As IoT continues to cross the chasm, we see new business models emerge that bring about the deployment of infrastructure and services. As IoT continues to be at the heart of digital transformation, how IoT gets deployed is being reimagined. This panel reveals the opportunity to innovate new equipment strategies and "As A Service" solutions.
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ML applications have never been easier to build. Whether cloud or edge-based, developers have a number of tools at their disposal for adding machine intelligence to buildings and cities. But as our smart city systems become more sophisticated and capable and a dependence on the cloud increases, the need for privacy grows, and every embedded system should be designed with privacy in mind. Thankfully, there are advances in the ML and communications space that prioritize privacy, by default, including edge-based ML inferencing and cellular for cloud connectivity. With edge-based ML, decisions happen on devices instead of the cloud. And with cellular connectivity, edge systems send only the results of ML processing to the cloud, as opposed to potentially private or sensitive raw data. When used together, these two approaches help developers build smart city applications that are secure by default.
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