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on-board and central data recording, web and API access:
ensures the tracking and auditability of energy savings, costs and CO2 emissions


real-time tracking and data capturing
remote data access
user data security
data & savings visualization

The basis of the controlling process is the continuous monitoring and measurement of indicators, the creation and evaluation of data series and modelling the thermal characteristic of the system. Based on the real-time performance data and the thermal characteristic of the energy system, depending on the daily cooling/heating curves the Intelligent Controller calculates the parameters and timing of the intervention to achieve the desired condition.


Live data of an operating system can always be measured. The challenge is to record energy consumption data for a system (original system) without a Thermal Battery when the entire system is already affected by the Intelligent Controller (classic Heisenberg problem). This is required to plot energy usage charts with/without Thermal Battery and Intelligent Controller, "measuring" and visualizing what it would have been without the HeatVentors system.

We offer two options for this. The first and obvious is to supplement the new system with measuring instruments (heat and electricity consumption meters) and calculate and visualize the Delta based on the I/O data measured. The other is to measure and set up the behavioural characteristics of the new system before installation. Then periodically check the entire system during operation with ad hoc sampling days without Heatventors (switch Thermal Battery off) and adjust the characteristics. In this second case, the data “a priority” can be generated by interpolation to visualize the “without” graph and calculate savings data. Heatventors' interpolating Multipoint Stealth Algorithm is audited by external independent experts.


The Thermal Battery stores the digitized measurement data (1 minute sample rate). This is transferred via wireless connection to the Heatventors cloud-based system. The client partition created on the central server, stores data anonymously – each client having encrypted user access. Data flow analysis is used with Big Data algorithms to recognise user (unique), environmental (local), industry (global) characteristics.



Based on the data stream, the measured and interpolated data calculate the operating curve of the thermal energy system and calculate the energy data. The graphical interface shows the method and extent of savings in a simple, traceable "2 curve" diagram. From a business, marketing (CSR) and system operators’ perspective the figures are both easy to understand and to evaluate.


The on-site control panel provides full operational control. Central data is used for fine-tuning, self-learning algorithm development, recognition of overall trends, i.e. ability to analyse and make further precision adjustments to achieve maximum savings.


The data flow can also be accessed by the customer's building management system.



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