Real-Time Data Analytics for Large Scale Sensor Data
暫譯: 大規模感測器數據的即時數據分析
Das, Himansu, Dey, Nilanjan, Emilia Balas, Valentina
- 出版商: Academic Press
- 出版日期: 2019-09-03
- 售價: $6,120
- 貴賓價: 9.5 折 $5,814
- 語言: 英文
- 頁數: 420
- 裝訂: Quality Paper - also called trade paper
- ISBN: 0128180145
- ISBN-13: 9780128180143
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相關分類:
感測器 Sensor、Data Science
海外代購書籍(需單獨結帳)
相關主題
商品描述
Real-Time Data Analytics for Large-Scale Sensor Data covers the theory and applications of hardware platforms and architectures, development of software methods, techniques and tools, applications and governance, and adoption strategies for the use of massive sensor data in real-time data analytics. It presents the leading-edge research in the field and identifies future challenges in this fledging research area. Most of the envisioned IoT applications involve complex intelligent systems that have to cater to situations that are geo-distributed in nature. Examples of such IoT based use cases include smart healthcare, management and decision making in smart grids, and disaster management, among others. In order that the aforementioned applications can meet real-time constraints, a number of research issues need to be addressed. Though it has been a well-accepted fact that bringing processing from a central data center to much closer premises at the edge of networks through extensive distributed processing is a potential solution, this area has not been explored much. Such a computing paradigm should form the basis of large-scale deployments with real-time alarms and triggers for their control aspects. Real-Time Data Analytics for Large-Scale Sensor Data captures the essence of real-time IoT based solutions that require a multi-disciplinary approach for catering to on-the-fly processing, including methods for high performance stream processing, adaptively streaming adjustment, uncertainty handling, latency handling, as well as performance issues owing to geo-distributed data sources, optimization, distributed machine learning and many others.
- Examines IoT applications, design of real-time intelligent systems, as well as how to manage the rapid growth of the large volume of sensor data on a daily basis in an efficient way
- Discusses intelligent management systems for applications such as healthcare, robotics, and environment modeling
- Provides a focused approach towards design and implementation of real-time intelligent systems for the management of sensor data in large scale environments such as biomedical and clinical applications
商品描述(中文翻譯)
《大型感測器數據的即時數據分析》涵蓋了硬體平台和架構的理論與應用、軟體方法、技術和工具的開發、應用與治理,以及在即時數據分析中使用大量感測器數據的採用策略。它展示了該領域的前沿研究,並指出了這一新興研究領域未來的挑戰。大多數預想的物聯網(IoT)應用涉及複雜的智能系統,這些系統必須應對地理分佈的情況。這類基於物聯網的用例示例包括智能醫療、智能電網中的管理與決策,以及災難管理等。為了使上述應用能夠滿足即時約束,需要解決多個研究問題。雖然將處理從中央數據中心轉移到網絡邊緣的更近位置,通過廣泛的分佈式處理是一個潛在的解決方案,這一領域尚未得到充分探索。這種計算範式應該成為大型部署的基礎,並為其控制方面提供即時警報和觸發器。《大型感測器數據的即時數據分析》捕捉了需要多學科方法以應對即時處理的物聯網解決方案的本質,包括高效能流處理的方法、自適應流調整、不確定性處理、延遲處理,以及由於地理分佈數據源引起的性能問題、優化、分佈式機器學習等。
- 檢視物聯網應用、即時智能系統的設計,以及如何有效管理每日大量感測器數據的快速增長
- 討論智能管理系統在醫療、機器人和環境建模等應用中的應用
- 提供針對大型環境(如生物醫學和臨床應用)中感測器數據管理的即時智能系統設計與實施的專注方法