SANDY Forecast Service: Intelligent heating plan
Safe heating costs on a grand scale
Schools, offices and administration buildings of long past building years are presenting over average, high heating costs. Either old heating systems or outmoded insulation or inefficient and strictly scheduled thermostats contribute to a wasteful operation.
With the help of our “Intelligent Heating Plan” rooms are only being heated, if they are in actually use. It adapts fast to changing user behavior and makes essential cost savings possible without costly renovations.
Based on the established SANDY Forecast Service our “Intelligent Heating Plan” is simple, fast, and reasonably priced, also it is easy to integrate into existing systems because the service is reachable with a standard interface.
Product advantages in detail
Our “intelligent heating plan” is based on data of attendance sensors, which are triggered by movement and acoustic. As a result a continuously custom user profile is created.
The used SANDY machine learning algorithms make the manual creation and care for heating plans obsolete. Continuous self-learning ensures actuality of user profiles and records unscheduled changes in room usage. This way you can offer your users the latest heating plans and make noticeable heating savings possible. Instead of time consuming inefficient manual planning a self-learning system is established. The heating plans are easy to integrate into your existing product through standard interface and can be used to automatically program heating controllers.
Many schools and other public and private commercially used institutions do not have intelligent heating controllers. At best the heating system is centrally controlled and temperature in all rooms is lowered at night. Even if there is a smart controller in use, it only regulates at set hours, it does not adapt dynamically to change. Actual use of certain rooms is being disregarded.
Figure 1 shows the temperature progression of a school classroom with a manual controlled heating system. Every row signifies the daily temperature flow during 24hours.
The heating of the classroom start at times of room use. The room is being heated starting at 6a.m. and ending at 8p.m., due to evening classes. The heating plan is set up for the entire week even on Saturdays classes take place, on Sundays the classroom is not being used.
It becomes clear, that the weekly temperature is around 22°C unaffected by weekdays, time or actual use.
Figure 2 displays temperature progression with intelligent heating of the class room under consideration of the “Intelligent Heating Plan”. The heating of the room now starts later than before and depending on the scheduled first class either at 8a.m. or 9:30a.m..
In addition, it managed to single out days where the room is not being used after noon. The heating plan then adjusted the heating pattern automatic and also matched the pattern of the one evening class to its actual duration until 9p.m..
As it turns out the room is used differently than planned on the weekends as well, as at Saturdays the room is not being used and does not need to be heated at all. The intelligent heating plan reduced the times of heating for this room by 15% and saved about 30% of energy.
› Smart mome companies
› Heating technology producers
› Energy management System providers
› Energy contractors
› et al.
Added value for your customer
› Heat is used in a modern and automatic way
› Reduction of energy consumption and costs, since rooms are heated only if used
› Preheating moment is constantly matched through automatic learning
› Adjustment of heating plan by continuously and automated learning, even if room usage changes.
› Explicit increase of comfort since creating and adjusting manual heating plans is no longer required
Added value for your company
› Expanding your business portfolio with key accounts since larger buildings of companies and administrations can be served
› Increase of customer satisfaction and loyalty
› Fast, easy and cost-efficient system integration
› All benefits of “software as a service”, i.e. High availability, automatic updates, no maintenance
› No utilization of user sensitive data necessary
› Flexible scaling with growing customer base
› High security by using safe and encrypted interfaces
›Communicates over RESTful API
-sensor thermostat data measures attendance with motion or sonic sensors
-optional: incorporation of holidays school breaks
-live operation: individual heating plan on basis of room specific use
-encrypted data transfer with HTTPS
-individual authorization API-key
-steady operation in Microsoft Azure Cloud
› Kommunikation über eine moderne RESTful-API
– sensorische Daten zur Anwesenheitserkennung, beispielsweise durch Bewegungsmelder oder Schallsensoren
– optional: Berücksichtigung von Feiertagen und Ferien anhand der Postleitzahl
– individueller Heizplan auf Basis raumspezifischer Nutzung
– verschlüsselte Datenübertragung über HTTPS
– Autorisierung über individuellen API-Schlüssel
– zuverlässiger Betrieb in der Microsoft Azure Cloud
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