Why You Need Contextual IoT Device Management

In addition to basic IoT device management, contextual IoT device management is necessary to ensure success when dealing with IoT solutions involving thousands to millions of devices.

In this post, I explore some of the key aspects of contextual IoT device management, with real examples that demonstrate why you need to manage devices contextually if you’re building, buying, and/or implementing massive-scale IoT solutions.

When building, buying and/or implementing IoT solutions, it’s critical to assume that devices are going to experience issues. The world is imperfect. Trying to make an IoT solution perfect is an impossible and foolhardy endeavor. If you have one million devices, all it takes is a failure rate of 0.1 percent, and you already have 1000 devices that will fail. For IoT solutions with devices expected to last for years in harsh conditions, the percentage of devices that will experience issues at some point increases dramatically.

Issues with devices can take many forms, including hardware defects in manufacturing, firmware bugs, device failures due to extreme temperatures or weather conditions, degraded performance from wear-and-tear, dying batteries—the list goes on. It’s therefore essential first to be able automatically to identify, and then be equipped to address issues, with IoT devices.

Let’s look at an example in which you have thousands to millions of devices in an agricultural setting. What happens when a device stops communicating? If there’s an issue with the device, you’ll want to replace that device with a new device. Alternatively, if the device’s battery is simply drained, you’ll want to replenish the battery in that device.

In either case, you’ll first need to know where the device is located. If the devices don’t have a GPS module, this means that when the devices are installed out in the fields, you’ll probably need to record their coordinates (latitude/longitude) as part of the installation process, so that you can visualize them in a user interface (UI). These installation and visualization capabilities would need to be included as part of the IoT solution.

In addition, it would be costly to replace or replenish individual devices, so instead, you should probably hunt down and address multiple devices at a time. Rather than replenishing drained batteries after they’ve already died (and thus have ceased to provide you with data), you’ll want to know which devices are getting close to being fully drained. But what does “close” mean? Where’s the threshold? Devices may be able to report the percentage of battery life remaining, but what does “10 percent battery life” translate into? A year? A few months? A few weeks? A day?

The rate of battery drain depends on usage, and usage depends on the use case. For a use case like agricultural IoT, the battery usage will likely be relatively consistent and, therefore, predictable.