San Francisco, California--(Newsfile Corp. - September 21, 2021) - Technology industry leaders Phizzle, Cisco, Intel, and Glasshouse Systems announced today that they will work with the University of Miami Institute for Data Science and Computing (IDSC) to identify ways to use lab-grade cleanroom technology and data analytics in traditional campus buildings, as a way to monitor air quality in real-time.
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Tech industry leaders will explore ways to ensure student, faculty and staff wellness on the University of Miami campus.
The Collaboration leverages innovative IoT edge technologies pioneered in pharmaceutical manufacturing, where safety is a requirement.
Phizzle's EDGMaker software will be used with lab-grade particle counters to measure air quality inside and outside university-designated buildings.
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Phizzle's EDGMaker is the only SaaS-based IoT solution to remotely operate multiple scientific instrument brands and systems from a single, cloud-based user interface - harmonizing the control and integration of data from these heterogeneous devices into automated workflow systems. Phizzle's EDGMaker creates the most customer value in regulated or compliance use cases for pharmaceutical manufacturing, food production and cleanrooms.
Phizzle' is the only IoT solution to remotely operate and automate multi-vendor particle counters for scientific data applications. The EDGMaker software stack offers fully digitized testing and compliance processes to reduce labor, human error, and wasted batches in regulated manufacturing. The core innovation in the company’s enterprise-class software stack is Regenerative Engineering, which solves the power and data complexity challenges typical of edge computing in an entirely new way. Phizzle’s EDGMaker benefits many pharmaceutical, smart manufacturing, food production, healthcare ICU systems, and smart cities initiatives around the world. The company's go-to-market partners include Cisco. Founded in 2005 and headquartered in San Francisco, Phizzle has a history of creating innovative products from consumer data to machine data.
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