As I wrote in an earlier post, the Internet of Things is enabling enterprises to tap into vast new sources of value. A large part of that success stems from the rise of analytics techniques to sift, evaluate, and operationalize the massive amounts of data generated by IoT applications. The world of analytics moves fast; a great way to keep up to speed is to join us at HPE Discover 2018 Las Vegas, June 19–21. Here are three hands-on demos that will highlight IoT analytics capabilities and how they’re enhanced by Edge Computing (you can find the complete Discover content catalog here
Integration of Blockchain and video analytics for assembly line quality assurance (Session ID: DEMO1104). Quality assurance (QA) is an important element for manufacturers looking to continuously improve production processes. The complexity of today’s products and the move towards unique, customized configurations make traditional manual production processes slow and prone to error. Learn how you can leverage high-definition video, machine learning and object recognition to achieve faster and more accurate QA capability. We’ll also show how, by coupling this solution with Blockchain, HPE can deliver a secure, fully digital record of quality assurance and all other stages in the manufacturing environment – all of this done at the edge, where the data is being generated. For a preview of this, read Steve Fearn’s blog post that details how we do it at our own production facilities.
Deep learning video analytics on HPE Edgeline (DEMO1213). Artificial intelligence (AI) and deep learning (DL) techniques excel at extracting information and identifying what the algorithm has been trained to do. However, one of the biggest challenges with video analytics is the dependence on connectivity in order to send heavy video files to the datacenter for processing, which defeats the purpose of “real time”. But not anymore – in this demo, algorithms (running on any AI software platform) can process video data at the edge and extract the relevant metadata to send back to the command center, so that the user can easily focus on attributes of interest. HPE Edgeline Converged Edge Systems and NVIDIA Tesla general-purpose graphics processing units (GPGPUs), together with software from our ISV partners, form the perfect platform to do real-time secure video analytics and management at the edge.
AI meets IoT: HPE Digital Prescriptive Maintenance (DEMO1215). Remotely monitor the function and health of your manufacturing assets and take full advantage of the Internet of Things. By collecting and analyzing data directly from sensors in those assets, companies can generate real-time insights, automatically predict equipment failure and optimize actions to fix it. Hear how advanced analytics capabilities for IoT are disrupting legacy approaches to the maintenance process. You will see a specific use case based on HPE Edgeline platforms, partner solutions, and HPE Pointnext expertise.