June 3, 2016 | Written by: Chris O'Connor
Categorized: Article | Blog
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Today, in a typical industrial deployment, only 1% of IoT data is actually analyzed. This is because of legacy processes and drawbacks in current IoT platforms that make it too expensive and slow to analyze the other 99% of data Let’s take a look at a typical oil platform to understand why most data goes unused.
Oil and gas data loss
The illustration above shows that not only is it difficult to pull in data, making sense of the data and figuring out how to use it is also a challenge. The good news is there is so much valuable data – if you can figure out how to harness it, there are nearly unlimited possibilities.
Enter edge analytics. A solution that helps to address the deluge of IoT data by distributing analytics to the edge, or very close to it. Enterprises can harness the intelligence of the myriad of smart devices and their low cost computational power to allow them to run valuable analytics on the device itself. Multiple devices are usually connected to a local gateway where potentially more compute power is available, enabling more complex multi-device analytics close to the edge.
Even more powerful in many cases, edge analytics are more than just operational efficiencies and scalability. Many business processes do not require complex analytics and therefore the data can be collected, processed and analyzed on the edge to drive automated decisions. Cognitive IoT can infuse these edge analytics with intelligence to make devices environmentally aware and able to react in real-time.
Cisco and IBM
Cisco and IBM are redefining the network with an intelligent platform through Cisco’s leadership in the market; and enabling a hybrid approach to IoT analytics at the network edge or in the cloud through IBM’s Watson IoT Platform. Together we are delivering a first of its kind solution that creates the ability for customers to analyze business performance at the point of data collection; so they can tightly control how their environment, assets and people are performing against their mission. Structured and unstructured forms of data such as video and auditory are monitored for changes relevant to risk. Corrective actions are driven based on analytic evaluation based on business rules defined by the enterprise. Analysis performed at the edge is used to perfect performance models in the cloud, continuously learning and perfecting operating condition models. Analysis of data at the edge of the network frees capacity in transmission and drives down costs of communications for remote monitoring.
Businesses can now achieve new levels of competitive advantage by tapping previously unconnected data, empowering decisions at the point of data collection. This solution will enable dynamic distribution of data processing and analytics with performance-critical computation for applications/data center functions at the very edge of the network. Allowing you to respond to one machine, while continuing to learn from data from all machines, on a single IoT platform.
Check out this webcast, to hear leaders from IBM and Cisco discuss this first of its kind solution enabling immediate analytics on IoT data at the edge of the network. And be sure to find out how you can get started with this new solution.