Vidcentum Energy



Provides a collection of open source libraries, frameworks, languages for smart meter connectivity, IoT, data processing, rule engines, telemetry and integrations at the IoT Edge Gateways and Mobile Apps. It serves as overlay for widely used energy software such as EnergyPlus and OpenStudio.

Picominer® Computing Platforms
  • Android (ARM64).
  • Single board Linux computers.
  • Cloud/On-Prem servers.
Field Devices/Smart Meters Connectivity

It supports a wide range of device connectivity protocols: IEC62541 (OPC-UA), MODBUS/TCP, IEC61499, IEC61850, IEC62056 (DLMS/COSEM), MQTT, BACnet, CAN, SPI, I2C, RS-485, UART.

The platform has support for Websockets, SocketIO, REST APIs, ZeroMQ, XMPP, SNMP, RDF, SPARQL etc., to connect with data sources (logical assets).

AI/ML At The Edge

The platform provides access to several AI/ML libraries:

  • Expert Systems to execute business rules.
  • Classification, Regression, Clustering algorithms.
  • Linear programming and optimization.
  • Time series analysis.
On-Premises/Self-hosted Deployment

Data collected is stored, processed and archieved locally. Low dependency on off-premises servers unless the system desing requires.

Accouting At The Edge

The platform provides access to libraries for conducting quantitative analyses that assess energy consumption.

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Rapid Solution Development

Picominer® platform provides a suite of libraries for efficient data processing, advanced analytics, and integration framework for the existing systems. It serves as overlay for widely used energy software such as EnergyPlus and OpenStudio.

Learning capabilities
Flexible deployment
  • Multiple data sources are combined and converted into a single format for analysis and storage.

  • Structured and unstructured data are both handled by reliable data storage and management components.

  • The platform incorporates standards-based frameworks for AI/ML algorithms for model interoperability.

  • A wide rage of open source and commercial software libraries are integrated into the platform blueprints.

  • Decision support components enable users to explore data, analyze trends, and make informed decisions.

  • The platform components support integration with external systems, such as CRM, ERP, or data APIs.

  • The platform handles data processing and analysis, ensuring scalability and performance.

  • The architecture incorporates standards based security measures for data protection and compliance.