Sensing capabilities will be fundamental to the next generation of smart home automation and adoption, with 4.6bn sensors of various types predicted to ship embedded in smart home devices, robots and appliances by 2027, according to ABI Research.
This figure has jumped dramatically from the 1.8bn in 2021. Some of these sensors are already key to the functionality of devices, while others support additional functionality that will push into more products as manufacturers and service providers look to improve the appeal of their offerings.
The increased use of sensors enables smart home systems and consumer robotics to better match resident preferences alongside wider issues such as environmental impact and energy demand. However, the demand and comfort among consumers for how data is captured in the home will shape which sensing technologies win out.
“Our report examined 15 types of sensors, from motions and moisture to LiDAR and biometrics, and the technologies leveraged across them to determine which smart home devices and systems are best suited for which sensors,” said Jonathan Collins, smart home research director at ABI Research. “Alongside longstanding demand for microphones and image sensing, air quality, ambient light, water flow, and moisture sensing will all see significant adoption over the next five years.”
He added: “Smart home device manufacturers will have to determine which specific technologies will meet their system or system partner’s demands for functionality, cost, power demand, and more. A single sensor for something such as lighting levels or motion could be leveraged across a range of applications to support home environment management from automated lighting and window shading, heating, cooling and more.”
The upcoming Matter specification for device interoperability will further influence sensing data availability across smart home systems.
“The best-positioned sensor technologies will deliver detailed insights into the home environment without driving concern regarding resident privacy and control,” concluded Collins. “This will hamper image and biometric capture and favour lighter, less intrusive capture.”
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