugs 98
5.3. Proposed Power Management Framework System 98
5.3.1. System overview 98
5.3.2. The Design of Smart Plug 99
5.3.3. The Design of Smart Gateway 100
5.3.4. Network Communication between Smart Plug and Gateway 101
5.3.5. The Protocol Design of Management Platform 102
5.3.6. Continuously Learning Power Management System 103
5.4. Experimental Results 105
Chapter 6. Conclusions and Future Works 109
6.1. Conclusions 109
6.2. Future Works 111
References 113
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