Machine learning in low-power devices brings sound recognition to the smart home market

The Smart Home market is now at an inflection point. Early devices in the market were connected to the internet but were typically single-function, often lacking connectivity to other devices and with closed APIs, denying the user the ability to design multi-device applications around smarter living use-cases.

The first wave

The first wave of Smart Home assistants such as Amazon Echo and Google Home are now in the market. They combine artificial intelligence and speech recognition to deliver new services and manage other devices within the home. Their arrival and accessible price points are rapidly moving the Smart Home experience from early adopter to mainstream adoption.

The popularity and familiarity of voice assistants on mobile has transferred to the Smart Home ecosystem and voice has quickly become a standard user-interface for Smart Home assistants and devices. Once a Smart Home assistant is adopted within the home, homeowners are more inclined to purchase other smart devices they can incorporate into their home and manage through their assistant.

OEMs and the market opportunity

Increasingly, Original Equipment Manufacturers (OEMs) are responding to the growing market opportunity by seeking ways to transform low power single-purpose devices into low power-multi-purpose devices, connected to the wider Smart Home ecosystem. Consumers are also looking for ways to make traditionally “dumb” unconnected devices such as smoke alarms smarter, but without incurring the cost of replacing existing units with more expensive, connected versions. Hence industry analysis firm IHS predicts a significant growth of the Home consumer IoT device market over the next years and expects above 1 billion in unit shipment worldwide by 2025.

Download the white paper

This white paper addresses how artificial intelligence and machine learning are used in the Smart Home market focusing on sound recognition. We will describe use cases and requirements across several end-device categories and how Audio Analytic’s embedded software platform Artificial Audio Intelligence (ai3 ) can be used on low-power ARM Cortex processors.

Download white paper

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