How to choose a cloud IoT platform

IoT, the Internet of Things, is currently one of the most hyped concepts in the computing world. Cloud IoT platforms may even exceed IoT on the hype scale. Nevertheless, both have real applications and could become important to your business. In this article we’ll define IoT and cloud IoT platforms without too much technical detail, then discuss what you need from a cloud IoT platform and how to choose one.

The simple explanation of IoT is that it is physical things connected to the internet. These things can have sensors that measure various parameters and send their data over the internet, typically back to a remote or “edge” server located in the same geography. Internet things can also take directions via the internet and act on them. Most usefully, the physical things that make up IoT might both send measurements and receive instructions.

For example, a “smart” internet-connected soil moisture sensor could report its readings periodically, and whenever the soil in a field was too dry an internet-connected water valve could open. When the soil moisture was adequate, the valve would close.

The moisture sensor and the water valve might be connected to the same “edge computing” device or node that talks to the internet, or they might be connected to different nodes, since many soil moisture sensors are likely to be used for a large field, while only one centralized irrigation system would be needed for each field.

How does IoT relate to the cloud?

“The internet” is not an endpoint, of course, but an interconnected collection of networks that transmit data. For IoT, the remote endpoints are often located in a cloud server rather than in a single server inside a private data center. Deploying in a cloud isn’t absolutely necessary if all you’re doing is measuring soil moisture at a bunch of locations, but it can be very useful.

Suppose that the sensors measure not only soil moisture, but also soil temperature, air temperature, and air humidity. Suppose that the server takes data from thousands of sensors and also reads a forecast feed from the weather service. Running the server in a cloud allows you to pipe all that data into cloud storage and use it to drive a machine learning prediction for the optimum water flow to use. That model could be as sophisticated and scalable as you want.

Copyright © 2020 IDG Communications, Inc.

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