Data Analytics by Glassbeam

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.

FEATURES

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.

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.