Founded in 2017, Eniware Open Source started as a collaboration initiative between Lagoni Engineering - an UK consultancy company and Technical University in Garbovo. This partnership produced number of successfully implemented projects at national critical infrastructure sites in the UK.
Innovation and new technology focused on the Industry 4.0 paradigm lie at the heart of what Eniware Open Source does. In addition, collaborative working relationships which focus on long term value, enable us to co-operate effectively with external organizations – a key aspect of delivering success in an innovation-led environment.
Our methodology is to first identify a requirement, then assess the need, purpose and objective followed by an analysis of available possible solutions. Only then are we in a position to define a solution, considering aspects of functionality, operation, availability or restrictions of equipment on a particular site or project, and its ability to adapt and accommodate future potential requirements.
This is where we apply our innovative thinking and address solution definition and subsequent delivery to meet the identified need, not force a pre-packaged system to fit a purpose. In doing this, we can ensure vital aspects including reliability, cyber security, robustness, inter-connectivity, safety and quality are at the heart of a solution, not added at a later stage.
Eniware Open Source operates at the cutting edge of Industrial Internet of Things through close integration of open source technologies with our in-depth industrial knowledge and engineering skills. We aim to revolutionize the Industrial Internet of Things (IIoT) market and drive value out of assets through data analytics.
We utilize a combination of open source technologies, containerization and powerful Edge computing devices to develop:
· Cyber-secure and vendor agnostic SCADA platform
· Intrusion detection system for TCP IP networks
· LoRaWAN based communication channels
· Data acquisition, secure transmission, distributed storage and analysis based on the state of the art machine learning (Sensor-to-Cloud)
· Forecasting software for renewable energy generators (photovoltaic and wind power) based on numerical weather prediction model
· Optimization modelling for reduction of CO2 and reduction of energy costs in discrete manufacturers or continuous processes.