智慧城市(Smart City)期望有效整合都市的組成系統及服務，提昇資源運用的效率、最佳化都市管理和服務，以及改善人類的生活品質。在智慧城市的架構中，城市模型及物聯網(Internet of Things, IoT)各提供了靜態與動態的多種資訊，為了達到具系統性的智慧城市基礎建設，物聯網及城市模型的整合是不可或缺的。然而，目前多數整合城市模型及物聯網資源之現有解決方案都是根據個別應用情境而客製化而成，不同應用的資料整合方式不具有互操作性。本研究除了搜集相關文獻對各式整合策略進行分類歸納及優劣分析，為了提升智慧城市的互操作性，本研究提出了一種基於語義(Semantic)本體論(Ontology)的方法整合開放地理空間聯盟(Open Geospatial Consortium, OGC)所定義的CityGML、IndoorGML、及SensorThings API之標準資料模型。此外，由於物聯網中對於物(Thing)的定義非常彈性，此篇研究提出的本體論考慮了在城市模型中對於Thing之認知的不同視角，例如將建物、房間、門窗、裝置視為Thing的不同包裝方式。根據本研究的結果顯示，基於所提出之本體論，各自獨立的CityGML、IndoorGML、SensorThings API資料來源可透過SPARQL(SPARQL Protocol and RDF Query Language)查詢彼此對應之關係。此外，本研究也將該本體論應用於各式模擬智慧城市案例，如智能家居、智慧保全系統、智慧醫療照護、以及智能火災疏散系統，以證明這項研究的貢獻。總體而言，此研究所提出的解決方案以具互操作性的方式促進物聯網資源及城市模型資訊的整合，進而支援多樣的智慧城市應用。

Smart cities effectively integrate human, physical, and digital systems operating in the built environment to provide automatic and efficient applications. While city models, Internet of Things (IoT), and domain models are essential components of smart cities, the integration of IoT resources and the city models are central information backbone for smart city cyber-infrastructures. However, by reviewing existing literatures and cases, we argue that most of the existing solutions integrating city models and IoT resources are customized based on individual applications and lack of interoperability. To improve the interoperability between smart city modules, this study first categorizes and analyzes the pros and cons of integration strategies, and proposes a semantic-based method to integrate OGC (Open Geospatial Consortium) CityGML, IndoorGML and SensorThings API standards. To be specific, this study proposes an integration ontology to connect the data models from these standards. In addition, due to the flexible definition of Things in the IoT, the proposed ontology also supports multiple views of Things, including a-building-as-a-Thing, a-room-as-a-Thing, an-opening-as-a-Thing, and a-device-as-a-Thing. As a result, information from the CityGML, IndoorGML and SensorThings API can be connected and queried via SPARQL (SPARQL Protocol and RDF Query Language) queries. To demonstrate the contributions of this research, different use cases such as smart home, smart security, smart healthcare and fire evacuation system are simulated. Overall, the proposed solution can facilitate the integration of IoT resources and city models in an interoperable manner to support smart city applications.

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