The quantity and the granularity of data provided by SmartCim System, beyond imagination just a few years ago, represent by itself a huge step ahead in HVAC systems management. Data visualization allows users to acquire a different level of awareness of behaviors and consumption and create a behavioral change in usage patterns.
Thanks to SmartCim, the HVAC system provides extremely detailed information about its different areas, delivering detailed and real time description of its functionalities, a goal that before today was believed to be unreachable at reasonable costs.
With SmartCim System, this level of detail is provided automatically and therefore we can visualize and analyze each single thermodynamic parameter in order to optimize the system performances and to achieve energy savings that are above 30% in the current pilot installations.
This huge step ahead in systems performances is just a first step. The availability of such a large number of real time data allows to redesign completely the HVAC systems management processes and to implement new and more advanced functionalities, impossible to implement until now.
In order to be able to extract as much intelligence as possible from this huge amount of information, Cimberio has selected mnubo, the leading Internet of Things (IoT) Data Analytics company, to provide actionable insights and advanced IoT analytics for the SMARTCIM system.
Through this partnership, mnubo will provide its SmartObjects solution – purpose-built Big Data analytics platform, Artificial Intelligence algorithms and IIoT expertise to enable real-time analysis, anomaly detection and preventive maintenance use cases; these insights will help plants cut energy management costs and reduce harmful emissions.
There is an ongoing effort to collectively reduce energy consumptions and CO2 emissions, with already-standing buildings accounting for nearly 50% of worldwide energy usage. By retrofitting these buildings with the SMARTCIM system powered by mnubo’s IoT insights will result in significant efficiencies and furthermore, provide an unparalleled amount of information and insights for real-time decision making.
The system generated data will automatically issue alarms in case of faults detection and will implement predictive maintenance. New user cases can be developed so that a revolutionary approach to heating and cooling can be realized, significantly decreasing energy consumption.