IoT and AI are two of the hottest acronyms around, each significant in its own right. But combine the two, and the results are even more astounding.
By some estimates, there will be more than 80 billion connected things producing more than 180 zettabytes of data annually by 2025. Bolder predictions have their sights set on IoT devices creating 847 zettabytes of data by 2021. Either way, it's a large number -- and one that is only going to grow.
All this data will lead to insights that will revolutionize business processes, save money and help enterprises create new products and services, but the only way to get there is with a little help from IoT's friend, AI. With AI, companies can process, parse, analyze and act on real-time IoT data. This capability is integral for IoT uses such as autonomous vehicles, smart supply chains, connected factories and smart buildings.
It's important to note, however, that IoT and AI are still nascent -- and complex -- and there are many considerations to keep in mind when deploying them individually or in tandem. Beyond the sheer complexity and volume of data collected and analyzed, companies must contend with issues such as latency, power and security.
This handbook outlines the benefits of the power duo before diving into best practices for deploying AI and IoT at the network edge. Then read how another hot technology -- blockchain -- just may be the solution to the AI and IoT edge deployment security challenge.
