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系統識別號 U0026-1402201910275500
論文名稱(中文) 由互操作性觀點探討即時性地理資訊之處理及展示
論文名稱(英文) An interoperability perspective towards the process and visualization of real-time geographic information
校院名稱 成功大學
系所名稱(中) 測量及空間資訊學系
系所名稱(英) Department of Geomatics
學年度 107
學期 1
出版年 108
研究生(中文) 劉瀚文
研究生(英文) Han-Wen Liu
學號 P66054010
學位類別 碩士
語文別 英文
論文頁數 96頁
口試委員 指導教授-洪榮宏
口試委員-蔡博文
口試委員-黃智遠
中文關鍵字 即時性資料  異質性資料  視覺化 
英文關鍵字 real-time observation  heterogeneous data  visualization 
學科別分類
中文摘要 隨著近年來感測器的快速發展,配合IoT技術對我們的生活帶來革命性的影響與改善,讓我們有能力透過網路或各式通訊技術的傳輸獲得感測器持續不斷的產生各式觀測資料,使我們能夠利用「即時性」資料來發展各項創新的服務及應用,例如智慧城市中各項跨領域的應用服務。然而,縱使我們有能力使用這些資料,各種資料卻並不一定能夠成功的相互配合,特別是有些應用需要整合來源不同的即時資料,並迅速做出決策。因此徹底了解所使用的各種資料對於最終的決策至關重要。有鑑於目前所謂的「即時性應用」很少由時間觀點針對資訊之整合與融合深入探討,其中隱藏許多潛在的風險,本論文將提出一個具有高互操作性的方案,強化對於感測資訊之時間、空間、主題(語意)以及品質資訊之掌握。在考量四項層面後,為了提供即時性及應用需求的必要內容,我們針對即時性地理資料應包含的各項元素設計一個概念模型,希望能將必需的即時性考量納入觀測與示警資訊中,確保來自不同領域的資料能夠以標準化且具互操作性的方式加以處理。
此模型的內容主要包含四大部分:觀測值與感測器共通屬性、直接觀測、衍生觀測以及示警資訊。各類資料若皆遵循標準化的模型設計,使用者無須分別設計不同的介接方式,即可於後續發展的機制中直覺檢視與分析不同來源感測資料之即時性差異。為了驗證我們所提出概念模型的可行性,我們使用現有的即時性開放資料對應到概念模型中進行測試,並證實此概念模型確實可以成功接收不同單位的異質性資料。我們也根據標準化的各項屬性提出六種即時性資料的應用情境:最新資料模式、有效資料模式、理想資料模式、下次更新資料模式、歷史資料模式以及示警資料模式。六種模式皆考量即時性、資料類型以及品質進行設計,因此可以直接應用,智慧化且自動化地呈現出有助於使用者做出決策的資料
針對我們所設定的情境,本研究進一步設計了不同的「情境感知」介面,以視覺化的方式呈現不同來源資料間的差異。介面設計參照地圖設計概念,讓使用者能夠在視覺上辨別具不同即時性特性的資料,也能避免做出錯誤的決策。除了地圖本身外,我們更配合文字以及圖表工具,呈現圖中資料的輔助訊息。若資料缺少校正資訊、觀測數值、不同資料來源、與現在時間差異以及距離下次更新時間長短,在地圖介面終將以不同的符號樣式表示。為了呈現更多即時資料的資訊,我們也加入了包括模式選擇器、時間序列圖、警告訊息視窗、時間統計儀表、指標以及圖例等各類視覺輔助工具。
由於即時性地理資訊應用情境必須經常在具有高度時間壓力的情況下使用,使用我們所提出的標準化流程可以成功的增加感測器資訊的互操作性,只有在確保各類資料皆具有應用上必須的元素,才能享受網路上巨量且多樣的資料所帶來的便利性。
英文摘要 The rapid growth of sensor and IoT technology brings revolutionary improvements to the quality of humans’ daily lives. As a tremendous volume of sensed data is continuously collected and distributed via mobile networks, we enjoy the luxury of using real-time data to develop innovated applications, e.g., cross-domain applications in smart cities. However, the availability of data does not necessarily mean the data can automatically fit together. Especially for applications demanding the fusion of real-time data from different sources for making prompt decisions, the comprehensive understanding about the data being used is extremely important. As current applications rarely address the “real time” issue in an appropriate manner, this research intends to develop an interoperable solution to examine the real-time properties hidden in the distributed datasets.
With the consideration of different aspects in spatial, temporal, thematic and quality information, we propose a conceptual model specifically for modelling the various aspects of the real-time properties of the GIS data. The design aims to provide necessary real-time considerations for both observations and alert information to ensure all the data acquired from different domain providers can be processed together in a standardized and interoperability way. The conceptual model includes 4 major parts: common information for observation and sensor, direct observation, derived observation and alert information. By following the conceptual model, users no longer need to create all kind of connectors to access different types of data. We demonstrate the feasibility of the proposed approach by successfully mapping the real-time open data to the conceptual model. Based on the designed elements in the standardized schema, we further propose six different working modes for real-time applications, namely, latest available information mode, valid information mode, ideal information mode, next update information mode, historical information mode and alert information mode. As every mode is designed according to the considerations of real-time, data type and quality, it can be directly used for smartly and automatically presenting only the datasets that are reliable and helpful for users’ decision making.
Following the defined modes, we further propose a status-aware interface for visually presenting the various aspects of differences among the selected datasets. The interface design is augmented with cartographic knowledge to enable users to visually distinguish data with different real-time properties and avoid wrong decision making. In addition to the map interface, analyzed outcomes are also presented with textual or widgets to provide additional guidance. Map symbols are designed for showing data without calibration, time differences to the current time, observation values, different data source and observation value. From the perspective of showing the additional information for real-time data, different visual aids are included: mode selection and filter, time sequence diagram, warning message box, time statistic gauge, indicator and map legend.
As real-time GIS applications often operate under extremely high time pressure, the proposed standardized approach proves to be able to provide a feasible solution to improve the interoperability of sensor observations in real-time GIS applications. Only after ensuring the necessary information for all the observations is available, can we successfully take the best advantages of the abundant volume and a variety of domain observations in the internet-based exchange environment.
論文目次 摘要 I
ABSTRACT II
TABLE OF CONTENTS IV
LIST OF TABLES VI
LIST OF FIGURES VII
Chapter 1 Introduction 1
1.1 The evolution of GIS 1
1.2 Sensor data 2
1.3 Real-time issues in GIS-based integrated applications 4
1.4 Organization of the thesis 8
Chapter 2 Literature review 9
2.1 Primitive ISO geomatics standards 9
2.1.1 ISO 19107: Spatial schema 10
2.1.2 ISO 19108: Temporal schema 10
2.1.3 ISO 19157: Data quality 11
2.2 Application-oriented standardized schema 13
2.2.1 Observations and Measurements (O&M) 14
2.2.2 SensorThings API 15
2.3 Data fusion 16
2.4 Visualization 20
2.5 Real-time applications 21
2.5.1 Airbox 22
2.5.2 City dashboards 23
2.6 Alert information 24
Chapter 3 Conceptual models for real-time observations 27
3.1 Research strategies 27
3.2 Real-time data modelling considerations 29
3.2.1 Temporal consideration 30
3.2.2 Location consideration 32
3.2.3 Concept/ Semantic consideration 34
3.2.4 Quality consideration 36
3.3 Conceptual model 37
3.3.1 Common properties for sensing data 38
3.3.2 Direct Observation Class 40
3.3.3 Derived Observation Class 40
3.3.4 Historical Dataset Class 41
3.3.5 Alert data class 41
3.4 Mapping from different sources 44
3.4.1 Mapping Airbox data to conceptual model 44
3.4.2 Mapping Air-quality data to conceptual model 45
3.4.3 Mapping Air-quality data in SensorThingsAPI format to conceptual model 47
3.4.4 Comparison between O&M and proposed model 51
Chapter 4 Working modes and visualization of real-time information 55
4.1 Real-time property characterization 55
4.2 Working modes for the real-time data 57
4.2.1 Mode 1: Latest available information mode 59
4.2.2 Mode 2: Valid information mode 61
4.2.3 Mode 3: Ideal information mode 62
4.2.4 Mode 4: Next update information mode 64
4.2.5 Mode 5: Historical information mode 65
4.2.6 Mode 6: Alert information mode 66
Chapter 5 Implementation 69
5.1 System architecture 69
5.2 Test data 71
5.3 Test analysis 76
5.3.1 Latest available information implementation 78
5.3.2 Valid information implementation 83
5.3.3 Ideal information implementation 85
5.3.4 Next update information implementation 86
5.3.5 Historical data implementation 87
5.3.6 Alert data implementation 89
Chapter 6 Conclusion and future work 92
6.1 Conclusion 92
6.2 Future work 93
Reference 94
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