Industrial automation is changing how organizations do business, and driving OT/IT network convergence at a high velocity. By next year, over 50% of industrial IoT analytics will be performed at the edge – closer to where the data originates – up from just 10% in 2017. Not only are organizations deploying more IoT devices to gather this data but they must also now think about how to manage it. In fact, Gartner reports that by 2022, more than half of all enterprise data will be processed outside of the datacenter.

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Cash-In-Transit vehicles are the critical fleets for financial institutions, as they transport valuable assets like cash, jewelries and other valuable assets. Therefore, it is a mandatory procedure to reduce the risks of robbery, theft and unidentified personnel, while securing the vehicle and the assets in it. In fact, it is believed that a 4G/LTE-based networked surveillance is currently the most optimal and real-time solution for the security of cash-in-transit.

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Intelligent surveillance solution is one of the most widely adopted AI applications as it can be deployed for a broad range of use scenarios, delivering advanced video analysis with deep learning for almost all vertical sectors. Before they can leverage the benefits such as AI-enhanced detection accuracy and flexibility, however, businesses and organizations must overcome a significant numbers of challenges before and after a deep learning model is trained because AI-powered video surveillance solutions rely on visual data capture for analyzing/solving security, safety, and operations challenges; and such reliance demands simultaneous analysis of vast volumes of video footage.

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As the demand for network bandwidth continues to accelerate, telecom operators are constantly challenged to meet client needs driven by video streaming, additional devices, and the cloud. Carriers can now meet those needs with netElastic Virtual Broadband Network Gateway (vBNG) software and white box servers from Lanner.

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The introduction of smart grid has revolutionized the conventional approaches of electrical grids in supplying and distributing electricity. Smart grid offers enhanced data communication and automation for power grid so that data regarding power generation and distribution can be collected and analyzed in a near real-time synchronization. Besides the technological benefits, smart grid offers the visibility of all the integrated subsystems and provides predictive information to the control center. The convergence helps critical infrastructure owner to save operating and capital expense.

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