Senior health management through internet of things and real-time big data analytics

Author(s):  
Xin Deng ◽  
Donghui Wu
Author(s):  
Shaila S. G. ◽  
Bhuvana D. S. ◽  
Monish L.

Big data and the internet of things (IoT) are two major ruling domains in today's world. It is observed that there are 2.5 quintillion bytes of data created each day. Big data defines a very huge amount of data in terms of both structured and unstructured formats. Business intelligence and other application domains that have high information density use big data analytics to make predictions and better decisions to improve the business. Big data analytics is used to analyze a high range of data at a time. In general, big data and IoT were built on different technologies; however, over a period of time, both of them are interlinked to build a better world. Companies are not able to achieve maximum benefit, just because the data produced by the applications are not utilized and analyzed effectively as there is a shortage of big data analysts. For real-time IoT applications, synchronization among hardware, programming, and interfacing is needed to the greater extent. The chapter discusses about IoT and big data, relation between them, importance of big data analytics in IoT applications.


Author(s):  
Sornalakshmi Krishnan ◽  
Kayalvizhi Jayavel

In this chapter, a discussion on the integration of distributed streaming Big Data Analytics with the Internet of Things is presented. The chapter begins with the introduction of these two technologies by discussing their features and characteristics. Discussion on how the integration of these two technologies benefit in efficient processing of IoT device generated sensor data follows next. Such data centric processing of IoT data powered by cloud, services and other enablers will be the architecture of most of the realtime systems involving sensors and real-time monitoring and actuation. The Volume, Variety and Velocity of sensor generated data make it a Big Data scenario. In addition, the data is real time and requires decisions or actuations immediately. This chapter discusses how IoT data can be processed using distributed, scalable stream processing systems. The chapter is concluded with future directions of such real time Big Data Analytics in IoT.


2022 ◽  
pp. 722-757
Author(s):  
Sornalakshmi Krishnan ◽  
Kayalvizhi Jayavel

In this chapter, a discussion on the integration of distributed streaming Big Data Analytics with the Internet of Things is presented. The chapter begins with the introduction of these two technologies by discussing their features and characteristics. Discussion on how the integration of these two technologies benefit in efficient processing of IoT device generated sensor data follows next. Such data centric processing of IoT data powered by cloud, services and other enablers will be the architecture of most of the realtime systems involving sensors and real-time monitoring and actuation. The Volume, Variety and Velocity of sensor generated data make it a Big Data scenario. In addition, the data is real time and requires decisions or actuations immediately. This chapter discusses how IoT data can be processed using distributed, scalable stream processing systems. The chapter is concluded with future directions of such real time Big Data Analytics in IoT.


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