How AI Has Changed the Game in RTLS

Five years ago, even the most cutting-edge real time location system (RTLS) technology required hospitals to accept a trade-off. Hospitals could opt for a highly accurate RTLS, but the system would require heavy infrastructure, a lengthy installation, and a hefty price tag. Or hospitals could choose a less expensive system that ran on lighter infrastructure and a Wi-Fi network, but the RTLS would deliver less accurate, less actionable data.

Real time location solutions built on these older technologies have largely failed to deliver the ROI that hospitals were promised when they signed their contracts years ago. Because of those failures, many hospitals today are skeptical that an RTLS can provide meaningful value to their bottom line.

But technological advancements over the past half-decade—specifically, the maturation of AI and machine learning—have given rise to a new wave of RTLS solutions. These solutions don’t ask hospitals to sacrifice quality for price, and they can provide a faster, more reliable path to ROI than their predecessors.

A real time location system with less disruption

An AI-powered RTLS puts the “brain” of the solution in the cloud, simplifying the infrastructure required on-site. These solutions don’t need wires to be pulled through the ceiling or equipment to be installed in every room. Instead, AI-powered RTLS solutions typically include four parts:

  • Beacons securely installed at infrequent intervals in and around the hospital.
  • Tags, which are attached to all mobile medical equipment.
  • Gateways, which are wireless receivers (typically installed one per floor) that send the tags’ data to the cloud-based platform.
  • The cloud-based platform (the “brain”), which uses machine learning algorithms to compare the information it receives with a reference network of the facility.

The lightweight infrastructure of an AI-powered RTLS is quicker to deploy than solutions built using older technology. That means hospitals can have a system up and functioning within weeks with minimal disruption to clinical activities.

The machine learning algorithms in the cloud-based platform are trained during a walkthrough of the hospital, creating the reference network that helps to pinpoint the tags’ location. These algorithms enable high-confidence accuracy not only in patient rooms but also in open spaces like corridors, atriums, and waiting rooms. The real time location system can even cover parking lots, garages, and pathways leading to and from the hospital.

Adding operational benefits with AI-powered RTLS

Such high-confidence accuracy enables a slew of operational benefits for hospitals, including:

If you’re reading this, your hospital may be considering investing in an RTLS for the first time—or you’ve already invested in a solution that’s not working and want an upgrade. In either case, you’ll want to choose an affordable solution that stays accurate over time, unlike other systems that can lose accuracy when the hospital’s environment changes.  AI can adapt and learn the environment rather than suffer from the accuracy decay common with non-AI powered solutions.

Using AI as its engine for accuracy, the Cognosos real time location system is at the forefront of this technological shift. In 2023, Jamaica Hospital Medical Center in Queens, N.Y. implemented our AI-powered RTLS.  “We’ve already been contacted by some other hospitals who have embraced the older tracking system technologies and are now considering replacing them,” says Nabil Ibrahim, Director of the Biomedical Engineering and Asset Management Department at JHMC. After a successful first phase, the medical center is now expanding its use of Cognosos’ AI-powered RTLS. “We’re really on the right track.”

Learn more about how Cognosos’ AI-powered real time location system is delivering value to JHMC in this case study. To see how the Cognosos RTLS can bring similar benefits to your hospital, get in touch.

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