Here's what it takes to make IoT data ready for AI and machine learning

The integration of artificial intelligence and the Internet of Things introduces a wide array of connected health tools that produce a vast amount of data that must be synthesized, analyzed, stored and communicated by a robust information infrastructure. But if hospitals don't structure and store IoT patient data properly, that information could be rendered not assessable by AI tools. For starters, significant infrastructure is needed to streamline IoT-generated data to make sure it is simple to assess and manage with AI. "AI adoption and scale will be accelerated by the relatively low cost of deployment," said Rick Krohn, president of HealthSense, a connected health consulting firm. "A terabyte of storage costs less than $100, and wearable sensors and cloud infrastructure are becoming increasingly affordable. But AI requires sophisticated applications that deliver contextually aware right-place-right-time clinical decision support."