Smart Meter radar-based home patient monitor

  • September 30, 2025
  • William Payne

Florida-based Smart Meter has launched an ambient sensor that uses radar technology to passively track patient vital signs, such as heart rate, respiration, movement, and bed exits, without requiring any patient interaction.

Smart Meter distinguishes its new iAmbientHealth system from conventional monitoring such as wearables or camera-based systems by emphasising its unintrusive nature for the patient. The company says it is designed to improve patient adherence, privacy and ease of use, which Smart Meter define as ‘the biggest barriers in remote care’.

Early adopters have reported significant improvements in patient engagement and outcomes, particularly among populations who resist wearable devices or struggle with cognitive impairments or physical limitations.

iAmbientHealth’s AI software provides data and insights to predict a decline in overall health status and emergent healthcare events up to seven days in advance.

In a study of over 200 patients, the proprietary algorithm predicted more than 75% of hospital transfers and reduced hospitalisations by 50%.

The sensor integrates with Smart Meter’s Smart Solutions Platform as well as EHR platform PointClickCare. This allows remote patient monitoring (RPM) companies, long term healthcare facilities, and other healthcare organisations to view ambient sensor data alongside other cellular-enabled vitals. The device is available as part of a flexible data service, with tiered packages that let customers tailor programs to their clinical and business needs.

iAmbientHealth qualifies for reimbursement under RPM and Chronic Care Management (CCM) CPT codes. It is already in use in skilled nursing facilities. It is now available for home use.

“iAmbientHealth is a game-changer,” said Casey Pittock, CEO of Smart Meter. “We’ve eliminated the need for wearables and cameras, giving providers a powerful tool that works silently in the background. It’s the future of remote care—private, predictive, and effortless.”