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<p>IoT implementations produce all different types and frequencies of data. Some generate low volume, high value data, and others generate very high volume data streams that become valuable when they are processed and analyzed. For these types of applications, the data processing solutions need to be able to store and analyze this large volume of data quickly and efficiently. One solution for this use case in the <a href="wot.io">wot.io</a> <em>data service exchange</em> is <a href="http://www.ngdata.com/">NGDATA</a> and their <a href="http://www.ngdata.com/products/lily-3/">Lily</a> big data toolset.</p>
<p>At wot.io, we deliberately define IoT in the broadest sense when we think about data processing solutions. For us, any device in the field generating data is suited to an IoT data solution. These devices can be traditional IoT like sensors on a tractor or a machine in a factory or a shipping container, but they can also be a set-top box delivering media and processing user preferences to create a better user experience. One such stream of data is that compiled by our data exchange partner at <a href="http://www.criticalmention.com/">Critical Mention</a> where they process media streams in real-time and provide a rich data feed of activity across radio and television broadcasts. Although some may not consider this a typical sensor IoT scenario, this is exactly the type of high-volume data feed wot.io partner solutions are built to handle.</p>
<p>In one implementation, we worked with our data service partner NGDATA to offer a Hadoop and Solr based big data data service and then routed a sample Critical Mention data stream to it. We were then able to query the live data for a variety of information that users might find interesting like trending topics, brand mentions, and the times and frequencies select issues are discussed. Other partner services, like those provided by <a href="http://www.apstrata.com/">Apstrata</a> now named <a href="http://www.scriptr.io/">scriptr.io</a>, could also be applied to search and process the data from Lily. This video gives an overview of how we did it.</p>
<p><iframe src="https://www.youtube.com/embed/RQ0z48qkijI" frameborder="0" width="420" height="315" allowfullscreen="allowfullscreen"></iframe></p>
<p>NGDATA's Lily toolset also has a set of user interfaces provided as part of the solution. You can get a feel for those tools below.</p>
<p><iframe src="https://www.youtube.com/embed/WaZyGPv4hp4" frameborder="0" width="560" height="315" allowfullscreen="allowfullscreen"></iframe></p>
<p>The examples in the video are designed and configured for banking, media, and telecom verticals, but you can imagine trending and alerting applied to the Critical Mention data product, or even industrial use cases where trending is monitored for tracked devices, machines, or vehicles out in the field.</p>
<p>This application of existing data services like NGDATA to IoT data streams, with the broadest definition of IoT, is what excites us at wot.io. The broad set of data services in our exchange bring both industry-standard and innovative solutions to IoT projects of all types.</p>
<p>wot.io is an authorized partner with Critical Mention to add value to the Critical Mention broadcast data stream. If you're interested in access to the Critical Mention data stream please contact us at: <a href="info@wot.io">info@wot.io</a></p>