《傳感網流數據處理技術》課程介紹
《傳感網流數據處理技術》是物聯網工程專業的專業選修課。該課程内容是一個全新的研究領域，主要包含兩個方面：數據流管理和數據流分析/挖掘。
該課程主要介紹傳感器網絡中的數據流處理技術，使學生對該領域的原理、技術及研究現狀有一個全面、深刻的了解。主要内容包括四個部分。第一部分，數據流處理和傳感器網絡概述，包括：傳感器網絡在技術和計算方面的背景知識，數據流模型、算法，傳感器網絡中數據流處理的分類、問題和挑戰；第二部分，傳感器網絡中數據流管理的關鍵技術，包括數據流管理系統的特征、傳感器網絡的查詢處理、數據流的彙聚和概括；第三部分，數據流挖掘算法，包括聚類技術、集中和分布的預測學習、傳感器網絡的張量分析；第四部分，介紹傳感器網絡在安全、科學和教育方面的典型應用。
通過本課程的學習，使學生對該領域的原理、技術、研究和應用的現狀有一個深刻的理解，為今後的實際應用奠定紮實的基礎。
The Introduction of Course ---
Data Streams Processing Techniques in Sensor Networks
《Data Streams Processing Techniques in Sensor Networks》is an optional specialty course of Internet of Things Engineering. The content of this course, mainly including data stream management and data stream analysis/mining, is a brand new research field.
The emphasis of this course is to introduce data stream processing technology in sensor networks so that the students can have a comprehensive and profound understanding of the theory, technology and research status about the field. The main content includes four parts. The first part presents an overview of the field of data stream processing and sensor networks including a background about sensor networks from technological and computational points of view; data stream models and algorithms; classification of data stream processing in sensor networks; research issues and challenges that face sensor networks with relation to data stream processing. The second part discusses data stream management techniques in sensor networks including the features of data stream management system; the query processing in sensor networks; the aggregation and summarization of sensor data streams. The third part concerns with data stream mining in sensor networks including clustering techniques, centralized and distributed predictive learning, tensor analysis in sensor networks. The last part presents some of the exciting applications on security, science and education.
By learning this course, students may profoundly understand the principle, technology and the state of art of the research and application and lay a solid foundation for future practical application.
