scholarly journals Proposing a streaming Big Data analytics (SBDA) platform for condition based maintenance (CBM) and monitoring transportation systems

2017 ◽  
Vol 4 (13) ◽  
pp. 152750
Author(s):  
Jamal Maktoubian
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Transportation Systems ◽  
Condition Based Maintenance ◽  
Streaming Big Data

Big Data Analytics for Maintaining Transportation Systems

2019 ◽  
pp. 73-91 ◽  
Author(s):  
Ravdeep Kour ◽  
Adithya Thaduri ◽  
Sarbjeet Singh ◽  
Alberto Martinetti
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Transportation Systems

scholarly journals Big Data Analytics and Intelligent Transportation Systems

2021 ◽  
Vol 54 (2) ◽  
pp. 216-220
Author(s):  
Jairo R. Montoya-Torres ◽  
Sebastian Moreno ◽  
William J. Guerrero ◽  
Gonzalo Mejía
Keyword(s):  
Big Data ◽  
Intelligent Transportation Systems ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Intelligent Transportation ◽  
Transportation Systems

scholarly journals Streaming Big Data Analytics- Current Status, Challenges and Connection of unbounded data Processing platforms

2019 ◽  
Vol 8 (9S2) ◽  
pp. 698-700
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
High Speed ◽  
Big Data Analytics ◽  
Current Status ◽  
Data Sets ◽  
Huge Data ◽  
Timely Fashion ◽  
Iot Devices ◽  
Streaming Big Data

A strategy of examining immense dimensions of structured, un-structured, Semi-Structured data sets is referred as Big data Analytics. Streaming Big Data refers to data generated continuously from number of data sources like Internet-of-Things (IoT) devices, mobile applications, Embedded Sensors, web clicks and many more are needed to be store, processed and analyzed in a tiny interval of time in order to extract meaningful insights and take proper decisions in a timely fashion as the necessity arises. However analyzing streaming big data (continuous flow or unbounded data) is a very challenging problem. Continuous data streams have become essential prerequisite for numerous industrial and scientific applications, the current existing technology Hadoop-MapReduce is not appropriate for stream processing of big data. This paper discusses the challenges and benefits of streaming big data along with its architecture, and focuses on different open source streaming processing platforms that are existed to process the huge data at a high speed

Distributed Streaming Big Data Analytics for Internet of Things (IoT)

2018 ◽  
pp. 303-338 ◽  
Author(s):  
Sornalakshmi Krishnan ◽  
Kayalvizhi Jayavel
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Real Time ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Cloud Services ◽  
Sensor Data ◽  
Efficient Processing ◽  
Streaming Big Data ◽  
The Internet Of Things

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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