Machine learning has introduced new capabilities and applications relevant to embedded systems that offset the development costs and considerably reduce the programming overheads.
FREMONT, CA: Over the past few years, incorporation of machine learning (ML) in the embedded systems is gaining momentum. Till recent, ML was beyond the reach of the resource-constrained microcontrollers that embedded developers work with. But what role ML plays in embedded systems? Here are a few potential use cases:
• Embedded devices are increasingly using ML algorithms to solve problems that are traditionally difficult for developers to code. For instance, hand-coding, a code required to detect what was written in a range from 0 to 9 on a 28X28 pixels image is complex as writing a digit will not result in an identical image. Thus, the hand-coding may result in coder starting at a different place, or writing the figure on an angle, or any other variation. However, with ML, the same task can be accomplished within a few hundred lines of code or less.
• Some tasks are easy for humans but difficult or expensive for a computer. ML can support humans while dealing with such tasks. One such example is object detection and recognition, which is simple for humans but extremely difficult for a computer. With ML, it is possible to create digital assistants who can recognize keywords and detect objects on an assembly line or in the way of a drone or a rover.
• ML can enable the developers to scale their systems into new situations without the need for the developers to modify the code to add new behavior. Indeed, ML can eliminate the need for any manual interference with the system code. The ML model requires to be retrained with the desired actions, and they can scale the systems as per the new requirements.
New features and applications relevant to the embedded systems are available due to ML that offset the development costs and considerably reduce the programming overheads. As of now, embedded systems are ready for the next level of design, incorporating other technologies that are already transforming several industries across the globe.