智慧聯網(IoT)是由許多個智慧裝置組成，把真實世界的資料帶進去虛擬世界，協助解決人類每天遇到的挑戰(例：環境汙染)。隨著智慧聯網的興盛，許多的平台(例:xively)相繼出現，允許人們可以分享感測器，和建置相對應的應用程式。然而，如何有效率如從極大數量的感測器，搜尋和選擇適合自己應用程式的感測器是一個挑戰。這篇論文調查了有關情境感知的感測器挑選，辨識了感測器的能力，和提供感測服務的流程。我們建置了一個感測服務架構，並提供了一個情境感知的語意挑選方法，讓使用者可以從極大量的感測器中挑選適合的感測器。這個方法可以讓使用者可以輸入情境相關的參數，包括使用者偏好、感測器的準確度、感測器的感測範圍、感測器的能量消耗等。我們的架構更進一步的嘗試去減少每當感測器狀態改變時，要對伺服器做更新的網路流量。我們實作了一個感測服務架構和挑選的原型，證明架構和方法的應用可能性。我們的模擬結果顯示了我們提供的感測器搜尋和挑選方法和傳統的關鍵字搜尋方法相比，可以達到較低的感測器能量消耗，進一步延伸了感測網路的生命週期。

The Internet of Things comprises a large number of “smart things” bringing in physical world data that help resolve the challenges (e.g., environmental pollution) we face every day. With the prevalence of IoT, some platforms emerged (e.g., Xively) on which people are allowed to share or retrieve sensor data and deploy applications. It is, however, a challenge to search/select appropriate sensors among enormous sensors for a particular application in an efficient and effective way. This paper investigates context-aware sensor selection, identification of sensors characteristics, and the process of publishing services. We propose a sensing service architecture and proposes a context-aware search/selection method to efficiently select relevant sensors among a large set of available sensors. The context-dependent parameters for sensor selection proposed in this paper include user preferences, accuracy, sensing range, power consumption, etc. Moreover, the proposed architecture attempts to reduce excessive network traffic caused by frequent change of sensor states. We develop a prototype of the proposed architecture with semantic sensor selection and demonstrate its applicability to many applications. The prototype can select proper sensors intelligently for users according to their requirements to develop their personalized applications. Our simulation results show that the proposed search/selection method can achieve lower power consumption, as compared with traditional text-based search schemes, which further extends the lifetime of sensor networks.

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