Illustration of cloud-connected servers representing the Glassbeam data analytics platform

Data Analytics by Glassbeam

Glassbeam has innovated a simplified approach to a complex IoT big data problem by inventing a patentable language called SPL (Semiotic Parsing Language). SPL drives a 10x efficiency in the data transformation process by allowing a solutions engineer to perform the same work in a week or less as is done in 6 months by a team of database and system engineers.

Overview

Glassbeam has innovated a simplified approach to a complex IoT big data problem by inventing a patentable language called SPL (Semiotic Parsing Language). SPL drives a 10x efficiency in the data transformation process by allowing a solutions engineer to perform the same work in a week or less as is done in 6 months by a team of database and system engineers. The company has filed patent applications in this area. Besides SPL, Glassbeam has invented a real time streaming platform called SCALAR, that can convert complex machine logs into actionable output using a complex rules engine, machine learning Apache Spark, and the latest innovation with a tool called Glassbeam Studio that allows rapid data modeling on complex log files. Core platform is coded in SCALA with a backend data store in Cassandra & Solr Cloud, all tightly engineered for hyper scalability, multitenancy, and security.

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Remote Monitoring

Uses Glassbeam’s CLEAN™ (Clinical Engineering Analytics) blueprint for connecting systems from all key manufacturers including GE, Siemens, and Philips. Data is collected on 30+ key readings including cryogen levels, cold head temperature, magnet pressure and scan counts, aborts, and arcs for MRI and CT modalities, respectively.

Desktop monitor and laptop displaying Glassbeam data analytics dashboards with system health and utilization reports

Real-time Environmentals Monitoring

Provides dashboard and/or alerts to monitor Compressor Power, Room temp/humidity, and Chiller water temp In/Out. Additional sensors could be added based on customer needs especially to monitor mobile units in remote locations.

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