Our most popular stories of the year, from Apache Spark integration to predictive maintenance.
With 2015 approaching the rear-view mirror, we thought we’d take a look at some of our most popular stories on real-time analytics. Here they are:
Apache Spark and Storm have enabled extremely fast processing of Big Data and real-time analytics. However, DataTorrent CEO Phu Hoang argues that many organizations do not have the coding chops to successfully deploy and integrate Spark. He also argues that the capabilities of Spark across the application lifecycle are not ideal. Read more.
(For a different take, see “What’s Behind the Attraction to Apache Spark.”)
The Industrial Internet Consortium launched a collaborative Track and Trace (T&T) testbed, which seeks to develop the ability for manufacturers to remotely adjust the settings and tolerances of tools and machines used on a production floor. The effort, which is also being spearheaded by Bosch, Tech Mahindra and Cisco, makes it possible to automatically adjust tools and equipment in real time using WiFi. One possible use is aircraft maintenance, where the correct type of screw and torque is critical for repair work. Read more.
The days in which data analysis would take place at a central location are over, surpassed by the cloud, and now edge computing. Long before Dell announced its new Edge Gateway 5000 systems, Ryan Begley of IBM noted a number of applications where real-time analysis would be beneficial at the edge of the network: pipeline monitoring, oil and gas exploration, energy production, and hospitals. Yet, as Begley argues, central data analysis will still be part of the mix, and the trick for IoT applications is finding that balance. Read more.
There’s been a lot of hoopla about driverless cars, but this article surveys the landscape of what traditional car manufacturers and upstarts are doing with vehicles and components. The article highlights the state of the connected-car industry, including efforts from Google, Uber, Hortonworks, IBM, and others. Read more.
Predictive maintenance is one of the strongest use cases for real-time analytics for the Internet of Things. Industrial machines—such as a gas turbine, an aircraft landing gear, or manufacturing equipment—are highly costly to replace. With sensors hooked up to machines, however, it is possible to analyze real-time data streams and prevent a piece of equipment from failing. Under the umbrellas of the Industrial Internet Consortium (IIC), IBM and National Instruments (NI) are collaborating on an initiative called the Condition Monitoring and Predictive Maintenance Testbed, which intends to provide a cloud-based predictive maintenance solution which will offer continuous online measurements, automated analysis, and balance of plant coverage. Read more.
Want more? Check out our most-read content:
Research from Gartner: Real-Time Analytics with the Internet of Things
Frontiers in Artificial Intelligence for the IoT: White Paper
Data Visualization: How a Futures Exchange Sees Clearly
Video: Three Analytics Companies Explain Approaches
Three Types of IoT Analytics: Approaches and Use Cases
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