One of the big promises of the Internet of Things (IoT) is understanding the physical world around us and taking action based on insights and observations.
Over the last decade, we’ve gotten really good at the first part, using smart devices and sensors for monitoring and data collection. We have sensors everywhere, in consumer products, on the floor and embedded in manufacturing and industry, distributed across nature and remote areas of the world—always on and always streaming new readings as they happen. This has transformed our understanding of how we work and live because we have more up-to-the-second data and analysis than ever before.The next area ripe for innovation is what we do with that data. We’re beginning to see more artificial intelligence (AI) / machine learning (ML) implementations in IoT that better process massive sets of data and derive insights. This has allowed businesses across a wide variety of verticals to increase efficiency, make better decisions and predict future performance more accurately. And with the leaps and bounds made in processing and analysis, the underlying data infrastructure technology has also grown. With a vast flow of data, immense advances are being made in optimizing the machines and networks that deliver the massive streams or individual pieces of data where they need to go.
That’s critical, since every second matters in the world of IoT. Indeed, every millisecond counts. Companies are taking advantage of this instantaneity to the benefit of all.
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