The internet of things is transforming how we work and live. By 2030, the number of connected IoT devices worldwide will jump 12% on average annually, from 27 billion in 2017 to a staggering 125 billion in 2030. This means that there will be nearly five times more devices and sensors to manage, each of which is producing a vast amount of data.
These intelligent devices are expected to have an average 10-year life span, so organizations need a way to test and monitor the performance of each device through the duration of the deployment. To attempt to manually test the software once in a controlled environment and hope that everything will work is simply not going to fly.
This is especially true in industrial settings, where the impact of a software update can have a negative effect on the business and, in some cases, produce catastrophic results. There is no margin for error when updating the software on a remote smart irrigation system, for example, or even more critically, with a sensor that measures pressure in a gas pipe. These scenarios illustrate the importance of ensuring that the software update works before rolling it out. To do this requires continuous testing and monitoring of smart devices.
Take the example of a field irrigation system on a remote farm, where a worker only visits once a year. There needs to be a way to ensure that the software update has worked and that the fields are receiving the correct level of water based on soil, weather and other variables. To do this requires testing and monitoring the entire ecosystem continually in a real-world setting before pushing out updates. Once the release goes live, there must be continuous monitoring of the performance to ensure that the device continues to deliver as expected in a dynamic environment.
Digital twins will play a key role here. Essentially, we need to create digital twins of the real production environments, constantly update these based on information from production and then test against the digital twins to ensure that updates are going to work effectively in the massively diverse environments into which IoT systems are deployed.
With the rapid growth in IoT, dynamic continuous testing and monitoring must become the norm to assure constant quality. As the digital and physical worlds continue to blend, those organizations that adopt continuous testing will be able to deliver a flawless experience and reap the benefits from the surge in data created by IoT.
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