Part 1 of this series looked at how smart devices can deliver real value at a reasonable cost. Part 2 will cover different barriers to successful smart home design.
Barriers to Successful Smart Device Design
By understanding the barriers to designing smart products, OEMs can design devices for the smart home that will be successful in the mass market.
Ease of use
Early smart homes required a multi-stage commissioning process, starting with getting the device on the network, connecting it to the home ecosystem (i.e., Amazon Alexa or Google Home), and then configuring it. The more complex commissioning a device is, the more ways consumers can make mistakes, leading to a higher product return rate.
To succeed in the mass market, smart devices need to be plug-and-play. Technologies like Smart Start significantly simplify the commissioning process by allowing consumers to scan a QR code that connects the device to the home network and ecosystem in a single step. From a user perspective, commissioning becomes a much simpler scan-and-configure process. This results in a positive — and successful — out-of-box experience. It also makes adding multiple devices, such as a pack of eight smart lightbulbs, fast and easy.
Reduced maintenance
The smart home will be filled with sensors. Some sensors track temperature or ambient light in the home. Others measure soil moisture. Cameras detect motion to turn on lights when someone enters a room or to trigger an intruder alert. Medical devices track an individual’s heart rate, blood pressure, and oxygen levels.
Devices, however, also need to track themselves. Devices with batteries need to be able to alert users that batteries need changing. Medical devices need to regularly verify their reliability to ensure that the data they collect is accurate. Self-diagnosis capabilities allow users to have confidence that devices are taking care of themselves so that users don’t have to.
Artificial intelligence
Artificial intelligence is the primary technology behind implementing many of the advanced features that smart devices need to become capable of doing to provide high value to consumers. By identifying patterns and anomalies in data, AI enables the home ecosystem to decide what to do with the data it collects.
Consider a home safety system that uses video to monitor the outside of the home for when someone approaches the house. These systems use motion detection to determine whether an event is taking place that needs to be recorded or livestreamed to a user. A primary function of intelligence, in this case, is to eliminate false detections. A homeowner does not want to be notified every time a bird flies by or a car on the street backfires and sounds like a gunshot.
One important application of AI is facial recognition. New smart door locks use AI to decide who to allow into the home. Next-generation baby monitors will use facial recognition to determine if a baby has woken up. As companies continue to develop new AI innovations, more capabilities and new applications will become possible. For example, posture detection will alert parents as to whether a baby is sleeping on its back or not.
Development resources
Perhaps the most important barrier to smart device design is the integration of all the various technologies. Building even a simple proof of concept for a smart device could take weeks or months just to pull together the various components.
To accelerate design, engineers need access to a comprehensive development environment offering an array of development resources. In addition to software and design tools, silicon needs widespread industry support from third parties. With access to modules and application-specific reference designs and libraries, engineers can speed their evaluation of the various technologies available. This is especially important when designing with AI. AI models can be extremely complex to build from scratch. Working from a foundation provided by a third party can substantially reduce development time from months to days.
A silicon manufacturer’s development resources should also include services partners. For example, Silicon Labs provides chips and modules for the major wireless technologies. Its partners offer application software and other tools needed to build advanced applications such as smart door locks. A variety of leading AI vendors have already done the work needed to deploy their technology on Silicon Labs processors. Silicon Labs has also partnered with Arrow to provide compatible components like sensors and cameras, as well as design services to jumpstart new product development.
By understanding the barriers to designing for smart technology, OEMs can quickly develop smart devices that bring high value to consumers. Part 3 of this series will look at what it takes to deliver compelling smart products — and services — to consumers.