The Internet of Things (or IoT) has revolutionized the way we think of computing.
In the past, computers were self-contained, general purpose machines that could load complex operating systems, run multiple applications, and perform a wide variety of tasks. They could communicate with one another in order to either share data or distribute workloads.
Now, tiny computers can be found in a huge number of devices around one's home or workplace. When these devices are connected to the cloud, they become far more powerful because much of the processing and storage traditionally done on the computer is moved to the massively-scalable cloud.
At home, refrigerators, thermostats, and automobile contain computers that send and receive information, making them better able to adapt to the world around them.
Businesses take advantage of devices connected to manufacturing machines or vehicles or weather detectors to monitor local conditions and productivity. Capturing data from these devices allows them to respond to anomalies in the data that may indicate a need for action. Imagine a monitor on a factory floor that monitors the health of an assembly line and sends an alert to a repair team if the line breaks down. Or, better still, if the data indicates a strong probability it will break down soon. Imagine a shipping company being able to track the exact location and health of every one of their trucks and to re-route them as necessary.
Industries as disparate as transportation, clothing, farming, and healthcare have benefited from the IoT revolution.
Cloud tools, such as Microsoft Azure IoT Hub allow businesses to capture data from many devices, store that data, analyze, and route it to a particular location or application. As applications become more complex, cloud tools become both more powerful and simpler to create.
These tools offer things like real-time analytics, message routing, data storage, and automatic scalability.
This IoT revolution has enabled companies to capture huge amounts of data. Tools like Machine Learning allow these same companies to find patterns in that data to facilitate things like predictive analysis.
The cost of both hardware and cloud services has fallen dramatically, which has accelerated this trend.
The trend shows no signs of slowing and companies continue to think of new ways to connect devices to the cloud and use the data collected.
The next series of articles will explore how to process IoT data using the tools in Microsoft Azure.