SYSTEM ARCHITECTURE- stand alone network with cloud


The ReMaster system collects local data streams on the Tridium platform at the industrial site location.  These streams are pushed to the cloud through a data gateway.  This data is then analyzed using rules based artificial intelligence algorithms. System anomalies are generated and distributed to analysts and customers that can take appropriate measures.  Since data and information are stored, analyzed and viewed in the cloud, there is no need to have access to the industrial site thereby solving firewall issues.

SYSTEM ARCHITECTURE- on premise using dcs or bas


The ReMaster system has the ability to interface with an on-premise data historian generated by a DCS or BAS. The data can be communicated using an industrial protocol interface such as OPC, MODBUS, or HTTP at the industrial site location to the Sparks Analytics Engine running on a local server. This data is then analyzed using rules based artificial intelligence algorithms. System anomalies are generated and distributed to analysts and customers that can take appropriate measures.  

Virtually Analyzing Change

Data Acquisition and analysis


The ReMaster system analyzes time series data streams on the Sparks Analytics and Data Management Software Platform. This data is analyzed using rules based artificial intelligence algorithms that identifies inefficient operating patterns and potential equipment operating problems. System anomalies are automatically identified by the software and distributed to analysts and customers that can take appropriate measures. Stand Alone Cloud Systems, On Premise Server Systems and Hybrid System Architectures are options.

SYSTEM ARCHITECTURE- hybrid using dcs or bas


The ReMaster system has the ability to interface with an on-premise data historian generated by a DCS or BAS.   The data can be communicated using an industrial protocol interface such as OPC, MODBUS, or HTTP at the industrial site location through a data gateway to the Sparks Analytics Engine running on a cloud server.  This data is then analyzed using rules based artificial intelligence algorithms. System anomalies are generated and distributed to analysts and customers that can take appropriate measures.