Ensuring the quality and safety of life-saving vaccines, medications, and other healthcare specimens require strict temperature monitoring and control to maintain product integrity. The solution combines Emerson’s expertise in environmental monitoring and the behind-the-scenes refrigeration network known as the cold chain with HID Global’s broad spectrum of connected health systems and Internet of Things solutions, enabled by Bluvision. This collaboration is providing first-of-its-kind monitoring solutions for the healthcare industry.
“Helping our customers monitor and improve safety and health is a cornerstone of our business and mission, and we’re proud to bring these solutions to the industry,” said John Rhodes, group president of cold chain for Emerson’s Commercial & Residential Solutions business. “This strategic partnership allows Emerson to extend our leading sensing and connected technologies to help healthcare providers optimize their operations and protect their life-saving treatments.”
The solution combines automated alerts, audit trails, condition monitoring and location services for a more advanced approach to medical-grade temperature monitoring using Internet of Things technologies. Leveraging HID’s Location and Condition monitoring network services based on Bluetooth Low-Energy (BLE), the solution delivers enterprise-wide pervasive connectivity, linking active personnel badges with both temperature and vibration sensors to allow rapid and cost-effective deployments at scale.
“Combining HID’s BLE network with Emerson’s environmental monitoring sensors brings together best-in-class products to help healthcare providers monitor temperature-sensitive assets as part of an IoT stack that healthcare institutions can easily integrate into existing workflows,” said Rom Eizenberg, VP at Bluvision, part of HID Global. “Hospitals can quickly increase patient safety, the quality of care and pharmacy workflows while enabling more advanced capabilities like the construction of Health System Digital Twins to better predict, model and extract further efficiencies.”