We’ve grown accustomed to our devices becoming more intelligent, recognizing and interpreting voice and movement through advanced audio and video processing techniques as well as sophisticated sensors. Say “Hey Google” or wave a hand and our devices not only respond, but often serve up preferences they have been trained to offer. Welcome to the era of Smart IoT Edge devices.
These smart devices have become ubiquitous and their capabilities expected: speakers with voice control that utilize highly accurate speech recognition from an extensive vocabulary of trained voice commands; wearable activity trackers that recognize human activity such as sitting, standing, walking and running based on input data from sensors like gyroscopes, accelerometers and magnetometers; smart camera-equipped doorbells, performing facial recognition and triggering an alert that can be sent to the owner’s mobile device with an image or video; even self-driving cars, applying advanced computer vision techniques to detect vehicles, pedestrians and hazardous driving conditions.
At the core of this evolution are increasingly powerful and sophisticated machine learning techniques that have become more widely adopted to make our systems more contextually aware and responsive. Machine learning technology that has been trained to recognize certain complex patterns (e.g., voice commands, human activity, a face, pedestrians) from data captured by one or more sensors (e.g., a microphone, a gyroscope, a camera) bring new levels of safety and convenience to our lives. When a pattern it is trained to recognize is sensed, the device can respond accordingly. For example, when the voice command “play music” is recognized, a smart speaker can initiate the playback of a preferred song.
The advent of more powerful neural networks and algorithms has allowed the evolution of machine learning-powered devices that learn without being explicitly programmed. However, the promise of greater automation and intelligence that machine learning enables, particularly in consumer devices or other applications that operate at the edge, is limited by power consumption.